Adaptive Lifelong Learning for an
Inclusive Knowledge Economy

The Calhoun Center for Higher Education Innovation
Virginia Tech Publishing
The International Academic Forum
Future Talent Council

Copyright © 2020 Virginia Tech
Individual chapters © 2020 respective authors
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First published 2020 by the Virginia Tech Calhoun Center for Higher Education Innovation in collaboration with The International Academic Forum, Future Talent Council, and Virginia Tech Publishing.
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DOI: https://doi.org/10.21061/adaptive-learning-report
Suggested Citation:
Calhoun Center for Higher Education, Virginia Tech. (2020). Adaptive Lifelong Learning Report for an
Inclusive Knowledge Economy. doi:https://doi.org/10.21061/adaptive-learning-report
Graphics and illustrations: Olivia Menezes

Adaptive Lifelong Learning for an
Inclusive Knowledge Economy
List of Co-Authors and ParticipantsThis report was compiled by 60 co-authors and contributors engaged with adaptive lifelong learning
across different sectors. The team worked together remotely over 12 months and also met for a twoday, in-person workshop in October 2019. Starting in August 2020, the report will be further developed
through working groups with different learning communities and stakeholders.
Amy Arnold, Virginia Tech

Eta Nahapetian, Fairfax County

Andrew Lindsey, Alpha Corporation

Feng Hou, Maryville University of St. Louis

Andrew McCoy, Virginia Tech

Glen Holmes, Virginia Tech

Anne Khademian, Virginia Tech

Jared Keyel, Virginia Tech

Barbara Lockee, Virginia Tech

Jeff Garrett, Brookville High School

Carol Adams, University of Lynchburg

Jenna Joo, Ithaka S+R

Catherine Amelink, Virginia Tech

Joel McPhee, Bank of America

Chip Blankenship, Virginia Tech/UVA/GEJohn Boyer, Virginia Tech

Christopher Glover, Beacon of HopeJohn Flato, Future Talent Council

Chrystal Harris, An Achievable Dream

Jonothan Lister, An Achievable Dream

Clayton Hoyle, Journeys

Joseph Haldane, IAFOR

Colin Potts, Georgia Tech

Julie Greenwood, Arizona State University

Dale Pike, Virginia Tech

Karen Eley Sanders, Virginia Tech

Dale Whittaker, University of Central Florida

Karla Bruce, Fairfax County

Daniel Kjellsson, Future Talent Council

Kate Lindsey, Alpha Corporation

David Hare, GE Appliances

Kimberly Carlson, Virginia TechDavid Tegarden, Virginia Tech

Kristin Wingfeld, Academies of LouisvilleDavid Tinapple, Arizona State University

Laura Hamilton, Beacon of HopeDavid Ucko, Museums+more LLC

Lisa McNair, Virginia TechManny Contomanolis, Northeastern University

Scott Weimer, Virginia TechMark Kamlet, Carnegie Mellon University

Shahabedin Sagheb, Virginia Tech

Marsha Semmel, Marsha Semmel Consulting

Shari Garmise, APLU and USU

Matthew Holt, Virginia Tech

Sherrell Ashburn, An Achievable Dream

Michael Richey, The Boeing Company

Sylvester Johnson, Virginia Tech

Mukul Kumar, Hult Business School

Taran Cardone, Virginia Tech

Nene Spivy, Children’s Science Center

Todd Nicewonger, Virginia Tech

Owen Cardwell, University of Lynchburg

Tom Martin, Virginia Tech

Rachel Holloway, Virginia TechTom Quick, GE Appliances

Randy Swearer, Autodesk

Thanassis Rikakis, Virginia Tech

Ralph Hall, Virginia TechThomas Skuzinski, Virginia Tech

Rebecca Clark-Stallkamp, Virginia Tech

Virginia Tech Student Participants: Alicia
Gendell, Ariel Carter, Golder Baah, Mimi Dang,
Sabrina Chin, Taha Shaikh

Robert Mazer, Smart City Works
Robert Smith, The Boeing Company
Roger Reynolds, University of California San
Diego Scott Bess, Purdue University

Workshop facilitator: Tom Martin

Workshop Sponsors
The following Virginia Tech organizations supported the workshop and work on this report:
The Calhoun Center for Higher Education Innovation
The Center for Humanities
The Institute for Creativity, Arts, and Technology
The College of Agriculture and Life Sciences
The Pamplin College of Business
The College Access Collaborative
The Office of the Vice President for the National Capital Region

Report Co-Publishers
The publishing and dissemination of this report is a collaborative effort of:
The Calhoun Center for Higher Education Innovation
Editors: Thanassis Rikakis, Jared Keyel, Amy Arnold
Co-editor: Rebecca Clark-Stallkamp
Graphic Design: Olivia Menezes
The International Academic Forum (IAFOR)
Editor: Joseph Haldane
Future Talent Council (FTC)
Editors: Daniel Kjellsson and John Flato
Virginia Tech Publishing
Editors: Peter Potter, Robert Browder, Lauren HoltCONTENTS
EXECUTIVE SUMMARY	2

INTRODUCTION	7

Authors: Jared Keyel, Anne Khademian, Thanassis Rikakis
Contributors: Sylvester Johnson, Lisa McNair, Joseph Haldane, John Flato, Catherine Amelink

CHAPTER I: The Integrative Professional and Personal Development
Model (IPPD) and 21st Century Knowledge

13

Authors: Amy Arnold, Thanassis Rikakis
Co-authors: Jared Keyel, David Tegarden, Kimberly Carlson
Contributors: Robert Smith, Brock Avery
1.1 Lifelong Learning Needs in the 21st Century Economy 13
1.2 Higher Education Evolves 17
1.3 Meeting the Talent Demand Through On-ramps

19

1.4 Integrative Professional and Personal Development Model

22

1.5 Characteristics of Integrative Development 29
1.6 Collective Responsibility for Integrative Professional and Personal Development 32

CHAPTER II: Adaptive Approaches to Integrative Professional andPersonal Development

37

Authors: Thanassis Rikakis, Kim Carlson, Jared Keyel, Owen Cardwell
Co-authors: David Tegarden, Randy Swearer, Barbara Lockee, Feng Hou, Glen Holmes, Syvlester
JohnsonContributors: Taryn Cardone, Mark Kamlet, Dale Whittaker, Colin Potts, Amy Arnold, John Boyer, Tazio
Grivetti, Chip Blankenship, Michael Richey

2.1 Adaptation and Integrative Development 37
2.2 Co-Creation Approaches to Learning38

2.3 Understanding Learners’ Personal and Relational Knowledge 42
2.4 Moving From Fixed Courses and Curricula to IPPD-based Adaptive Learning Platforms 43
2.5 Technological Tools for Aiding Adaptation

49

CHAPTER III: Adaptive Learning Pathways: Examples from Higher
Education, Industry, and Across Sectors

59

Authors: Rebecca Clark-Stallkamp, Shari Garmise
Co-authors: Thanassis Rikakis, Amy Arnold, Jared KeyelContributors: Andrew McCoy, Chip Blankenship, Colin Potts, Chrystal Harris, David Hare, Jena Joo, Julie
Greenwood, Kristin Wingfeld, Manny Contomanolis, Marsha Semmel, Mukul Kumar, Randy Swearer,
Robert Smith, Scott Bess, Sherrell Ashburn, Tom Quick
3.1 Adaptive Pathways in Higher Education

60

3.2 Adaptive Pathways in Industry 64
3.3 Adaptive Pathways that Cross Sectors
3.4 On-Ramps and Off-Ramps

6572

3.5 Expanded Access and Reduced Cost73

3.6 Cross-sector, Learner-Centric Credentialing

74

CHAPTER IV: Point of Need Learning and Inclusive Learning Societies
Authors: Jared Keyel, Thanassis Rikakis, Anne KhademianContributors: Todd Nicewonger, Sylvester Johnson, Dale Whittaker, Michael Richey, Taryn Cardone,
Rebecca Clark-Stallkamp, Catherine Amelink, Ralph Hall, Matt Holt
4.1 Participatory Knowledge and Flatter Organizations

79

4.2 Communities of Integrative Learners as Pilots for Learning Societies 81
4.3 Point of Need Learning Platforms 84
4.4 Predictive Modeling of Practices Within an Inclusive Knowledge Economy 87

78

WORKING GROUPS	

93Group 1: From School, to Manufacturing Employment, to Lifelong Learning
Group 2: Adaptive and Integrative Learning in Global Academia

9394Group 3: Adaptive and Integrative K–12 Preparation in Underserved Areas—Trusting the Young
Learner 94
Group 4: Cross-Sector Summit on Adaptive Learning for an Inclusive Workforce at the Intersectionof Humans and Technology 94
Group 5: Integrating IPPD Adaptive Learning in Current Higher Education Structures—Calhoun
Discovery Program 95
Group 6: An Inclusive Workforce Development Workshop with Virginia Mayors—Focus on Industry
4.0 95
Group 7: Institutional Partnerships with Local Employers in Rural Settings

95

Group 8: Transdisciplinary Relational Knowledge for Integrative Development and Revaluing the
Humanities and Arts 96
Group 9: Towards a Point-of-Need Platform for Inclusive and Sustainable Industry 4.0

96

APPENDIX A: The Calhoun Discovery Program—A Pilot IPPD Curriculum

98

Author: Thanassis Rikakis
Co-authors: Lisa McNair, Shahabedin Sagheb, Alkan Soysal, Mike Kretser, Robert Smith, Neal Henshaw
Contributors: Michelle Kovac, Paul Knox, Paul Heilker, Tom Martin, Akshay Sharma, Lara Khansa, Mark
Embree, Sylvester Johnson, James Ivory, Anne-Lise Velez, Nikki Lewis, Luke Lester, Chip Blankenship,
John Tracy, Amy Arnold, Les Duffeld, Howard Haines

REFERENCES	108

RESOURCESThe Calhoun Center for Higher Education Innovation will host an iterative, online repository of examples, case-studies, and pilot programs related to the themes and practices explored in this report.
These resources provide greater detail and context to a number of ongoing adaptive, lifelong learning projects that expand on the recommendations of the report and will inform the working groups.

Authors will continue to add and update their contributions, which can be found at: https://honorscollege.vt.edu/cdp/Report/Resources.html•

KY Federation of Advanced Manufacturing Education (FAME) (David Hare)•

Adaptive Professional Development at GE (David Hare)•

The Academies of Louisville (Kristin Wingfeld)•

A Discussion of Ken Wilbur’s AQAL Model (Owen Cardwell)•

A Pilot Study of an Experimental, Multimodal-Curricular Design (Kimberly Carlson, Buzz Williams, Thanassis Rikakis)•

The Myers Lawson School of Construction Cross-sector Curriculum (Andrew McCoy)•

Calhoun Discovery Program Assessment (Lisa McNair)•

Industry 4.0 for Sustainable Development Lab (Jared Keyel)•

Blockchain Revolution (Feng Hou)•

Modularizing the World: Redesigning World Regional Geography into Multiple Mini-Courses Format (John Boyer)•

Transdisciplinary Relational Contexts for Adaptive and Inclusive IPPD (Thanassis Rikakis, Sylvester Johnson, Roger Reynolds)•

Working through Differences: An on the ground exploration of the socio-cultural experiences offaculty and staff engaged in campus-wide, cross-disciplinary collaborations in higher education(Todd Nicewonger)

Executive Summary

﻿

EXECUTIVE SUMMARYI

n January 2019 the Calhoun Center forHigher Education Innovation at Virginia Tech launched a multiyear project designed to explore the connections between adaptation and inclusiveness in learning. Our thesis wasthat a full-fledged commitment to adaptive learning has the potential to diversify the emerging
knowledge economy while also making it more
inclusive. Moreover, increased diversification andinclusiveness can enhance socioeconomic sustainability and enable our society to engage all pertinent voices when approaching complex problems.

•Stage 1: Record emerging practices in a preliminary report and discuss them during a twoday workshop in Washington, D.C. (March
2019–October 2019)•

Stage 2: Synthesize the outcomes of the research and discussions into a report that summarizes emerging practices and provides anagile framework of recommendations for further development of adaptive and inclusive
lifelong learning. This report concludes thesecond stage. (November 2019–August 2020)

To test this thesis, we first explored an adaptive and inclusive approach to defining what wemean by learning and knowing. A dynamic definition allowed us to then openly explore adaptation
to specific aspects of learning including: i) How islearning realized? ii) When is learning delivered?
iii) Who is included in learning?

•

Stage 3: Launch working groups to further
explore and test the recommendations of thisreport. These working groups can be found at
the end of this report. They are launching inAugust 2020 and are open to participation byentities and individuals interested in the project. (August 2020–August 2021)

Our first step was to bring together 60 individuals, each with significant direct experience withadaptive learning. These individuals came from30 different organizations representing a range ofsectors: higher education, K–12 education, industry, and non-profit. Together, we collaboratively
developed a three-stage plan:

While implementing the second stage of our
project, a number of world events intervened,
which only served to amplify the urgency of our
mission. One such event, COVID-19, is alreadyshowing the speed with which scientific andtechnical knowledge can be developed, shared,
and advanced as never before. This, of course,2﻿

has profound implications for the developmentof life-saving treatments. At the same time,
COVID-19 has laid bare the social disparities inherent in 21st century socioeconomic structuresand highlighted the challenges we face as a society
in coordinating the handling of complex issues.
Entire segments of the population are effectively
excluded from participating in, and reaping thebenefits from, the knowledge-based economy. Individual achievement is being disconnected fromsocial progress. What is clear is that we must do amuch better job of bringing together diverse individual perspectives and experiences if we expect
to produce collective action that is both wise andequitable.

ed knowledge, learning preferences, and pathways
will also be unique. Adapting our learning practices to fit diverse needs and experiences will
increase our capacity to be inclusive. Inclusive
participation will benefit all learners as they discover how to engage with multiple perspectives.
Over time, learners will come to value, leverage,
and embody difference, which in turn will makethem agile learners with the ability to intuitively
combine their expertise with the diverse expertiseof others, and structure collective intelligence foraddressing complex societal tasks and challenges.
In Chapter I we review literature that establishes adaptive development of domain-specific,
domain-general, and life skills as key to training diverse, versatile learners for a collaborative
21st century economy. Learners who develop all
three layers of skills in an interconnected fashion are able to transfer knowledge across different relational contexts. This in turn enables themto connect their diverse experiences to multiple
professional pathways and collaborative contexts,
as well as adjust their stock of skills to changing
workforce needs.

This report begins with an introduction that defines our meaning of inclusive knowledge and explains how our proposed definition expands someof the traditional understandings of knowledge.
First and foremost, we conceptualize knowledge
not as a fixed product or outcome—something
stored in our brains, computers, books, or institutions that we access as needed. Nor do we separate the mind (cognition) from the body (action).
Rather, we see knowledge as inclusive, dynamic,
and evolving. This report takes a knowledge inaction approach where knowledge is an emergent,
pragmatic, situated, and historical process that ispracticed collectively in the classroom, on the job,in the neighborhood, on the road, on the internet,
and at home.

Chapter I also highlights several organizations
that have developed agile training frameworks inan effort to address 21st century proficiencies. In
some cases, organizations are also providing onramps for nontraditional learners who may be underor unemployed. A key takeaway is that co-creation
processes enable learners who are at risk of being
left behind to acquire integrative multilayer skills
that are needed in the 21st century economy.

Our understanding of knowledge in action as
relational comes from the fact that knowledge exists in many different contexts, and those contexts
vary from one individual to the next. To have relational knowledge, we also need to account for
personal knowledge; active and embodied knowledge-making by individuals. Because human beings have unique life experiences, their accumulat-

Chapter II focuses on ways to adapt existing
best practices to better serve the needs of learners as they develop and expand their multilayer
skills across professional and personal contexts.
As we explain, educators and employers must firstacknowledge that learners already possess unique3﻿skill sets that simply need to be tapped into. Educators and employers must then find creative ways
to partner with learners, enabling them to connect
existing skill sets and aspirations to future career
pathways and acquire the additional skills necessary for these individualized pathways.

across institutions. We show how these programs
are mobilizing people to learn whenever and however they require it regardless of barriers that may
exist at the individual, social, or cultural levels.
We also consider new approaches to cross-sector
learning and credentialing that increase access andreduce cost while allowing for the learning record
to stay with the learner rather than with the institution.

The way we propose to facilitate this partnering is to structure learning experiences as networksof short modules that utilize different learning modalities and connect through multiple pathways
to allow learners to develop skill proficiency andconnectivity precisely when it is needed and in
the most efficient customized manner. Structuring
pathways of short modules allows just-in-time information to emerge in the course of learning suchthat a learner’s pathways can change and evolveto reflect the new situation. Utilization of different
learning modalities (e.g., experiential, theoretical,
in-person, asynchronous, blended, etc.) helps toaddress the needs of a truly diverse body of learners and cover the full range of knowledge types.
We conclude the chapter by discussing a numberof existing and emerging technological tools andtechnology-assisted processes that facilitate adaptive learning. These include intelligent/cognitive
tutors combined with interactive content; the Internet of Things and paired technologies such as
augmented/virtual reality and robots for embodied
interactive learning; and multidimensional data
analytics for assessment of progress and adaptation of learning.

In Chapter IV we propose advancing inclusive and integrative adaptive learning throughcross-sector cooperative communities organizedaround transdisciplinary themes of societal impact. As envisioned, these communities value andengage all aspects of knowledge in action, rely on
inclusive and non-hierarchical participation andpromote integrative, multilayer skill development
for all participants. We further propose expanding
these communities by developing Point of Need
Learning Platforms (PNLP) that allow diverse
learners to explore the mapping of their existingskills to current and emerging training and employment pathways. PNLPs provide efficient individualized pathways for immediate learning needs
while guaranteeing that learning is transferable toother contexts and situated within integrative professional and personal development. PNLPs contain interconnected, modular content that has beendeveloped by all participating sectors and that accommodates all types and levels of learning need.
Many of the modules integrate multi perspective
learning and bring diverse learners together to explore complex problems. PNLPs use high dimensional analytics to continuously adapt to societal
and individual needs and provide a lifelong learning record owned by the learner.

In Chapter III we survey a number of adaptive
learning programs currently being implemented
in academia, industry, and communities. As weshow, these programs are increasing access tolearning by employing multiple delivery modalities, alternative cost structures, holistic support
mechanisms for diverse learners, transferability oflearning, and transparency of learning outcomes

PNLPs can be developed by adopting, experimenting with, and evolving many of the recommendations presented in this report. The model of4﻿

institutional change proposed in this report is theresult of integrative discourse between a radical
paradigm shift—inclusive transdisciplinary communities supported by PNLPs—and the gradualchange processes embedded in existing institutions.

learning professionals working in and across sectors (K–12, Higher Education, Industry, etc.). Taking place in the second half of 2020 and Spring of
2021, the groups will collect more information on
emerging adaptive learning practices and engage
participants in reflexive dialogue on their experiences with various learning models and approaches. The insights gained from these groups will beanalyzed and incorporated into a draft of a crosssector PNLP for Industry 4.0 and Sustainable Development. The findings of the working groups
will also be presented in a digital book publishedby Virginia Tech Publishing at the end of 2021.

Appendix A summarizes the Calhoun Discovery Program (CDP) at Virginia Tech. The
CDP focuses on the development of versatileand collaborative lifelong learners through adaptive and integrative training of domain-specific,
domain-general, and life skills. The learning isembedded in cross-sector transdisciplinary communities focused on sustainable and equitable socio-technical innovation.

We thank you for reviewing this report andwelcome questions and suggestions as well as
inquiries for participation in the working groups.
Please contact us at cchei@vt.edu.

In closing the report, we propose the establishment of nine Working Groups with learners and5Introduction:
Inclusive Knowledge in Action

INTRODUCTIONINTRODUCTION
Authors: Jared Keyel, Anne Khademian, Thanassis Rikakis
Contributors: Sylvester Johnson, Lisa McNair, Joseph Haldane, John Flato, Catherine
AmelinkT

his report addresses the globalized
knowledge economy in the 21st century; not only as it exists today, but theknowledge economy needed to meet the demandsof tomorrow. This report proposes that in order for
our knowledge economy to grow and be sustainable, it must be inclusive in ways that enable it toadapt to—and incorporate within it—the personal and professional growth of a large and diverse
body of lifelong learners. In this introduction, we
first define what we mean by inclusive knowledge
and explain how our proposed definition expandssome of the traditional understandings. We thenshow that an expansive and dynamic conceptualization of knowledge increases inclusion and promotes lifelong adaptive learning as a mindset anda practice.

knowledge in exclusionary ways. Top-down practices represent knowledge as discrete components
of information, disciplinary-based, and siloed interms of what individuals need to know, what constitutes expertise, and where they learn—such asclassrooms and workplaces. This means that our
traditional understanding of knowledge has been
defined in terms of cognitive expertise developed
and acquired through education, reading, and research that is largely held and protected by practicing professionals and degree-granting institutions.
In a similar fashion, we have come to view
the organizations that make up the educational
enterprise as repositories of knowledge and expertise tailored to a specific mission or mandate.
Knowledge is often considered a product thatorganizations can have and that is stored withindomain-specific databases, procedures, and protocols. In the higher education sphere, students enter schools and colleges to acquire specific subject
matter knowledge that is organized according tovarying levels of specialization. Students are tested at each level to ensure mastery of the knowledge, from which they ultimately move on, degrees in hand, ready to work in jobs that align withthe specific knowledge they have acquired.

Inclusive Knowledge in Action
The way we learn and know in today’s world isdeeply shaped by the informational and relational
practices of educators and decision-makers acrossthe educational enterprise. This begins in K–12
schools and continues through higher education,
on-the-job training, and continuing professional
education. Within the established educational enterprise, longstanding learning practices approach
7

INTRODUCTION

In contrast to such understandings, this reporttakes a knowledge-in-action approach (Argyris &Schön, 1978; Dewey 1933; Polanyi, 1958; Schön,1983). Rather than conceptualize knowledge as afixed product or outcome—something stored inour brains, computers, books, or institutions that
we access as needed—and rather than separate themind (cognition) from the body (action), we believe it is important to see knowledge as inclusive,
dynamic, and evolving. Knowledge in action is an
emergent, pragmatic, situated, and historical process. It is practiced collectively in the classroom,on the job, in the neighborhood, on the road, on theinternet, and at home.

Knowledge in action is an
emergent, pragmatic, situated,and historical process practiced
collectively in the classroom, on
the job, in the neighborhood,and at home.

A fundamental component of knowledge inaction is tacit knowledge that has been acquired
through experience (Polanyi, 1958) rather thanabsorbed through verbal explanation or written
form. Existing exclusive meritocratic approaches
have largely ignored or overlooked expertise andknowledge that is acquired through our day-today activities—in business, in school, on the bus,
playing sports, painting, or cleaning at home. Yet,anyone who knows the best driving routes acrossa city, the safest schools and best teachers, the experience of troubleshooting home computer network issues for friends and family, or the tactics
to catch a particular kind of fish has tacit knowledge. Knowledge in action involves synergistic
interactions of explicit, implicit, and tacit knowledge (Polanyi, 1967; Reber, 1989) combined withintegrative cognitive, psychomotor, and affective
learning (Anderson & Krathwohl, 2001).

2014). When considered in these contexts, knowledge is not a set of rational, discoverable facts thatcan be neutrally applied to test an idea, do a task,
or solve a problem. In fact, what we know cannot
be distinguished from how we know it (Polanyi,1958) or from the multiple interactions that givemeaning to information. To have relational knowledge, we also need to account for personal knowledge—active and embodied knowledge-making
by individuals. Individuals accumulate knowledge
differently based on their mode(s) of participation,
preferences, situational contexts, and goals. Each
person brings the totality of the knowledge they
have acquired across many different contexts to
any new learning situation. To structure effective
learning, we need to recognize that comprehensive personal knowledge accumulates in the person rather than the formalized curricula. Because
everyone has different life experiences, their accumulated knowledge will be diverse, and theirlearning preferences and pathways may also be
multiple. To include everyone and allow everyone
to develop most effectively, adaptation of learning
is imperative.

Knowledge in action is also relational andpersonal (Dewey 1933; Dourish, 2001; Polanyi,1958). To understand knowledge as relational is toemphasize the importance of the historical, social,technical, cultural, and economic contexts in whichknowledge is situated (Coghlan & Brydon-Miller,

If we focus solely on knowledge as an outcome, we end up with clusters of knowledge defined by particular understandings of the world.
This, in turn, leads to pre-set paths to expertisethat invariably limit other possible paths that areotherwise able to emerge in adaptive situations.
8

INTRODUCTION

Heterogeneous groups can achieve global maxima
and transformative change, but the connectivity ofthese groups is highly challenging (Eagle, Macy,& Claxton, 2010). The interrelation of dynamic
personal knowledge of lifelong learners and thediverse collective intelligence of learning societies may hold the key to solving this problem.
Adaptive learning practices that address diverse,
personal knowledge needs can promote inclusive
participation.

Knowledge in action isrelational and personal. It
involves active and embodied
personal knowledge-making by
individuals in multiple contexts.
Such is true with disciplinary sets of scientificrules about the physics of the universe, homogeneous understandings of the relationship betweensocial services and human behavior, and collective
understandings of national identity. In this context,
knowledge, beliefs, and convictions are seen as agiven, set in stone, requiring compromise and negotiation to navigate differences, or the give andtake of academic investigation and deliberation
to make incremental adjustments. Alternatively,
when we understand collective meaning as a wayof knowing, the relational, diverse, and enacted
nature of knowing comes to the fore, with opportunities for continuous adaptation and formulation of new ideas, techniques, and approaches.
A pluralistic and dynamic knowledge-in-action
discourse resists the creation of static knowledge
structures and permanent hierarchies of knowledge
power. In fact, by its very nature, this discourse isdeconstructive. In view of these characteristics, itis perhaps more useful to understand knowledgein action not as a fixed outcome but as an active
system of multiple ways of knowing that are dynamic and engage a multitude of process-productpermutations.

This results in diverse relational contexts for
all participants and encourages participants toembody difference. Learners that can embody
multiple points of view become aware of the fullcomplexity of societal problems and the need forcollaborative approaches to complexity. Memberswith diverse expertise can then coalesce aroundcomplex societal tasks and challenges and share
their knowledge intuitively with one another, including less experienced members, resulting incollective intelligence. This promotes the empowerment and mobility of individuals within
and across organizations, and mitigates the loss oforganizational memory (Harnecker, 2007). Collective intelligence also facilitates a flatter professional pyramid since the “expert” is a dynamic
notion that emerges from context (Guattari, 1972).
For example, while an experienced medical doctor
might lead in making diagnoses, an experienced
nurse or physical therapist might be most effective in promoting participatory health for patients(Sepkowitz, 2020). Collective intelligence canthus be conceptualized as a complex ecosystem
where instructors are also learners and diverse
participants inform the continuous adaptation of
personal and relational knowledge. This, in turn,enables participants, as a group, to successfully
navigate complex tasks and facilitate recovery
from disruptions or systemic failures (Hutchins,1995). As these intelligence ecosystems grow they

Connecting highly individualized ways ofknowing to collective ways of knowing is an ageold challenge. Institutional standardization cancircumnavigate this issue by advancing homogeneity of collective knowing but homogeneousgroups get stuck on local maxima (Page, 2007).
9

INTRODUCTION

time (Whitney, 2010). The initial creation of universal primary and secondary education, for example, was a leap forward for inclusion. In the
United States in the late 19th century, the Morrill
Acts framed public education as a democratizing
force in society by allowing for greater access tohigher education for diverse populations (Geiger,2015). These acts also allowed for the creation ofland grant universities, like Virginia Tech, that attempted to expand education to new students andsubjects. Efforts to expand access and inclusion ofdiverse learners and knowledge have taken placethroughout the world. In the United Kingdom, forexample, institutions founded in the 19th century,
such as University College London and the London Mechanics’ Institute (now, Birkbeck College,
University of London), offered education to women and people from a much broader range of social
backgrounds. Birkbeck College began as a pioneerin adult learning as well. More recently, the Open
University was founded in the UK in 1969 with acommitment to modernization and growth in technological development. It was an early advocate
and practitioner of increasing access to education
through distance learning and was a precursor for
online learning that is now vital in a university setting.

The interrelation of lifelong
learners’ dynamic personal
knowledge and learning
societies’ diverse collective
intelligence may hold a key toconnecting the individualized tothe collective.
can promote the realization of learning societies
built upon the process of participation (UNESCO,
2008, 2019). Members of a learning society seek
to embody process-oriented creation and dissemination of knowledge. As a result, participation in
itself becomes a form of knowledge. We expectthat the creation, building mechanisms, and function of learning societies as institutions of democratic governance will help acknowledge andaddress wider racial, gender, and socioeconomic
inequalities (UNESCO, 2019).
Throughout history, educators have contemplated how to develop learning societies and rethink their approaches to the content and forms oflearning to increase accessibility and inclusivity.
Learning and education are inherently evolutionary; practices and approaches shift and respondto social, economic, and political changes over

Like these earlier iterations and efforts to expand educational opportunities, we are proposing
an adaptive approach to learning with the poten-

Figure I:

Four Key Dimensions of Inclusive Knowledge Presented as Expansive Continua
Outcome-focused

Process-focused

Institutionalized

Personal

SegregatedIntegrative

Standardized

Adaptive

10INTRODUCTION

tial to create vastly more inclusive and accessible
learning possibilities that leverage knowledge inall its dimensions. Rather than seeing differences
as polarizing binaries (i.e., outcome focused vsprocess focused), adaptive learners and learning
societies can explore the full space between thetwo notions, thus moving from the binary categorization to expansive continua (Dewey, 1906,
1933; Xenakis, 1971). In Figure I, we present,
as continua, the four key dimensions of inclusive
knowledge discussed in this introduction.

tate the engagement and growth of different typesof knowledge, and societies adapt to value andembrace the diverse personal knowledge of theirmembers. Prior personal and relational knowledge
becomes highly transferable to many new typesof contexts and becomes stronger and deeper posterior knowledge (Tenenbaum et al., 2011). This
deep inclusion and (re)valuing of a vast array ofknowledge modes and practices increases a society’s human capital (Spence & Hlatshwayo, 2011).
Consequently, those societies are able to findmulti-perspective solutions to complex problems
that promote socioeconomic sustainability (Morrar, Arman, & Mousa, 2017). Knowledge becomesa “powerful tool for taking action” to “deepen democracy and to struggle for a fairer and healthierworld” (Hall & Tandon, 2017, p. 13).

When we value the full spectrum of knowledge, adaptation becomes both a mindset and amechanism. Individuals adapt in ways that enable
them to engage and embody many different typesof knowledge. Learning structures adapt to facili-

11Chapter I:
The Integrative Professional andPersonal Development Model (IPPD)
and 21st Century Knowledge

CHAPTER I

CHAPTER I

The Integrative Professional and Personal Development
Model (IPPD) and 21st Century Knowledge
Authors: Amy Arnold, Thanassis Rikakis
Co-authors: Jared Keyel, David Tegarden, Kimberly Carlson
Contributors: Robert Smith, Brock AveryIn this chapter, we lay the foundation for theremainder of the report by establishing thebasis for the claim made in the introduction,that a new framework for learning and training isnecessary to meet the knowledge requirements ofthe 21st century. Definite socioeconomic changes are
influencing the global economy, and our society is
at risk of not having the human capital or adaptive
ability to navigate them. We show that sustainablegrowth of human capital requires integrative andcontinuous development of a wide range of skills tailored to the diverse interests, abilities, and capacitiesof each learner. We survey emerging frameworks oflearning and training throughout higher educationand industry that aim to address these needs. Finally,
we propose a new model for Integrative Professionaland Personal Development (IPPD) comprised of two
main components, personal knowledge and relational knowledge. The personal knowledge is organized
as a three-layer hierarchy: life skills, domain-general skills, and domain-specific skills. Diverse and dynamic relational knowledge provides the context forthe development of integrative personal knowledge.

in the midst of major structural change. The most notable change is the shift from tradable sector jobs tomore non-tradable sector jobs. According to Spence and Hlatshwayo (2012), in the years leading up
to the 2008 recession, 97% of employment growthoccurred in the non-tradable sector—largely jobs ingovernment, health care, and retail. Non-tradablejobs are jobs performed by a domestic workforce
creating goods and services that cannot be tradedinternationally (Hlatshwayo & Spence, 2014; Spence & Hlatshwayo, 2012). Economists caution thatgrowth in the non-tradable sector cannot continue
forever. Standing in the way are restraints on government budgets, reduced public sector spending,and high levels of consumer debt (Spence & Hlatshwayo, 2012).
The story is different when it comes to the tradable sector—that part of the workforce producing
goods and services that can be traded internationally—e.g., manufacturing, information processing,mining, etc. In the US, the tradable sector has actually seen net contraction. The only real growthhas been in high-income occupations such as consulting, computer systems design, finance, and insurance. These occupations face competition fromindividuals performing the same occupations in other countries (Spence & Hlatshwayo, 2012). In an

1.1 Lifelong Learning Needs in the 21st Century
EconomyIt is no secret that the American labor market is13

CHAPTER I

effort to address the expected slowed growth in the
non-tradable employment sector and contraction/
income inequality in the tradable sector, a dynamic response is required that emphasizes growth ofhuman capital.

Expected slowed growth in
the non-tradable employment
sector and contraction in the
tradable sector of the economy
requires a dynamic response ingrowing the human capital.

Following Spence and Hlatshwayo’s (2012)
recommendation of increasing human capital, it
is important not to overlook social issues. One ofwhich is the lack of access to the essential knowledge and educational tools that are necessary not
only to survive in the 21st century economy but toimprove learners’ lives and develop to their full
capacities (World Economic Forum, 1990). Largesegments of the current and future global workforce are either excluded or left behind. For example, 70% of the world’s poor reside in Sub-SaharanAfrica (World Data Lab, 2019), and the majorityof this population is under the age of 25 (Coulibaly, 2019). The learners of this region need bothaccess to knowledge as well as greater economic
opportunities for employment. Everyone, regardless of their sex, gender, religion, or geographic
background, has the right to learn (UNESCO,
2000, 2019).

the knowledge economy means rethinking current
practices that exclude a vast amount of existing
human capital. Fundamentally, thought leaders
and institutions of trust must develop ways to connect the economy to this human capital, instead ofconnecting human capital to the economy. Focusing on the needs, diverse interests, abilities, andcapacities of lifelong learners may be the first step
toward influencing such a shift.
Furthermore, any effort to connect the economy
to human capital must be progressive rather than reactionary. Currently, smart factories, artificial intelligence (AI), and automation disrupt the status quo(Muro et al., 2019). The needs of learners change asa result of these disruptions, which in turn requiresthat knowledge dissemination practices change.
In fact, those responsibl for providing additional
knowledge and greater access must continuously
adapt their methods of dissemination on behalf oflearners that face challenges to successfully navigate these economic and technological shifts. For
learners to thrive in an environment facing constantdisruptions by machine learning, artificial intelligence, and future unknowns, institutions of trust
will need to re-conceptualize training by focusing
on the development of all types of human skills
over a lifetime rather than idealizing preparation tobe centered on a single career and limited to performing specialized tasks within one discipline.

In practice, this requires universal access to
the knowledge economy as well as a basic recognition and valuing of all ways of knowing. Developing an inclusive definition of knowledge andInstitutions of trust will needto reconceptualize training
to encompass a more holisticcompetence model enabling alearner to thrive over a lifetimeof constant disruptions anduncertainty.

14

CHAPTER I

Table 1.1

Comparison of Machine and Human Expertise

Adapted from Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises
and implications for teaching and learning. pp. 24–25.
According to economist David Autor (2015),
programmers attempting to replace the tasks performed by humans with machines face immense
challenges when it comes to more abstract andnonroutine categories. Similarly, economists at
MIT in quantifying the effects of automation
and AI on employment and wages, conclude thatlearners who possess nonroutine cognitive skills
such as flexibility, problem solving, and complex
communication face less threat from automation
than those who perform routine cognitive tasks,
routine manual tasks, and nonroutine manual tasks(Autor et al., 2003; Autor & Price, 2013).

These governing bodies view such programs as
adequate responses to economic downturns andhope to address emerging gaps between industry’s
needs and the populations’ skill set. Such an approach is not without criticism (Coffield, 2000;
Popović, 2014; Rees & Bartlett, 1999b). One criticism is that it places the impetus on the learners
to acquire an adequate skill set rather than recommending the formation of partnerships to assist in
upskilling (Rees & Bartlett, 1999b). Another argument is with the naïve belief that improving thebasic skills of a population will resolve a nation’s
macroeconomic issues (Brown & Keep, 2000).
More education or training will not help someone
residing in a geographic region that lacks employment opportunities (Popović, 2014).

In the United Kingdom and European Union,
officials have a long history of investing in lifelong learning programs as a response to economic
issues (Popović, 2014; Rees & Bartlett, 1999b).

A philosophy of lifelong learning may be an
15

CHAPTER I

important first step on the path toward universal
access and equity if it engages comprehensively
all the types of knowledge embodied by learner and especially the less extractable, more-difficult-to-assess categories of tacit and implicit
knowledge (UNESCO, 2000). By focusing on
one’s knowledge in action (Polanyi, 1958; Schön,
1987), individuals become more valued (Rees& Bartlett, 1999) and self-actualized (Maslow,1968). Furthermore, lifelong learning needs toalso address alignment to opportunities specific to
one’s relational contexts (i.e., geographic region).

Lifelong learning will not solve anation’s macroeconomic issues.
systems of education do not fully meet the needsof the learners, their current and future employers or society as a whole (Banerji, 2007; National
Academy of Engineering, 2005; Flowers, 2009).
The resulting knowledge shortfall can be especially pronounced when learners lack the high-demand, transferable skills, such as communication,
collaboration, and problem solving that are criticalto the economy of the 21st century (Rhodes, 2019;
Snell et al., 2016).

Institutions of trust also have an importantrole to play in supporting individual learners in
the pursuit of lifelong learning programs (Popović, 2014; Rees & Bartlett, 1999b). The report
Robot-Ready: Human+Skills for the Future ofWork stresses the importance of educators, state
governments, and employers collaborating in aneffort to find a common language to describe (a)the totality of skills employers seek in composing
job descriptions and (b) how the learner knows
and applies the in-demand competencies of critical thinking and communication during their careers (Weise et al., 2018). Traditional training andlearning assessment mechanisms often disregard
learners’ tacit knowledge gained through experiences across every aspect of daily life. Instead,they focus on explicit knowledge within the classroom and prepare graduates to practice within thedomain-specific area of their chosen fields, withlittle regard for acquiring the “know-how” to perform within the context of a complex job (Eraut,1985) or a fast-evolving global society. This focus on explicit, domain-specific knowledge is aremnant from the second industrial revolution thatviewed learners’ socioeconomic needs being fulfilled by a single career focused on performing
a set of specialized tasks that evolved gradually.
In this often-disrupted economy, these traditional

An early foundational framework for understanding inclusive knowledge is Benjamin
Bloom’s taxonomy, which emphasizes three domains of learning: cognitive, affective, and psychomotor. The goal of this taxonomy is to create
learning opportunities to help promote change
in individual behaviors (Bloom, 1956). Cognitive learning focuses on the “amount and kind ofknowledge” that the student possesses (Bloom,
1956, p. 28). The affective domain focuses on “afeeling tone, an emotion, or a degree of acceptanceor rejection,” by which an individual learns andthen incorporates situational values (Krathwohl etal., 1956, p. 7). Finally, the psychomotor domain“emphasize[s] some muscular or motor skill, somemanipulation of material and objectives, or someact which requires a neuromuscular coordination”(Krathwohl et al., 1956, p. 7). As learners have experiences that engage these domains, they become
better equipped with skills to take on more complex challenges. The taxonomy shows this potential for growth by organizing each domain in risinglevels of competency. Many curricular programsuse Bloom’s taxonomy as a guide to developing
16

CHAPTER I

learning outcomes, with first- and second-year
courses using lower levels of the taxonomy while
third- and fourth-year courses focus on the higher levels. However, most traditional curricula develop learning outcomes that focus solely on the
cognitive domain (Senge, 1990). This approach iscounter to the well-established understanding thatknowledge in complexity is embodied, experiential and integrative (Dewey, 1938, 1966; Dourish,
2001; Hutchins, 1995).

skill to a widening scope of situations and experiences, gaining new competencies, building new
relationships, and assuming new roles,” whichmakes them adaptable learners, not generalists (p.
12).
Unfortunately, The T-shaped individual concept gradually evolved away from the original
concept of versatility. By 2006, Spohrer was calling for T-shaped individuals who acquire a greater
breadth of knowledge in addition to a deep knowledge in one discipline. Interdisciplinary programs
aimed at T-shaped learning, where the depth isassociated with the segregated discipline, arenow embedded in the majority of US Universities(Knight, 2013). Foundational education programs
that continue to associate depth of knowledge witha few specific subsets of personal knowledge failto acknowledge and leverage the relation of domain-specific and domain-general skills and theoverall dimensionality and differentiation of personal knowledge. It is our contention that the simplification of learning into an outcome-focused,discipline-specific specialization, combined witha loosely-related body of general knowledge,
contributes to the mismatch between learning
outcomes produced by higher education and theskills demanded by employers and required byour complex societal needs (Hart, 2015; Madrigal,2017). Furthermore, as societal problems become
increasingly more complex and dynamic, demand
for the full scope of personal and relational knowledge will continue to grow.

1.2 Higher Education Evolves
The need to update educational structures toaddress all types of human skills and their relation
to contemporary workforce needs has been predicted for over 30 years (Jantsch, 1972; d’Hainaut, 1986). In 1991, Guest introduced the conceptof the T-shaped individual as a variation of theRenaissance man: someone who develops generalizable skills by practicing across disparate specialization areas such as computing and music.
Guest’s (1991) definition of T-shaped individualsaligns with what Fadel, Bialik, and Trilling (2015)refer to as versatilists—learners who exhibit deep
knowledge in a range of subjects as well as thegeneralizable skills to transfer knowledge acrossthese domains. These learners “apply a depth of

Versatilists “apply a depth of skill
to a widening scope of situations
and experiences, gaining newcompetencies, building new
relationships, and assuming
new roles,” which makes
them adaptable learners, notgeneralists.

Several organizations are acting as thought
leaders by taking action to aid learners in their discovery, application, and continuous adaptation of
their full personal and relational knowledge withintoday’s knowledge economy. The following paragraphs illustrate a few examples of efforts underway:
17

CHAPTER I

The Coalition of Urban Serving Universities(USU) and the Association of Public and Land
Grant Universities (APLU) state in their 2019 report Delivering 21st Century Skills, that universities need to partner with industry leaders in orderto develop and continuously improve the curriculum. Both organizations call for innovation inmeeting the needs of individuals and society whenit comes to the evolving workforce. This means
focusing on technical, human, and social competencies in addition to the cognitive. The USU and
APLU also recommend changes in affordability
and more mobile credentials.

2). AACU’s Liberal Education and America’s
Promise initiative (LEAP) is responsible for thedevelopment of rubrics as part of leaders’ efforts
to connect the economy’s needs to a liberal education (Association of American Colleges & Universities, 2011).
Similar calls for changes in education appear
in current literature. For example, Joseph Aoun,president of Northeastern University, proposes a
new model called humanics, which he defines as“mastery of content as well as the development ofparticular skills” (Aoun, 2017, p.53). The purposeof this new model is twofold: (1) to enable learners’ comprehension of the continuously advancing
technological world that surrounds them, and (2)to enhance their ability to transcend that world
through acquiring robot-proof skills, such as creativity and mental flexibility. The author recommends greater skill sets under the headings of data,technological, and human literacies (Aoun, 2017).

The National Association of Colleges and Employers (NACE) annually surveys employers to
ask what skills they value most when hiring recent
graduates. In 2019, they rated the following skills
in order of importance: critical thinking/problem
solving; oral/written communications; teamwork/
collaboration; information technology application;
leadership; professionalism/work ethic; and career
management. Researchers at NACE also state thatthe way for undergraduates to differentiate themselves amongst their peers is to exhibit “outstanding credentials in a number of non-industry specific desired skill areas” (DuPre & Williams, 2011,p. 8).

The Lumina Foundation’s Degree Qualifications Profile (DQP) is a highly developed modelof bridging academia with the needs of the 21st
century workforce. At the time of its second iteration, over 400 colleges and universities haveadapted it. It aims to calibrate learners’ knowledge
and abilities per degree level by offering mechanisms for proving the learners’ ability to apply
what they have learned over the course of theircollege careers. While it does not standardize degrees, it does clarify the general proficiencies that
graduates need to achieve regardless of their fieldof study within the specific degree level, currently
covering associate’s through master’s. The DQP
also “assumes that general education and the major must work together” (Adelman et al., 2014, p.
10). The DQP serves different higher education
institutions as a tool to help shift from grades as amarker of performance to learners’ levels of pro-

The Association of American Colleges andUniversities (AACU) maintains a list of value rubrics that includes such skills as ‘’inquiry and analysis, critical thinking, creative thinking, written
communication, oral communication, quantitative
literacy, information literacy, reading, teamwork,
problem-solving, civic knowledge and engagement—local and global, intercultural knowledge
and competence, ethical reasoning and action,
global learning, foundations and skills for lifelong
learning, and integrative learning” (Associationof American Colleges & Universities, 2020, para.
18

CHAPTER I

Civic and Global Learning: As the name suggests, this proficiency is all about students integrating and applying their knowledge to create agreater impact across civic, social, environmental,
and economic challenges.

ficiencies. These proficiencies are organized into
five broad categories outlined below.
Specialized Knowledge: This area of proficiency concerns the learners’ subject field. While theinstitution may have certain proficiencies regarding the subject, there are also accrediting professional and licensing bodies that develop standards.
All fields usually require that this specialized
knowledge be recognized in the learner’s ability tocomprehend and apply terminology, theory, methodologies, literature, and solve complex problems
relating to the subject.

Inclusivity plays an important role for institutions of trust as they implement an integrative,
lifelong learning philosophy. To be of service requires that institutions of higher education broaden their scope to serve all learners regardless of
their life stage. Learners facing unemployment or
underemployment will not have the time or the resources (Dede, 2019) to dedicate to those traditional, explicit representations of knowledge acquisition such as degrees or certificates. Associations,non-profits, and educational institutions that truly
recognize this area of need will provide practicalframeworks for implementing change that closes
the gap between the competencies needed for mobility in this new economy and the existing knowledge repertoires of those learners already situatedin the workplace.

Broad and Integrative Knowledge: This areaof proficiency may include the learner’s area ofspecialization but, primarily, it incorporates learning across different fields. Rather than typicalgeneral education courses that are prescribed aspart of the curricula at most universities, the DQP
guides learners to explore, connect, and apply
broad learning concepts and methods across contexts and throughout their careers (Adelman et al.,2014, p. 14).

1.3 Meeting the Talent Demand Through Onramps

Intellectual Skills: This group of skills crosses
over many fields and domains. The skills of analytic inquiry, use of information sources, engaging
diverse perspectives, ethical reasoning, quantitative fluency, and communicative fluency interact
with the other areas of learning outlined in the
DQP.

Strada Institute (Weise et al., 2019) finds that32 million adults in the US are either underemployed or unemployed. This situation has growneven more dire due to the COVID-19 pandemic’s
influence on the economy. At the time of this report, an additional 29 million people had madefirst-time benefit claims for unemployment insurance during the Spring of 2020 (US Bureau of Labor, 2020). Many adults have less than two yearsof education and/or come from low-income environments. This means that they risk being left behind as technologies advance. The Strada Institutedraws attention to this problem with its On-ramps
to Good Jobs Report (2019). According to Strada,
on-ramps are “the leading edge of a new market ofApplied and Collaborative Learning: Students
exhibiting proficiency in this category use what
they have learned either individually or via groupeffort. They demonstrate their problem-solving
abilities across sectors such as the classroom,community, and work. Evidence of this proficiency might also be demonstrated by incorporating
the skills used in expertise within their field(s) ofmajor.
19

CHAPTER I

intermediaries connecting working-class adults tobetter economic opportunity” (Weise et al., 2019,p. 3). On-ramps focus on serving adults who areunable to seek a degree due to possible barriers
like finances, time, and childcare constraints while
matching them to employers wanting to use a morediverse talent pipeline.

nical workers in nuclear energy by partnering withindustry. By listening to the needs of employers,
he removed the college algebra barrier by creating
courses for students to learn only the precise algebra, trigonometry, and statistics skills necessary to
work within the field of nuclear energy. Membersof industry provide guest instruction in these mathclasses to provide the learners with real-world,
workforce application. The result has been a 90%
success rate in these courses that center on matching learners’ needs with specific industry needs(National Science Board, 2019).

On-ramps differ from other established programs that currently exist to educate and train
adults, namely those offered by community colleges, federal workforce programs, apprenticeships, and so-called last-mile providers such ascode academies (Weise et al., 2019, p. 12). Onramps align learners without traditional, four-year
degrees to high demand opportunities that requirebasic, technical, and human skill development.
Lasting anywhere from a few weeks to several
months, and occasionally as long as two years,
these programs not only offer intensive services
and training in areas such as reading and mathbut also, broaden learners’ human skills, including critical thinking, creative thinking, problem
solving, communication, teamwork, persistence,
self-efficacy, and professionalism. These programs also “hone high-demand, technical skills incomputer programming, information technology,
business and financial services, and cybersecurity”(Weise et al., 2019, p. 8). In 2019, Strada identified
65 on-ramps in the US. The report goes on to highlight nine successful on-ramps from non-profit organizations, for-profit providers, and workforce
boards. Some of these organizations even provide
post-placement support to aid the new employee
in confronting challenges and understanding how
not only to succeed but to advance in the new environment.

The World Economic Forum (WEF) makes
similar suggestions for action in the white paper
Accelerating Workforce Reskilling for the Fourth
Industrial Revolution (World Economic Forum,2017), which comes out of its “Shaping the Futureof Education, Gender, and Work” system initiative. This initiative aims to bring together governments, businesses, and other stakeholders so thatthey are better prepared to anticipate and manage
economic and industry transitions. One importantpart of this is workforce training. The first step is totake stock of individuals’ current skills repertoire.
Only after this step is completed, training is recommended based on each learner’s particular skill
set and the needs of the specific workplace. The
initiative recommends a consistent feedback loop
between industry and educational institutions for

On-ramps offer intensive
services, hone high-demand
technical skills, and broaden
learners’ human skills forlearners without traditional,
four-year degrees.

Kevin Cooper, Assistant Dean of Applied Technology at Indian River State College in Fort Pierce,
Florida, provides on-ramps for highly-skilled tech20

CHAPTER I

the purpose of understanding future skill demand.
Furthermore, the WEF believes that co-funding
models between government and employers could
increase access to lifelong learning programs previously unattainable to those with less formal education or technical skills. Other recommendations
from the initiative include affecting adult learners’
motivation via policy creation and increased accessibility, creating shorter modules, and promoting and maximizing on-the-job training opportunities. The initiative recommends targeting thoselearners who need it most: the ones employed insmall and medium-sized enterprises, lower-skilledworkers, and older workers. Lastly, the initiative
recognizes techniques such as gamification inlearning as well as tools such as blended online
learning for motivating adult learners and expanding access.

retain their older employees. The model identifies
four categories of competency:
1. Technical: The knowledge and skills related
directly to doing one’s job, including such domain-specific knowledge as state-of-the-art
knowledge, media skills, and process understanding.
2. Methodological: The skills and abilities related to problem solving, decision making, conflict resolving, and research and analysis; also,
efficiency oriented towards the domain-general knowledge category.
3. Social: The skills and abilities, as well as theoverall attitude, to cooperate and communicate
with others (p. 2). This includes intercultural,
language, communication, and networking
skills, as well as the ability to work in a team,transfer knowledge, and demonstrate leadership skills (p. 4).

The Fraunhofer Institute for Production Systems and Design Technology in Berlin proposesa “holistic competence model” (Hecklau et al.,2016) for sustainable workforce development for
the fourth industrial revolution. The model is basedon a close examination of the critical issues facing
today’s companies—economic, social, technical,
environmental, political, and legal. It aims to allow companies to meet the talent demand createdby the technological shift, even as they qualify and4. Personal: Hecklau et al. refer to this set ofskills as “social values, motivations, and attitudes” (p. 2). This ultimately comes down
to being “flexible” with one’s job responsibilities, which is operationalized into specific skills such as accepting change (such as
working virtually), the ability to work underpressure, having a “sustainable mindset,” and“compliance” (in response to stricter rules for
IT security, working with machines, or working hours) (p. 4).

Training is recommended basedon each learner’s particular skill
set and the needs of the specificworkplace. Co-funding models
between government andemployers increase access tolifelong learning.

Systems approaches to the fourth industrial
revolution, that aim to address sociotechnical andsocioeconomic issues in an integrative manner,are collectively referred to as Industry 4.0. Industry 4.0 is defined by five core technologies thathave evolved to define 13 enabling technologies(Habib et al., 2019) that are supporting five Sustainable Development Goals (SDG) for the year
21CHAPTER I

2030 (Schwab, 2016). The original five core technologies were developed from the integration of
traditional Operation Technologies (OT) and Information Technologies (IT). The SDG outcomesrequire that technical development of the enabling
technologies be placed in a systems context ofPeople, Peace, Planet, Prosperity and Partnership.
Implementation of such systems approaches to atechnology-enabled sustainable society requires
the valuing of all the skills of the Fraunhofer report
and the preparation of a workforce that can easily
connect domain-general skills as well as personaland social competencies to domain-specific proficiency (De Weck et al., 2011). It furthermore requires an inclusive and lifelong learning paradigm
for all participants (UNESCO, 2019).

IPPD model represents personal knowledge as athree-layer hierarchy of skills that can be dynamically organized into competencies. The three layers (from top to bottom of the hierarchy) are:•Life skills and personal fulfillment•

Domain-general skills (highly transferable
skills and abstract concepts)•

Domain-specific skills (specialized knowledge
and related task performance)

The three layers of skills are integrated. The
learner achieves competencies as well as depth
and sustainability of personal knowledge throughconcurrent growth across all layers rather than
through compartmental training in one skill, a subset of skills, or one layer of skills. In terms of the
IPPD model, competency is defined as a combination of strong skills across all three layers thatenables the learner to do a job well. Skills develop
across professional and personal experiences thatspan the process-outcome continuum. Higher-layer skills are aggregates of diverse knowledge experiences that can generalize to many lower-layer
skills; higher-layer skills inform and are informedby many lower-layer skills. In the following section, each skill layer of the IPPD model is definedand its relation to existing theories of knowledge isdiscussed. Following the definitions, recommendations are made for implementing learning strategies that can assist learners with IPPD. In Chapter
II, the authors discuss detailed recommendations
for adaptive instructional design that supports andpromotes lifelong IPPD.

1.4 Integrative Professional and Personal
Development Model
To achieve the level of sustainable workforce
participation that the new knowledge economy requires, current modes of learning and training must
be rethought. This is achievable by embracing thenotion of knowledge in action (as detailed in the
introduction of this report). This report proposesan Integrative Professional and Personal Development (IPPD) model (see Figure 1.1) that aims
to recognize and co-develop all skills and competencies encompassed within a knowledge in action
framework. This IPPD model is a combination andadaptation of the Rees and Bartlett (1999b) model
for creating learning societies, the John B. Carroll
model of three stratum theory (1993), and the Polanyi, Argyris, and Schön writings of knowledgein action (1958, 1978, 1983). The IPPD model isalso informed by the initiatives and literature discussed in previous sections of this chapter.

1.4.1 Social Learning
The global component of the IPPD modelrepresents socially constructed and contextually situated learning while acknowledging that aparadigm shift is necessary to ready all learners,

The IPPD model recognizes that knowledgein action has two highly interrelated components: personal and relational. Furthermore, the22CHAPTER I

Figure 1.1

Skills and Skill Relations in Integrative and Adaptive IPPD

Social LearningLife Skills

Domain General Skills

Domain Specific Skills

Specialized Task
Performance23

CHAPTER I

Knowledge, in this context, is not a set of rational,
discoverable facts that can be neutrally applied totest an idea, perform a task, or solve a problem.
Rather, this knowledge is indistinguishable from
how one acquires it (Polanyi, 1958) and the multiple interactions that give meaning to information.

This report proposes an
Integrative Professional andPersonal Development (IPPD)
model that incorporates
the personal and relational
components of knowledge inaction…. the model represents
personal knowledge as a threelayer hierarchy of skills: domainspecific, domain-general, andlife skills.

As mentioned in the introduction, learners accumulate knowledge across many different relational contexts (school, work, home, society) andcarry their accumulated knowledge to every learning context. Domain-general and life skills are
more abstract and can thus transfer across different
relational contexts and support integrative development across different personal and professionalsituations. It is a key reason why these skills are
gaining in importance in the 21st century economy. Leveraging domain-general and life skills canprovide inclusive and efficient entry points andpathways to the domain-specific components ofdifferent relational contexts for all learners. These
entry pathways, however, need to be adaptive.
Fixed relational contexts (i.e., standardized tests
in mathematics using symbolic methods) may notstrongly relate to the intelligences of some learners, thus portraying these learners as lacking inability. Adapting relational contexts (i.e., using
symbolic and statistical methods in teaching basic
mathematical principles) can provide connections
for differentiated learners (Costa et al., 2018; Van
Herwegen et al., 2018).

regardless of education level or age, for the 21st
century knowledge economy. This in turn depends
on strategic cross-sector partnerships that leveragea broad scope of social learning.
The IPPD social learning component takes
inspiration from Rees & Bartlett’s (1999b) social
learning model, which identifies the role of “social connectivity and the institutions of trust andcooperation in providing the economic foundation on which market-based economies can flourish and prosper” (Bartlett & Rees, 2000, p. 161).
The IPPD model expands on the social learningmodel to include theories of situated cognition(Brown, Collins, & Duguid, 1989), collective intelligence (Hutchins, 1995; Schuler, De Cindio,& De Liddo, 2015), and constructivism (Bruner,
1990; Piaget, 1963; Vygotsky, 1978) as well as
additional theories of social learning (Bandura,
1986, 1997, 2001). The IPPD model emphasizes
the importance of—and interactions between—social, technical, cultural, and economic contexts
and the history or legacies within which knowledge is situated (Coghlan & Brydon-Miller, 2014).

The relational component of
the IPPD model emphasizes
the technical, cultural, andeconomic contexts within whichknowledge is situated.

24

CHAPTER I& USU, 2019; Rhodes, 2019); productivity (Trilling & Fadel, 2009); efficiency (Hecklau et al.,2016); as well as exhibiting values and principles
that indicate a learner can coexist with others (Nagel, 1986).

1.4.2 Life Skills and Personal Fulfillment
Personal growth strategies tend to focus on developing an individual’s resilience in response tothreats to the economy. We need strategies that go
beyond this to consider an individual’s satisfaction
and fulfillment, which in turn will benefit society
as a whole (Popović, 2014). Rees and Bartlett’s(1999b) personal development model, which calls
for an increase in each individual’s “capacities toachieve self-fulfillment in other spheres of life,
not just economic activities,” inspires this layer of skills within the IPPD model (p. 21). Lifeskills span the cognitive, psychomotor, and affective domains (Anderson & Krathwohl, 2001) andthus cannot be treated only as high-level cognition(Carroll, 1993). Often tested as personality traits(National Research Council, 2013), such integrative skills are key components of complex professional competencies (NACE, 2017) as well as indicators of success in other areas of one’s life (Kelly,2016). More and more, researchers (Holmes et al.,2019) and industry representatives (NACE, 2017)
are coming to terms with the evolving needs ofthe 21st century economy, and a key part of thisis valuing each individual’s ability to exercise life
skills in multiple contexts. Life skills are critical toleverage social learning for professional and personal development and to inform the reorganization of lower-layer skills to deal with a fast-changing world. The overarching goal is for learners toacquire appropriate generalizable life skils as theyrealize their own principles and values within arich and inclusive social learning context.

Georgia Tech’s (2018b) whole-person education initiative (Initiative 1) is one example of auniversity taking action to answer employers’ calls
to develop these skills in future employees (Georgia Tech, 2018b; 2018c). Initiative 1 acknowledges the need for learners to develop not simply
discipline-specific knowledge (e.g., engineering
fields) but higher-level skills that span beyond
the cognitive domain such as the interpersonaland intrapersonal. The interpersonal skills include
communication, teamwork, and leadership. The
intrapersonal skills cover adaptability, initiative,
discipline, ethics, and persistence. These are recognized as traits that lead to long-term success(Georgia Tech, 2018c).
Higher education’s commitment to life skills
and whole person development needs to be reinforced by explicit engagement and valuing ofthese skills by industry. The Boeing Values-Based
Leadership Model establishes eight different life
skills/character traits that are explicitly connected to success and career development within andacross the domain-specific areas of the company(Boeing, 2020).

The overarching goal is forlearners to acquire generalizable
life skills that are critical toleveraging social learning for
professional and personal
development.

The most salient life skills and personal fulfillment skills are communication (Adelman et al.,2014; APLU & USU, 2019; NACE, 2017); collaboration (Rhodes, 2019; Weise et al., 2019); reflection (Schön, 1987); cultural agility (Adelman
et al., 2014; Aoun, 2017); self-direction (Aoun,2017); empathy (Aoun, 2017); creativity (APLU
25

CHAPTER I

to count that as a skill to be applied when it comestime to enter the workforce as a financial analyst(Aoun, 2017).

1.4.3 Domain-General Knowledge
This layer of skills of the IPPD model is key
for learners wanting to adopt a lifelong learning
mentality because it assists them in achieving
knowledge transfer and connecting life experiences to domain-specific skills. Domain-generalskills are also referred to as transferable skills and/or abstract concepts in the knowledge frameworks
covered in section 1.2 and section 1.3. The mostcommon general skills covered in these frameworks are logic and deduction, quantitative andcomputational thinking, analytical thinking andproblem-solving, written and oral communication,
data and information literacy, sensorimotor skills(i.e., visual perception, auditory perception), general memory, and systems thinking.

An example of domain-specific and domain-general learning from military training is
the Department of Defense Language Institute’s
use of Mordecai Meirowitz’s board game, Mastermind, to test the aptitude of potential cryptographers (J. Avery, personal communication, August2019). If a learner could demonstrate the logicalreasoning necessary to detect the encoder’s hidden pattern in the game’s colored pegs, then theexaminers viewed this as a skill transferable to thelanguage school training administered in Monterey, California. The evidence of pattern recognition skills indicated the presence of cryptographic
skills required to break encoded communications.
Additionally, a person with such transferable skills
might easily transition into the fields of machinelearning or robotic computing (Lu, Yang, & Chu,
2017).

It is important to realize that domain-general and domain-specific are areas of teaching andlearning, which are not exclusive of one another(Perkins & Salomon, 1989). Learners who havedomain-general knowledge may use techniquesthat exhibit metacognition, such as self-monitoring and self-directing their own learning throughthe use of self-questioning. Such skills need tobe taught in conjunction with those that are domain-specific (Perkins & Salomon, 1989). Development of domain-general skills in tandem withdomain-specific skills can gradually acceleratelearning of domain-specific skills through knowledge transfer. An example of this is the use of
proof in mathematics, which a student may learn
in a specific domain but, through guidance by an
instructor, see the concept’s ready application inboth philosophy and English. Once the concept islearned and carried across sectors, it can be highly
transferable to real life such as dissecting a politician’s argument or deconstructing a pundit’s editorial (Fadel et al., 2015). Another example is that ofan undergraduate student who practices analyzing
poetry in a British survey course and is then able

Greater research is needed in order to makeevidence-based recommendations on how to bestteach domain-general knowledge in tandem withdomain-specific knowledge (National ResearchCouncil, 2013). Throughout this report, we explore the role of collaborative learning as a strategy where the learners’ roles and responsibilities ina domain-general context are explicitly stated andeasily coupled with more domain-specific projects.

Domain-general skills assist
learners in achieving knowledgetransfer and connecting life
experiences to domain-specificskills.

26

CHAPTER I

Another generalizable strategy is the combinationof instruction and construction through guided experiential learning (Mooney, 2013). For example,
assigning a research paper that is conceptualized
and written over the course of a semester would allow an instructor to guide the students in deadlinesthat work backwards from the due date while scaffolding the learner with suggested benchmarks toteach them project and time management in addition to the domain of the research. Offering techniques for memory recall in tandem with content
development aids the learner in priming their own
memory or explicitly stating what should be in
their own schema before presenting content. Suchtechniques may assist with long-term memory andlogical deduction.

field is a knowledge-in-action paradigm that spans
all three layers of skills and integrates professional and personal development across the full spanof the process-to-outcome continuum (Osterberg
et al., 2016; Thornton, 2013). For this reason, the
IPPD model approaches competencies as multilayer networks of skills.
To understand the development of skill proficiency it is important to understand the differences between tasks and skills. David Autor (2013)

To reach expert status in a fieldof study, learners must be able
to integrate high proficiency inrelevant domain-specific skills
within a complex competency
envelope that spans domainspecific, domain-general, andlife skills.

1.4.4 Domain-Specific Knowledge, Task
Performance, and Competencies
Woolfolk and Margetts (2013) define domain-specific knowledge as pertaining to “a particular task or subject” (p. 251) and the LuminaFoundation in its Degree Qualifications Profilerefers to this category of knowledge as the learner’s field of study. Within the IPPD model, a domain-specific field of study is approached as a setof closely related domain-specific skills (see Appendix A). For learners to reach high proficiency
in a specific skill or task, they need only mastera specific domain or sub-domain (Hoffman et al.,2014). However, to reach expert status in a field ofstudy, they must be able to integrate high proficiency in relevant domain-specific skills within a complex competency envelope that spans domain-specific, domain-general, and life skills (Hoffman etal., 2014, p. 64). The ability of highly competent
medical doctors to relate to their patients (throughstrong personal and relational life skills) and connect that process to abstract knowledge of humanbehavior and specialized knowledge of their sub-in “The ‘Task Approach’ to Labor Markets” defines the word task as a “unit of work activity that
produces output” and defines skill as “a worker’s
stock of capabilities for performing various tasks”(p. 4). He advances this further by claiming thatskills must be applied to a task for output to occur. To move this into the realm of education, if
an instructor wants the learner to acquire a skill,
the process may begin with readings and lectures,
but practice is what ultimately moves the newly
acquired knowledge into an application. Outsideof education, the sport of baseball may serve as asimilar example of tasks providing output. A person may have great knowledge about the sport ofbaseball through knowledge of the statistics and27

CHAPTER I

rules of the game and by observing players’ performance on the field. This does not mean, however, that the individual has the skill of accurately
throwing the ball, running to the base with enoughspeed to avoid being tagged out, or judging theplayer’s pitch with enough accuracy to hit the ballinto an open area of the field.

educators to become better at assisting learners in
efficiently achieving the high proficiency of skills
necessary for masterful performance in the face ofan economy that is ever-changing and increasingly
complex. Based on their research into the possible
threat of artificial intelligence on human workers,
Dreyfus and Dreyfus (1986) developed a fivestep guide to skill acquisition. This guide explains
how someone passes through at least five levels of“qualitatively different perceptions of his task and/or mode of decision making as his skill improves”(p. 19). The five levels of proficiency are: novice,advanced beginner, mastery, proficiency, and expert. As learners advance through each of theselevels over their lifetimes, they become increasingly able to integrate domain-specific knowledge
with domain-general knowledge and life experience. This integration across skill layers increases
proficiency and facilitates speed of acquisition.

Furthermore, a task is a building block thatlinks theory to practice. Learners perform manytasks over the course of their academic careers:studying, answering questions, listening, andtaking exams. However, it does not necessarily
follow that they have developed these tasks intoa skill (Boulet, 2015). Performing tasks may be
indicative of knowledge gained from the content.
However, a skill has not been achieved until thelearner is able to provide an output (Autor, 2013)that has developed from applying classroom learning to task performance. To use the sport of baseball as an example again, someone new to intramural sports might be able to hit a baseball (task)
when receiving pitches off of their own team’s
pitcher but still not have the skill to avoid striking out when facing different pitchers due to their
misjudgment of the ball’s speed and location withrespect to the strike zone.

At the novice level of proficiency, elements
are context-free, meaning learners have no experiential-based knowledge of the skill content. All
behavior of learners at this stage is described as
rule-driven, limited, and inflexible (Benner, 2004).
Students judge their performances by how wellthey follow the rules because they “lack [a] coherent sense of the overall task” (Dreyfus & Dreyfus,
1986, p. 22). Students move to the next level, advanced-beginner, when they have gained some experience through real situations. These situations
are similar to examples that have been provided inclass or read in textbooks. An example of this level would be a driver new to using a manual fivespeed transmission. The driver no longer looks at
a range on the odometer to tell if they have shifted
into the appropriate gear, but instead relies on thesound of the engine revving to indicate the need toshift up or down (Dreyfus & Dreyfus, 1986). Bothlevels are still rule-based and objective, relying on
what was previously learned.

Following the paradigms of previous multilayered human intelligence models (Carroll 1993;
Johnson & Bouchard, 2005), the IPPD model
representation (Fig 1.1) places measurable performance of tasks under domain-specific skills.
The placement highlights that specialized tasks
cannot be performed well without proficiency inpertinent domain-specific skills. However, as tasks
get more complex, dynamic or ambiguous theyrequire the concurrent application of domain-specific and higher layer skills for masterful performance. Holmes, Bialik, and Fadel (2019) as wellas Hoffman, Ward, Feltovich, et al., (2014) advise28

CHAPTER I

the domain-specific knowledge accrued throughexplicit forms early in one’s education serves as afoundation as the learner navigates from novice toexpert in their practice. The accrued experience of
placing domain-specific knowledge into complex
life situations integrally informs all layers of skills
and the adaptation of the skills to deal with different relational contexts.

As learners advance over their
lifetimes through proficiency
levels they become increasingly
able to integrate domainspecific knowledge withdomain-general knowledge andlife experiences. This integration
increases proficiency andfacilitates speed of acquisition.

1.5 Characteristics of Integrative Development
An irregular hierarchy representation of the
IPPD (Figure 1.1 above) is chosen to highlightseveral key characteristics of the model.
1. Skill interconnectivity can be represented
as an irregular hierarchical network. The circular
nodes in the IPPD figure represent skills and thelines (edges) represent their connectivity. There
are multidirectional connections across skill layers (domain-specific sport and music practiceboth improve domain-general sensorimotor skills
and improved sensorimotor skills improve sports
and music performance) but also within layers(understanding of derivatives in calculus can besupported by practicing problem sets across physics, math, business, and design). The hierarchicalnetwork approach of the IPPD model symbolizes
the purpose of training and education, which is toincrease proficiency in domain-specific skills andincrease the learners’ ability to transfer skills andcapabilities to higher levels (Goldstein & Ford,
2002) and across domains and sectors when applying them in the workforce. The desire for moretransferable skills is based on the proposed instability of skills—a 42% predicted shift between
the years of 2018–2022 of the core skills needed
to do a job (World Economic Forum & Boston
Consulting Group, 2018). Strong and customized connectivity among the three layers of personal knowledge allows adaptability to changing
relational contexts. The IPPD approaches skills

The third level of skill acquisition is referred
to as mastery. Learners reach this level when they
exhibit hierarchical decision-making, which requires the domain-general skills of deduction anddecision making. For example, a nurse-trainee isgradually able to decide, through experience, what
is most important and which patient needs attention most urgently. The fourth level of skill acquisition, proficiency, is achieved when a learner isable to leave the rule-based supports of those earlystages. At this stage the learner realizes the mostsalient features of a situation and forces other lessrelevant features into the background (Dreyfus &Dreyfus, 1986). Moreover, the learner sees similarities with past professional and life experiences and is able to draw upon this domain-generalknowledge to inform their decision-making in a
mix that is both intuitive and analytical.
The final, fifth stage of skill acquisition, expert, describes an individual who has “an immense
library of distinguishable situations…built up on
the basis of [their] experience” (p. 32). In thinkingof these stages and the journey one takes involving
deliberate practice over years in order to reach theirgoal of achieving expertise (Ericsson et al., 1993),
29

CHAPTER I

growth as the result of complex interdependencies
between the skills of an individual and the knowledge economy institutions, and society overall.
According to Schön (1987), there is a difference
between knowing something and taking action
on that knowledge. Similarly, in the Lumina DQP(Adelman et al., 2014), learners achieve high proficiency only when they exhibit the ability to apply
knowledge in complex and changing situations. It
is not a matter of “seat time” or grades.

The purpose of training andeducation is to increase
proficiency in domain-specificskills and increase the learner’sability to transfer skills andcapabilities to higher levels andacross domains and sectors.
The learner’s ability will varyand necessitates adaptive
instructional approaches.

Within an IPPD model, the three domains ofBloom’s (1956) taxonomy (affective, psychomotor, and cognitive skills) grow in a parallel and interconnected manner. Their interconnected growth
characterizes the domain-general and domain-specific abilities of a person and supports the growthof interrelated life skills such as communication,reflection, relatedness, adaptability, creativity, andempathy. As one moves up the IPPD hierarchy,
skills become more general and more integrative.
A significant portion of domain-general and life
skills may be tacit and transferable. For example, as a waitress gains expertise in her job, she
is also building tacit abilities in everything frommulti-faceted communication and quantitative intelligence to multi-tasking and responding to unforeseen events.

(using the fingers to concurrently control multiple
piano notes), (b) general sensorimotor skills (theability to read the notes and use multisensory feedback in order to apply the prescribed pressure forthe appropriate duration given by the score), (c)specialized understanding of a musical form (e.g.,
Chopin’s Nocturne), and (d) abstract abilities tounderstand formal relations, memorize structures,and map them over time. Sensorimotor skills andformal understanding that are trained through music performance are highly transferable to mathematical, spatial, and verbal performances (Wan &Schlaug, 2010). Mathematical reasoning improvesformal understanding, which collectively improves the performance of specific musical pieces.
Sensorimotor, affective, and cognitive skills support and improve life skills such as communication, reasoning, and reflection. The sharing of amoving performance that promotes societal reflection constitutes an example of integrating personal
development into societal development (Carayannis, 2014) and denotes that the piano player has
reached the level of expert. High competency inpiano performance can therefore be seen as a network of multilayer skills spanning life and profes-

A simple example of interconnected, hierarchical skill development is that of a student evolving
into a professional pianist. Societal discourse andshared creative practice shape the student’s musical aspirations and communication needs (Dewey,1934). These aspirations advance life skills suchas understanding and directing complex feelings,
leveraging critique to drive reflection, and commitment to rigor. To achieve good piano performance technique (specialized task performance),
the student must demonstrate a combination ofskills including (a) specialized sensorimotor skills
30CHAPTER I

sional experience. When supported by relational
knowledge contexts that favor knowledge transfer,these integrated skills can inform and be informedby research and education in many fields of humanperformance (from neuroscience to social scienceto sports science).

characteristic of assessing professional development) may have a strong link to domain-specificknowledge (Carroll, 1993) but it is critically connected to many other things (Rees and Bartlett,1999b).
3. Skill development is process focused andoutcome focused. A significant amount of personal
knowledge is built through activities that focus onprocess. For example, participation in team sports
and cultural activities can help individuals develop complex networks of skills across layers while
also connecting personal and relational development (e.g., developing into a good team member across varied situations). For many learners,
these process-based activities may not produce astrong measurable outcome such as high-end performance in sports or arts. However, the abilityof these participatory processes to develop skills
across all layers of personal knowledge (including
some of the more complex abstract skills near the
top of the hierarchy such as teamwork, communication, reflection, and recovery from failure) can
help performance in other measurable outcomesthat are strongly connected to professional development.

2. Every learner’s personal knowledge is different. Individuals accumulate knowledge basedon their own mode(s) of participation, preferences, situational contexts, and goals (Anderson, Reder, & Simon, 1996; Brown, Collins, & Duguid,1989). There is evidence of this type of layeringin Michael Eraut’s (2004) research on professional
development when he claims that “there will also
be aspects of a person’s knowledge that have been
constructed through lifelong learning and havebecome unique to them, i.e., outside the circle ofshared cultural knowledge, because of the unique
set of situations in which they have participated”(p. 202). Even though people can have similar collections of skills (nodes), each person will havedifferent skill strengths (depicted by size of nodesin Figure 1.1) and will have developed these skills
through different connectivity. Domain-specificskills and training will transfer more readily forsome learners and less so for others, dependingon each learner’s general ability and strategies
as well as their “crystalized ability to transfer
the skill from past experience to similar tasks” or“fluid ability, flexible adaptation of skills to novel learning tasks” (Clark & Voogel, 1985, p. 121).
Because of this, the degree to which specific lower-level skills are connected to higher-level skills
will vary from person to person, which in turn will
necessitate adaptive instructional approaches. The
links in the network representation of personal
knowledge (Figure 1.1) have different strengths,
however, both strong and weak links need to beconsidered for professional and personal development. A performance of a specialized task (a key

For example, there is a strong correlation between women who become student athletes andtheir success in achieving leadership positions in
Fortune 500 companies (Zarya, 2017). There is

A significant amount of personal
knowledge is built throughprocess-based activities (e.g.,sports and arts) that help
professional development in atacit manner.

31

CHAPTER I

significant research and theory (Carayannis, 2014;
Dewey, 1938; Florida, 2002) indicating that societies that support participatory cultural activity builda reservoir of tacit complex knowledge amongst
their citizens, which then enables these societies tobe more resilient to change and disruptions. This
is not knowledge that is measurable at the levelof individual performance in specialized outcomesbut knowledge that is evident in the higher layersof personal knowledge and in the collective. The
irregular hierarchy representation of skills of the
IPPD model aims to highlight the complex andidiosyncratic connectivity and transferability ofknowledge across different experiences that is facilitated by aggregated development of higher layer skills. One of the working groups to follow thisreport (see Working Groups section) will explore
how an IPPD approach to knowledge can lead torevaluing of arts and humanism as mechanisms forsupporting collective experience that advances everyone’s domain-general and life skills.

in developing learners. The authors also provide
examples that demonstrate the need for institutional partnering. Creating and mapping pathways
for the skills and competencies that already exist
in the learner and those that need to be acquired
for future careers and promotions are crucial forthe learner’s success.
1.6.1 Knowledge Transfer
Developing a robust skill repertoire depends
on each learner’s ability to transfer existing andnewly developed knowledge to areas beyond thecontext in which the knowledge was developed(i.e., beyond the classroom). Enabling learners totransfer their knowledge as they apply their skills
across different contexts and in unknown settings
still to come will enhance their performance andincrease their mobility over their careers. While
such knowledge transfer is difficult to achieve(Baldwin & Ford, 1988), instructors, trainers,
learners, and employers all must share in the responsibility for success. When instructors are able
to take specific concepts, constructs, and tools of
one domain and explicitly connect them to otherdomains and/or applications, they help to makethe content more meaningful to the learner andenable knowledge transfer via practice and acrossdifferent contexts (Fadel et al., 2015).

A society that defines knowledge inclusively(across the full spectrum of the four dimensions
outlined in our introduction) is better able to recognize and benefit from the full diversity of personal knowledge of its members as well as the fullrange of skills of each person in their many different manifestations and combinations. Adaptive
learning is critical to identifying and advancing
different types of personal knowledge. Valuing ofdiverse knowledge within society encourages eachindividual to embody and relate to difference. It
also generates complex pluralistic discourse
among individuals. Such discourse can provide
sustainable solutions to complex problems.

It is well known that learners often naturally acquire domain-specific and domain-generalknowledge in tandem (Perkins & Salomon, 1989).
When designing for instruction it is important toask, “What concepts will remain in the learner after they graduate?” (Fadel et al., 2015). In otherwords, “How can this content be taught in a waythat enables the learners to transfer it to other domains and possibly real-world applications while
also providing them with the essentials to the discipline?” (Fadel et al., 2015). Instructors wanting
to operationalize integrated domain-specific and1.6 Collective Responsibility for Integrative
Professional and Personal Development
A number of times in this report, the authors
note that institutions of trust play an important role32

CHAPTER I

domain-general acquisition of skills may find it
useful to set up a matrix as described by (Fadel etal., 2015). If doing so, instructors need to realizethat it is not unusual for the matrix to be unevenly or incompletely populated across the layers of
the IPPD model. The idea of mapping connections
between the domain-specific and the domain-general works well with what Fadel, Bialik, and Trilling (2015) refer to as concepts and metaconcepts.
Take, for example, the idea of rate of change,
which students frequently learn in mathematics
classes by memorizing “rise over run” when determining the facts about a line (Fadel et al., 2015,
p. 77). In physics, the concept is used to figure
relationships between velocity, position, and ac-

rivative will reveal a higher-level rate of change ora maximum or minimum value. Unless you are amathematician, the real knowledge for a discipline
is understanding the purpose of each derivativeand how to use it, not the process by which it isobtained. The Wikipedia article on time derivatives (“Time Derivative,” n.d.) gives the following
examples from physics: (1) force is time derivative of momentum, (2) current is time derivative of
charge, and (3) power is time derivative of energy.
It also discusses the following examples from economics: (1) the flow of net fixed investment is thetime derivative of the capital stock, (2) the flowof inventory investment is the time derivative of
the stock of inventories, (3) the growth rate of themoney supply is the time derivative of the money
supply divided by the money supply itself, and (4)the growth rate of the labor force is the time derivative of the labor force divided by the labor force
itself.

Knowledge transfer is difficult
to achieve. Instructors, trainers,
learners, and employers all must
share in the responsibility for its
realization.

All of these examples use the same fundamental processes that can be laborious and confusing
to develop from first mathematical principles.
However, effective integrative thinkers will beable to grasp the relationships being expressed by
the examples, even when they are not part of theircore discipline training, because the relationships
are contextually understandable. They can calculate an outcome through the understanding of thecontextual relation and the use of computational
tools that do not require deep first principle mathematics understanding. Teaching computational
tools and how to use the results in context would
provide the real knowledge to integrative thinkers. Adaptively, students could dive deeper into
the results in different domains or into the fundamentals of mathematics if so desired. The entry
point to understanding and using derivatives caneven be experiential. For example, a pianist hastacit knowledge of velocity being a derivative ofceleration. While learned in a specific domain, theabstract of it helps with understanding change in
one’s everyday life. A general member of the public may use it to understand how pandemics spread(Fadel et al., 2015).
This approach of teaching math inside and outside the first principles method can apply to theoverall teaching of derivatives. Many disciplines
have calculus as an element and many of thosedisciplines teach the fundamentals of calculus asbuilding blocks to the final outcomes. A derivative
represents a change over time of some fixed parameter that has an implied direction of movement
represented by a function or vector. A second de33

CHAPTER I

rate of displacement of a piano key from rest position to the hammer hitting the string; the fasterthat displacement the louder the note. The pianist
uses this tacit knowledge expertly to control dynamics and with the appropriate instructional support could translate that knowledge into other domains that use derivatives. Earlier in this section
we discussed the relevant real-life example of the
Indian River State College in Fort Pierce, Floridathat removed college algebra barriers by creating
courses for students to learn only the precise algebra, trigonometry, and statistics skills necessary to
work within the field of nuclear energy (National
Science Board, 2019).

In a similar way, simultaneously acting as a
guide on the side, an instructor or a mentor may
empower the learner to develop and implement
their own metacognitive strategies and self-regulation (Ford et al., 1998); practices that will remain with the learners and assist their professional
and personal development throughout their lifetimes. Doing so aids learners in realizing how theirown inventory of knowledge and skills connects
to possible goals within the range of their zones ofproximal development (Vygotsky, 1978). It mightalso help them gain the self-efficacy and wherewithal to pursue and develop whatever skills theymight need to fill the gap between their current
professional states and their goal states. Resources provided by institutions of trust can assist themthroughout this co-creation.

This section focused on knowledge transfer processes between domain-specific and domain-general skills in order to highlight that theseskills can develop in tandem and that they aresynergistic. The authors discuss in more detail in
Chapter II, how connections between domain-general skills and life skills may be achieved throughinformal approaches such as mentoring, advising,solving research problems, or participating in collaborative problem-solving projects.

A well-structured co-creation paradigm canempower the learner without losing quality or rigor. For example, the highly ranked Computer Science (CS) program at Carnegie Mellon University
identifies only eight computer science courses andfour mathematics courses as fixed requirements of
the BS degree. Proficiency in other areas of the degree is achieved by the student choosing from a listof electives per area. Many of the electives bridge
CS with another field of knowledge. Students arealso required to complete a minor outside of CS.
Finally, students can receive significant hours ofcredit for research and work with industry (i.e., internships) (Carnegie Mellon University, n.d. -b).

1.6.2 Learner Autonomy
While the beginning awareness of transfer
may originate with an instructor, trainer, or peer
in a learner’s educational institution or place of
employment, the ability to continue moving andenhancing a skill set belongs to and resides withineach learner. As such, instructors, mentors, managers, counselors, and advisors can assist learners in realizing their prior knowledge and skills
through a learners analysis, which can be viewed
as an inventory for the purpose of connecting thatknowledge to new concepts and realizing its relevance through application outside of the originalacquisition context (Anderson, Reder, & Simon,
1996).

Beyond the classroom or training context,
higher education bears the responsibility to assist
learners as they discover and align their careergoals via pathways. Part of this responsibility canbe achieved by fostering learners’ relationships
with representatives from industry for the purposeof later exploring opportunities through internships or cooperatives (Coffield, 1999; Matusovich
34

CHAPTER I

et al., 2016) that serve the dual purpose of (a) “trying on” various job roles prior to committing to a
specific career, and (b) aiding learners in moving
or generalizing their knowledge from the classroom to the job and vice versa as they see the skills
being applied in the workplace. Once learners decide on a career goal, they need the flexibility tocustomize their personal curricula to match thatgoal (Georgia Tech, 2018a). This may be achieved
through the traditional format of coursework,through experiential learning opportunities withindustry, or via shorter, just-in-time mediums offered via services like Coursera, LinkedIn Learning, or boot-camps.

encouraged to grow their capabilities—including
but not limited to specific job task knowledge—insuch a way that they are building a foundation formobility within the organization and/or the economy more broadly.
Evidence of this thinking is being put into action by companies such as Amazon, AT&T, andGeneral Electric (GE), all of whom explicitly map
pathways that enable their employees to clearly see routes to advancement or career changes.
Chapter III of the report includes a summary of
the adaptive lifelong learning programs instituted
by GE Appliances for facilitating worker mobility
and advancement. Details on these programs andtheir outcomes are provided In the Resources section.

Lifelong adaptive and integrative professional
and personal development also requires a co-creation paradigm that engages both the employer
and employee. At a time when automation andsocioeconomic innovations make job tasks fleeting (Manyika et al., 2017), learners can perform
certain tasks within the context of their jobs while
simultaneously developing more inherent capabilities that, with the right support structures, canbe portable (Muro et al., 2019). Because individuals add value to their place of employment (andthe economy more broadly), the workplace system must also give value to the individual in theform of remuneration, as well as opportunities for
personal and professional development (Wolff &Resnick, 2012). In return, employees should be

It is important to note in closing that integrative development of skills allows all learners toconnect their diverse life experiences to multiple
professional pathways. It also makes each learner’s complex stock of skills highly adjustable tochanging workforce needs and provides employers with a large diversity of intelligences for dealing with 21st century complexity. In the remaining
chapters, the authors discuss how developing sucha non-linear model can only happen through ongoing trial, innovation, and collaboration between
and among different sectors.

35

Chapter II:
Adaptive Approaches to Integrative
Professional and Personal Development

CHAPTER II

CHAPTER II

Adaptive Approaches to Integrative Professional andPersonal Development
Authors: Thanassis Rikakis, Kim Carlson, Jared Keyel, Owen Cardwell
Co-authors: David Tegarden, Randy Swearer, Barbara Lockee, Feng Hou, Glen Holmes,
Syvlester Johnson
Contributors: Taryn Cardone, Mark Kamlet, Dale Whittaker, Colin Potts, Amy Arnold, John
Boyer, Tazio Grivetti, Chip Blankenship, Michael RicheyIn this chapter, we explore adaptive learning
methods designed to achieve integrative
professional and personal development.
We argue that the mapping of personal experienceand aspirations to adaptive career paths requires us
to rethink the notion of curriculum. The primary
focus must be on the skills and competencies that
individual learners accumulate rather than on thecourses they take. We then propose an approach tolearning in which the curriculum is conceived asa network of modular learning experiences connected through multiple pathways that allow individual learners to develop skill proficiency andconnectivity in their own unique ways. Finally, we
discuss a number of existing technological tools
and technology-assisted processes that facilitate
adaptation in the learning experience.

Integrative Professional andPersonal Development is“lifelong,” “life-wide,” and “lifedeep.” This notion of learning isvaried and requires a high levelof adaptation.
al., 2007). Such learning takes place in everyday
settings and family activities; the workplace andprofessional settings; designed spaces (such as
studios, classrooms, museums, and libraries) andprograms; and increasingly, online and via mobile technology. Within this context, the notion of“learning” is varied and therefore requires a highlevel of adaptation.

2.1 Adaptation and Integrative Development
Integrative Professional and Personal Development (IPPD) is “lifelong,” occurring throughout
the stages of one’s life; “life-wide,” taking placeacross a range of activities and social settings;
and “life-deep,” referring both to the multilayercomplexities of 21st century competencies (as outlined in the previous chapter) and to the culturaland social values that influence learning (Banks et

What this adaptation looks like is determinedby asking the following questions:•37

Who is the learner? How do we facilitate
the emergence of each person’s knowledge,
strengths, and aspirations so that we can customize learning to these strengths and aspirations? How do we integrate continuous andCHAPTER II

active learner participation into an individualized program of professional and personal
development?
•

What is the learner’s need(s)? Needs can range
from a minor upgrading of skills to reshapingof an entire career.

•When, where, and how can the most effective
learning take place? In answering these questions, it is important to anticipate that timing,delivery mode, and place of learning might
have to change along the way.

•

How do we track, record, and reward lifelong,
life-wide, and life-deep learning? How do we
make pathways flexible so as to respond tolearner development and discovery and to thechanging needs of the world?

•

How do we facilitate the merging of humanexpertise with technological tools and thecontinuous development of cyber-human intelligence to help address the complexity anddynamicity of high-dimensional adaptive andintegrative learning?

Dabars, 2020). The need for more inclusive approaches to learning that also address rising costs
and restrictive access to educational programs isdriving higher education institutions to rapidly
consider alternative approaches to curriculum development and course delivery (e.g., EdX, Coursera, Edplus).
While these programs are invaluable, it might
help us to also look outside of higher education
to identify emerging trends in learning and development organizations, especially within industry where flexible and customizable learning
approaches are being implemented. Looking for
emerging solutions to adaptive learning acrosssectors is also consistent with the spirit of integrative personal and professional development.
After all, school typically occupies only 18.5% ofa person’s lifetime waking hours (Stevens, 2005),
which means that most people attain the majorityof their knowledge through adaptive “free-choice”
learning outside of the classroom setting. Thiskind of learning can be characterized as “learner-motivated, guided by learner interests, voluntary, personal, ongoing, contextually relevant, collaborative, nonlinear, and open ended” (National
Research Council, 2009, p. 11). The current time
window is opportune for cross-sector sharing ofpractices for scaling of adaptive learning acrosshigher education and professional training.

Prior to the emergence of the current knowledge economy, opportunities for adaptive lifelong
learning tended to focus on the needs of non-traditional learners, especially working professionals
with a need for enhanced on-the-job knowledge ora desire for career mobility through the attainmentof a certificate or an advanced degree. For the mostpart, the programs (or products) created to addressthese needs have usually been delivered throughcorrespondence courses, video programs, andmore recently, asynchronous online instruction—
modes that allow for flexible access and self-paced
engagement. Higher education institutions haverecognized the need for adaptive learning at least
since the emergence of the new economy, but formal implementation has been sporadic (Crow &2.2 Co-Creation Approaches to Learning
A growing number of studies are discoveringboth social and economic reasons for rethinking
traditional approaches to curriculum development. For instance, Robert J. Sternberg (2006) has
found that students perform significantly better
when teachers forgo a textbook-based curriculumin favor of a curriculum constructed around students’ everyday cultural experiences or adaptive
skills they learned outside of the classroom. This38

CHAPTER II

is experiential learning at its best. In another study,
Sternberg and colleagues (2006) found that “whenwe teach students in a way that fits how they think,they do better in school” (p. 33).

size a student’s strengths. This produces neurological stimulation that, in turn, builds more
confidence (Jensen, 1998).

In their book Unlocking Student Potential:
How Do I Identify and Activate Student Strengths,
Yvette Jackson and Veronica McDermott (2015)
argue that learners demonstrate in everyday,
non-academic settings many of the skills that educators think students need to be college ready.
These skills include exercising independence, responding to the demands of a situation, comprehending and critiquing, and using technology anddigital media (p. 6). The key, they maintain, is totap into these skills, make learners aware of them,and help learners to employ them in other settings.
When this happens, learners are (a) better prepared to learn and (b) more likely to view themselves as capable, valued, and respected. This, inturn, promotes greater engagement, performance,and enjoyment in learning in an academic setting(Jackson & McDermott, 2015, p. 8).

When students reveal their interests, and when
they are allowed to practice skills based on
those interests, they exercise personal strengths
more frequently, which causes the brain to create more neurons, thereby helping them to be
more efficient and perform better (Anderson,2005).

•

Focusing on students’ positive talents improves
their emotional health, which is directly tied
to better learning and performance (Costa &Kallick, 2014).

•

When teachers intentionally bridge learningwith students’ cultural backgrounds and interests, students are better able to tap into innate
strengths, which enables them to learn better(Duncan-Andrade & Morrell, 2008; Mahiri,1998).

2.2.1 Redefining Strength

The challenge, unfortunately, is that social
norms tend to push learners to focus on theirdeficits rather than their achievements. Most of
the time, these deficits are defined by standards
and models that originated during the second industrial revolution—standardized testing of domain-specific skills and task performance (i.e.,
grades in standardized tests). Not surprisingly, students judge themselves based on these standards
and models, even though in some cases they may
be outmoded. It is essential, therefore, to counter this tendency by empowering students to recognize their strengths and then build upon them.
Jackson and McDermott (2015) cite numerous
studies showing the benefits of this positive reinforcement. For instance:••

When many of us hear the word “strength” ina professional or educational context we think of
the Clifton StrengthsFinder (Clifton, Anderson,& Schreiner, 2002), which identifies a strength asa natural talent embedded in a person’s identity.
If cultivated over time, this talent can become astrength and, for the most part, it remains relatively stable across situations and experiences. This
notion has been enormously influential in the business world. The Gallup Clifton StrengthsFinderassessment is used by 90% of Fortune 500 companies in their organizations (Clifton StrengthsFinder, 2019). And yet, there is a danger in viewing aperson’s dynamic skill set through such a restrictive lens: We risk identifying a person’s strength
tags prematurely and then locking them into an unnecessarily circumscribed learning path. Once thisConfidence increases when teachers empha39

CHAPTER II

happens, strength tags have a tendency to become
fixed, which can then limit adaptive development.

texts and evolving learner needs and aspirations.
Continuous personal discovery is most likely tohappen when learners are active participants indynamic learning processes. There is significant
research showing that learning is most effective
when it combines (a) instruction with construction and (b) knowledge assimilation with knowledge accommodation (Mooney, 2013; Niemiec &Ryan, 2009). An integrative co-creation approachto learning brings together instances across the full
spectrum of the four-dimensional inclusive knowledge representation discussed in the Introductionof this report. For example, participatory design
exercises tend to be more successful when theyencourage self-authorship and team formation;
this is more likely to happen when the exercises
move constantly between process-focused andoutcome-focused instances and between segregated and integrative work (Senge et al., 2012). Whenthe learner explores different pathways, they find
new strengths and discover new interests. This
opens new opportunities for professional careersand personal development. Institutions must, inturn, adapt their learning and career pathways toaccommodate the learners. In other words, learning is most successful when it happens via continuous co-creation.

For this reason, our IPPD model approaches
strengths as a dynamic amalgam of tacit, implicit,
and explicit skills. By empowering social learning
across different contexts, this amalgam of skills
acts as an anchor for varied personal and professional development pathways—i.e., for forming
many different types of explicit competencies.
Changes in relational context and personal development will enable a person’s unique array ofskills to emerge, develop, and evolve, which mightin turn force us to rethink that person’s perceived
strengths. For example, strong hand-eye coordination may manifest in sports or crafts. Within
an inclusive and adaptive learning context, thisability can become a strength that contributes agreat deal to a career as a neurosurgeon, architect, sports coach, or airplane pilot. A learner may
have strengths that are not emerging because of
the teaching methodology. Research at Kingston
University London has shown that learners who
may struggle with symbolic methods of teachingfundamental math skills can achieve high levels ofmastery of these skills through statistical methodsof teaching (Costa et al., 2018; Van Herwegen etal., 2018). Even a simple change to testing methodologies can result in a different ranking of a person’s skills because that person’s tacit and personal
skills may not be captured by institutionalized andstandardized testing (Bhattacharyya et al., 2013).

One example of an integrative co-creation approach to learning is Maria Montessori’s well-es-

Active participation in dynamic
learning processes creates
continuous professional andpersonal development. Skills arereorganized and expanded in
response to different contexts.

2.2.2 Integrative Lifelong Development throughCollective Co-Creation
The IPPD model links integrative development to adaptive learning by emphasizing that aperson’s accumulated life, domain-general, anddomain-specific skills do not have to be narrow,
fixed, or immovable. They can be reorganized, expanded, and remixed in response to different con40

CHAPTER II

tablished method for early childhood education(Mooney, 2013). The Montessori method values
self-directed, hands-on learning, with the goal
being for children to become self-motivated in
all areas of their development: cognitive, emotional, social, and physical (American Montessori
Society, 2020). Recent research shows that children who attend such preschools perform betterin academics and social cognition, are more mastery-oriented, and tend to enjoy academic tasks
over recreational ones (Lillard, et al., 2017). Thereis, however, some debate over the effectiveness of
the Montessori method. Advocates believe it prepares students for success as they age, but somestudies have found no difference in Montessori
versus traditional education for middle and highschoolers (Lopata, Wallace, & Finn, 2005; Ruijs, 2017). Some speculate that teachers in thesehigher grades have not been adequately trained todeliver a continuation of Montessori curriculum,that there are more options available for other specializations in high school, or that this curricular
framework which was developed based on early childhood development works well for young
children but that students in traditional schools
eventually catch up. Another possible explanationis that the focus on standardized, domain-specific outcomes in traditional middle and high school
education disincentivizes the continuous growthof domain-general and life skills a child begins tobuild in early Montessori education. Nevertheless,the Montessori method is a helpful example ofthe types of co-creation in learning for which the
IPPD strives.

cific knowledge before they have had a chance toreflect and develop as individuals. For instance,
Taran Cardone (2018) describes how we might use
design thinking to customize learning through amodel called personal learning design. Educators
can engage students in personal learning design byasking them to “map out experiences as big as theiroverall college journey and as small as specific experiences along that path” (p. 15). For their part,students are encouraged to ask themselves, “Whatunique combination of involvement, coursework,and everyday interactions would amount to ajourney that mattered?” (p. 11). In a similar vein,
Journeysmap.com is an online tool that enables individuals to chart their life journey from pre-kindergarten through secondary and college education, to their career, and beyond. If a learner has a
dream career, they can search through the databaseand discover multiple paths to achieve that dream.
Self-discovery exercises like journey mapping canbe effective because they exploit the strong relationship between personal and relational knowledge, enabling people not only to discover theirabilities and interests but to also gain confidence
by seeing how different abilities can be combined
to solve complex problems.
Co-creation approaches to learning can leverage inclusive relational contexts to promote
self-discovery for all kinds of learners while diversifying their interpersonal relations and consequently expanding their aspirations. This contributes to the development of much-needed social
capital, which Avis (2002) and Szreter (1998) argue is crucial to boosting the economy while also
increasing social inclusion and cohesion. Collective intelligence scholars propose defining Collective Intelligence for the Common Good as a method for harnessing the power of a diverse group topromote societal good, improve civic engagement,
and produce transformative solutions to complex

In the realm of higher education, co-creation
approaches to learning are opening new opportunities for college students to customize their learning experiences—or “journeys”—in ways thatgo against the traditional educational paradigm,
which expects students to excel in tasks and spe41

CHAPTER II

problems through democratic decision making(Schuler, De Cindio, & De Liddo, 2015). In otherwords, bring people with a variety of skills together
to leverage those skills for the broader social good.
In turn, those same people discover and gain confidence in their abilities, grow and develop personally, and create wide societal aspirations. Appreciative inquiry may be one method of promoting
self-discovery and collective intelligence. Appreciative inquiry is a process that “encourages organizations to identify strengths and imagine possibilities to outgrow problems and realize visions”(Tschannen-Moran & Tschannen-Moran, 2011, p.
422). Instead of focusing on problems that can spiral down to a blame game, appreciative inquiry,
which is founded on positive psychology, focuseson identifying positive aspects of people and thesituation and therefore shifts the team’s mindset
in new, positive directions (Tschannen-Moran &Tschannen-Moran, 2011). From there, the teamcan explore tasks to solve complex problems, ormay begin to understand how their own skills canbe used in other areas of their lives (personal development). We discuss in more detail the issue ofparticipation as knowledge creation in Chapter IV.

multi-layered skills, this qualitative framework
can inform the comprehensive implementation of
lifelong adaptive and integrative learning.
One possible starting point for developing aqualitative framework is Ken Wilber’s model for
integral theory, commonly referred to as AQAL,
which is shorthand for “all quadrants, all levels,
all lines, all states, all types.” Wilber et al. (2012)
contend that “this is the simplest set of distinctions
that account for the complexity of our evolving
world and the depth and breadth of consciousness
for which authentic practice strives” (p. 1628).
While it is often said that AQAL “makes sense of
everything,” the framework is not totalizing. In
fact, Wilber (2012) would argue that it leaves out
most of the details, to be filled in by new discoveries and individual experiences. We provide here abrief overview of the AQAL elements, and Owen
Cardwell explores the AQAL model in more detailin the Resources section.
•

2.3 Understanding Learners’ Personal and
Relational Knowledge
Our current learning institutions and systems
are very good at measuring domain-specific skills
through standardized approaches. But this only
takes us so far. IPPD-based learning strategies
supported by relevant high-dimensional analytics(see section 2.5) can help us understand and possibly begin to quantify integrative development
across domain-specific, domain-general, and life
skills. However, in order to track and understandthe totality of a learner’s personal knowledge,
we also need a qualitative framework, one that
focuses on the experience of personal development. Combined with quantitative approaches to
42

Quadrants refer to the four dimensions of being-in-the-world: interior/exterior and individual/collective, which translate into thinking (I), behavior (It), culture (We), and social
systems (Its). The first two quadrants—I and
It—focus on individuals and their strengths,
abilities, frame of mind, and how they relate
to the physical environment. The We and Its
quadrants help the individual see how they fit
within the broader social world. Using Wilber’s AQAL model, an integrally developed
person is one who can draw upon all four
quadrants. According to Wilber et al. (2011),“phenomena arise in all four dimensions simultaneously. The four quadrants co-arise (or,more precisely, ‘tetra-arise’) in the experienceof every now” (loc. 1704). In order to be bothaware of the narrative being performed andable to reframe that narrative, it is important toCHAPTER II

recognize all four dimensions in any situation.
••

Levels of Consciousness are higher-order structures that emerge as evolution breaks into new
territory. These structures reflect attitudes ofconsciousness (such as egocentric, ethnocentric, world-centric). According to Wilber et al.
(2011), there are higher and lower structuresof consciousness, and it is possible to grow tohigher levels in progressive stages or waves ofdevelopment. For example, as human beings
we move from childhood to adolescence toadulthood; as a society America moved fromslavery to segregation to civil rights. Our levelof consciousness defines our worldview.

•

Interpersonal: Who are the people with whom
I coexist?

•

Values: What is important to me and what is
important to others?

•

Emotional: How do I feel?

•Empathy: How do others feel?

If a traditional learning model focuses on thecourses someone took, a learning model focusedon IPPD shifts the focus to the skills that accumulate in the learner and on how these skills canquickly transform to meet fast-changing workforce needs. Lifelong application of an IPPD model requires highly adaptive learning platforms that(a) can recognize the full stock of the learner’s existing skills across the IPPD layers, and (b) allow
learners to pick up skills in many different ways
and environments (ranging from practical experience in the job to a formal course) and to compile
skills into competencies through customized pathways.

According to the AQAL model, consciousness
does not develop monolithically in all areas at thesame time. The pace of growth may differ in different
areas, and growth in some areas may be necessary for
growth in others, yet multiple developmental lines
can be distinguished through which growth occurs ina relatively independent fashion (Wilber et al., 2011).
Psychologists have identified multiple dimensions ofdevelopment (Abes, Jones, & McEwen, 2007; Kohlberg, 1971; 1981). In this report, our focus is on linesof development that address existential questions
and have potential connections to the IPPD life skills
such as reflection, self-discovery, values, and principles. The idea behind these self-evaluative questions
is to bring forward a person’s tacit life skills that canfacilitate adaptive and lifelong learning.
Self: Who am I?

Cognitive: What am I aware of internally andexternally?

2.4 Moving From Fixed Courses and Curricula
to IPPD-based Adaptive Learning Platforms

Lines of Development are specific areas inwhich growth and development occur (e.g., interpersonal, moral, musical, needs, cognitive).
They are also sometimes called “multiple intelligences” or “streams” of development.

••

An adaptive learning platform that supports
IPPD requires full flexibility of timing and content. A learner can access and exit structured learning fitted to their needs at any time. The learning
experience can range from a short module focusedon a single skill to a long pathway that produces
multiple competencies. Learners can, and should,
engage in these experiences throughout theirlives and realize adaptive pathways on their own
schedule. IPPD-based learning platforms recognize all types of knowledge (tacit, implicit, andexplicit) and all layers of skills (domain-specific,
domain-general, and life) thus allowing all typesof experiences to contribute to learning. For instance, upskilling for an employee can include
43

CHAPTER II

represent modules while links represent pathways
between modules (or flexible prerequisites). Proficiency in the targeted skill progresses through thenovice, capable, and skilled levels (see ChapterI). Each proficiency level has multiple modules
available that are interconnected by multiple pathways. To further advance a co-creation paradigm,
entry-level modules are short and focused on
helping learners discover their preferences before
committing to a longer pathway. In the Resources section, we discuss a current pilot program at
Virginia Tech in geography where entry to more
specialized geography courses is facilitated byshort, asynchronous entry-level modules open to
all university students.

Lifelong application of an IPPD
model requires highly adaptive
learning platforms that recognize
all of learners’ existing skills andallow learners to pick up skills inmany different ways.
everything from apprenticeships and mentoring
to online content and flipped classrooms (Lohr,2020). The timing flexibility of an IPPD-based
platform refers to when a person chooses to engage an experience but also how long they will
spend on that experience. Organizing content insmaller units (modules) and allowing each person
to take different amounts of time to complete each
unit can contribute to completion and retention
rates (University of Detroit Mercy, n.d.). Modular
content also allows testing for different orderingof concepts which helps with adaptation to learner needs and with the creation of overall analytics
to inform ordering recommendations (Koedinger,
McLaughlin, & Stamper 2014). Modular content
also contributes to just-in-time advising as learner
analytics emerging from small learning units canbe used to frequently update the learner pathways.

Instructors developing content for an IPPD-based platform should aim to connect domain-specific and domain-general knowledge
in the learning experiences wherever possible.
This may enable a learner to more easily transfer
knowledge between domain-specific areas, scaffold faster across levels of proficiency, and begin
to embody an integrative understanding of the relation of domain-specific skills to domain-generalskills. For example, domain-general knowledgeof the concept of derivatives can be mapped byinstructors across domain-specific modules inengineering, business, and physics (see Chapter
I). This would allow learners with experience innovice- and capable-level engineering modules toskip some novice-level modules when acquiring
related business information technology skills.

An IPPD-based adaptive learning platform caneffectively be structured as a dynamic collectionof networks of modules that connect through multiple pathways to allow learners to develop skill
proficiencies in a customized manner. Different
modules can approach the building of skill proficiency through different formats (experiential, theoretical, in-person, asynchronous, blended, etc.) so
as to accommodate different ways of learning anddifferent learners. We represent modular buildingof skill proficiency in Figure 2.1a: square nodes

An IPPD-based adaptive learning
platform can be structured
as dynamic, multi-pathway
networks of diverse modules.

44

CHAPTER II

Approaching complex concepts, such as derivatives, through different domain-specific lenses (i.e., engineering and business) also enhances
the student’s ability to connect seemingly disparate skill sets and builds the life skill of creativity(Page, 2008). Figure 2.1b illustrates this idea andhighlights that tracking the accumulation of multilayered skill development in the learner, rather
than progress through a fixed sequence of courses,
can significantly shorten learning paths and reduceburden on the learner. In Figure 2.1b skills are represented as oval nodes.

An IPPD-based platform places
modular learning experiences
between domain-specific anddomain-general skills andbetween domain-general and life
skills.
the need for any one learning experience to map
to all three layers while shortening learning paths
and still achieving an integrated development ofskills across the three layers.

An IPPD-based platform places structured
learning experiences between domain-specific anddomain-general skills and between domain-general and life skills. Learning experiences that focus
on connecting life skills with domain-general skills
can also be modular and may include self-discovery
design exercises, collaborative problem-solving,
and various forms of experiential learning that engage complex and inclusive “real world” contexts.
The gradual integration of skill layers achieved
through IPPD-based adaptive learning can facilitate collaborative engagement of real-world challenges and the emergence of diverse collective intelligence. For example, domain-specific skills inphilosophy, design, social science, and computing
can be mapped, through appropriately structured
modules, to the domain-general concepts of logical deduction and derivation. The common spaceof the domain-general concepts can in turn facilitate a collaborative learning experience between
these diverse disciplines on integrated security.
This collaborative experience would build life
skills and address societal purpose. It would promote multi-perspective discourse and reflectionthat can address the high dimensional complexityof safety and security in the 21st century while also
being fulfilling for all participants. The coordination of learning experiences across layers reduces

Figure 2.1a

Adaptive Pathways Between Modules at
Different Levels of Proficiency

45

CHAPTER II

Figure 2.1b

Shortening Domain-Specific Pathways Through Domain-General Skill

In Figure 2.2, we illustrate the layered natureof learning experiences recognized and facilitatedby an IPPD-based platform. The size of the oval
nodes denotes the strength of skills achieved by
the learner while the proximity of nodes shows
similarity of skills. The size of the links that connect skills shows the connectivity strength of skills
embodied by an individual learner. Developmentof integrative knowledge is based partly on structured learning modules and partly on the learner’s
tacit knowledge from various life experiences.

Competencies within an IPPDbased platform can be seen as
customized networks involving
skills across the three layers thatallow strong job performance.
specific modules (as well as following different
paths between modules) and by connecting thedomain-specific skills arising from these modules
to different combinations of domain-specific, domain-general, and life skills. Furthermore, personal competencies (i.e., being a good partner)
are related to professional competencies (i.e.,being a good engineer)—they both rely on anddevelop the life skills of collaboration, communication, and agility. We highlight these potential
connections to emphasize the importance of integrated personal and professional development.

Competencies within the IPPD-based platform can thus be seen as customized networks
involving strong skills across the three layers thatallow someone to perform a job well. Competencies are partly standardized and institutional(due to structured learning provided by various
mediums) and partly personal and adaptive. For
example, two people can become competent engineers by taking different sets of engineering46

CHAPTER II

Figure 2.2

Multilayer Skill Development Supported by Multilayer Modular LearningLife Skills

Domain General Skills

Domain Specific Skills

Mobility of the learner across learning experiences on the vertical (layer of skills) and horizontal(type of skills) facilitates integrative learning andpromotes complex thinking and dynamic lifelong
learning.

are fixed, this is merely a limitation of the dia-

It is also worth noting that while the size andcombinations of nodes and edges in Figure 2.2

a combination of institutional knowledge, learn-gram. Indeed, we believe that adaptive lifelong
learning is and should be flexible with respect tothe formation of competencies. Network shaping
is informed and continuously updated based on
er analytics, and workforce data. Our modular
47

CHAPTER II

ing together. For example, collecting large amountsof learner data across sectors could allow previous
experiences of a learner as a waitress, trucker, or
mechanic to be modeled as probabilities of existingskills across the three IPPD layers. This modeling
could inform the recommendation of pathways foreach of these learners to reskill for software engineering employment (Lohr, 2020) while allowing for the recommendations to be updated continuously as the different learners begin to tackle
their learning pathways. An HBM approach also
accommodates the combined modeling of thelearning environment and the individual learner,
which can significantly increase the efficacy andefficiency of learning (Koedinger et al., 2013). For
example, the probability of the number and typeof repetitions of a particular exercise necessary fora learner to grasp a concept can be modelled intandem with a particular learner’s prior skill stockand emerging learning preferences.

Rather than traditional
admissions, learners enter
IPPD-based platforms throughjust-in-time identification oftacit, implicit, and explicit skills.
Advising becomes individualized
pathway recommendations fordeveloping existing skills into
IPPD-based competencies.
approach to implementing adaptive learning for
IPPD makes it easy to add or subtract modules
and improve mappings of modules to skills andskills to competencies as societal knowledge
evolves.
The notion of admissions to an IPPD-based
adaptive learning platform becomes the just-intime quantitative and qualitative identification ofa learner’s tacit strengths and aspirations, explicit
and implicit skills, and related zones of proximal
development. The notion of advising becomes aset of individualized recommendations of pathways for developing existing skills into explicit
competencies and for overall professional andpersonal development.

An HBM approach to adaptation is also compatible with both human and computational modelsof learning and can thus facilitate the developmentof cyber-human systems that support IPPD-based
platforms (Rikakis et al., 2018). In section 2.5,
we discuss a number of technological advances(i.e., the Internet of Things) that can be combinedwith human expertise to instrument a wide rangeof learner-observed characteristics across multiple learning contexts (i.e., performing specialized
tasks at work and studying related skills throughonline learning). Considering the resulting data
as a single unified ecosystem could eventually
uncover the distributed nature of human learningthat is embedded in a thick network of human behaviors. The ability to shed light onto the so-called“ghost in the machine” (Koestler, 1967), whereknowledge making is embodied across a variety oflearner actions, has a powerful appeal (Madhavan& Richey, 2016). A holistic cyber-human under-

Of course, when advising learners on pathways
it is easier to recommend immediate steps than it isfaraway steps (Vygotsky, 1978). In this respect, a
Hierarchical Bayesian Modeling (HBM) approachto learning in complexity (Tenenbaum et al., 2011)
might be helpful to those advising learners utilizing
an IPPD-based platform because it is statistical (rather than deterministic), allows for updating the priorknowledge model of the learner at every learning
step, and accounts for multiple layers of skills work48

CHAPTER II

employer or educational provider remains a challenge. An integrative record should be an external
representation of the internal layers of personal
and professional development that an individual participating in the economy and society havesought and created. Certifying learning across
many modalities is challenging, but can be done.
We discuss approaches to this issue in more detailin Chapter III.

An integrative learning
record should be an external
representation of an individual’sinternal layers of development.
This requires a shift frominstitution-based to portable
credentials owned by individuals.

Appendix A contains a description of the Calhoun Discovery Program (CDP) that has been set
up to support integrative learning across the layersof the IPPD model through modular and diverse
learning experiences and customized pathways.
The CDP is in its early stages and works within
the constraints of traditional university curricula. Thus, the CDP cannot fully engage the open
co-creation paradigm of an IPPD-based platform
as discussed in this section. However, the CDP
does provide an ongoing proof of concept experiment of many of the integrative and adaptive
learning concepts explored in Chapters I and II.

standing of personal and relational “knowledgein action” (see the Introduction) would facilitate
the development of IPPD-based platforms that canrecognize and leverage the full range of skills ofdifferentiated learners.
An IPPD-based platform that recognizes thesum of the knowledge gained by an individual
would also require new structures for credentialing this knowledge. Such a change entails a shift
from credentials emanating from institutions toportable credentials owned by individuals.

2.5 Technological Tools for Aiding Adaptation

While badging (Zucker & Hicks, 2019) andmicro-credentials (Georgia Tech, 2018a) provide
possible solutions, they are not without issue. In“Credential Inflation and the Future of Universities” Collins (2002) argues that the pressure for
institution based micro-credentialing comes primarily from institutions of knowledge and is notbased on employers’ needs. Coffield (1999) also
warns against emphasis on micro-credentialing,rather than integrative knowledge embodied by
the learner. He warns that many learners will pursue badging or micro-credentials for the sake of
employment acquisition or promotion without
regard for mastery in their professional practice.
The issue of how to create and store credentialingoutside of a specific authority such as the original

Person-to-person tutoring and mentoring is
still one of the most effective ways to implement
adaptive and integrative learning (Bloom, 1984)
but it is not always an option, especially at a large
scale. Fortunately, a number of tools, platforms,
and technological solutions are being developedthat combine human expertise and technologicalstrengths to deliver integrative adaptive learningat scale.
2.5.1 Intelligent Tutor Systems
Intelligent tutor systems (ITS) show significant promise for implementing adaptive learningat scale. In essence, an intelligent tutor is a computer program designed around the concept ofmastery learning. Performance feedback enables
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learners to adapt their approach to learning a skill
until they reach a desired level of performance(Georgia Tech, 2018a). Likewise, intelligent tutors adapt over time. They are programmed withdomain knowledge and gain both tutoring andlearner knowledge through interactions. Cognitive
tutors are an especially promising subcategoryof intelligent tutors, although they are also complex and costly. Cognitive tutors aim to simulate
human-student learning both in terms of domain
knowledge and learner representation (Koedinger
et al., 2015; Aleven et al., 2016). This approach allows learners to self-pace and find a learning paththat works best for them. For example, the number and manner of training repetitions per skill
component and the order the skill components arepresented can vary while the intelligent tutor isalso providing rewards and hints. The learner gets
individualized support (tutoring), which has beenshown to increase performance by two standard
deviations and increase attainment for all students(Bloom, 1984; Ericsson, Krampe, & Tesch-Römer,1993) without requiring extensive interaction witha teacher.

online education, like that provided by intelligent
tutors, is much more effective than a passive massive open online course (MOOC) and provides significant promise for bringing adaptive learning togreater numbers of people (Koedinger et al., 2013).
Analytics from interactive large-scale learning
is important for developing intelligent tutors that
understand the engagement and progress of different learners and can use this information to customize learning paths, provide feedback, and evenpredict the level of mastery (or grade) a learner islikely to reach (Ginda et al., 2019). The data collected not only improves intelligent tutors but also
provides information that can be used to update thestructure of the domain knowledge. For example,
work at CMU has shown that some exercises widely used for teaching math in secondary education
are not as effective as others, and that the order ofproblem-solving skills traditionally used for teaching basic math skills in primary schools may not
be optimal (Koedinger, McLaughlin, & Stamper2014). Interactive learning can be further enhancedby availability of human experts to deal with unexpected or complex situations. For example, bothin the CMU and the Georgia Tech course, complex
questions are passed to TAs (Goel & Polepeddi,
2016).

Intelligent tutors (like many other artificial intelligence applications) are most effective when
the goal of learning is clear and fixed (Kelly,2016). Therefore, they are best at teaching standardized, domain-specific skills. For example, the Open
Learning Initiative (OLI) at Carnegie Mellon University (CMU) and Georgia Tech’s virtual teachingassistant (TA) program, Jill Watson, have had significant success in developing cognitive tutors forteaching programming to large numbers of students(Koedinger et al., 2015; Goel & Polepeddi, 2016).
The OLI has also had success in cognitive tutors
for teaching basic math concepts to secondary education students as well as introduction to writing,communication, and psychology to CMU students(Joo & Spies, 2019). Interactive learning throughInteractive adaptive teaching of some domain-specific skills at scale can increase efficiency
without losing quality. The experiences of CMU
and Georgia Tech show very little difference inlearning outcomes between students who took
the interactive learning versions of introduction
to computer science courses compared with those
who took the course in a traditional instructor format (Georgia Tech, 2018a). However, the students
that took the online version reported spending lesstime on the course (Georgia Tech, 2018c). Similarly, Boeing reports that in its training courses,
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learner trajectories can be optimized equally wellfor online learning and in-person learning depending on the skills sought (Ginda et al., 2019).
Moving some of the mastery of domain-specificskills to interactive learning would also free uptime for faculty to focus on teaching more complex domain-specific or domain-general skills.
A very promising future direction for interactive online learning is the development of hybrid
computer-human courses where the intelligent tutors deal with the teaching of the more repetitive
domain-specific skills, and educators (trainers,
teachers, instructors, and professors) teach more
complex domain-specific and domain-generalcomponents (Georgia Tech, 2018a). This could be
extremely valuable at a time when the need for domain-general skills connected to domain-specificskills is increasing, the number of people that require this type of training is expanding, and whereknowledge dissemination through technology enabled learning and social networks is driven by theunderstanding that decisions are based on rapidly
altering foundations.

of peer-to-peer and collaborative learning. This issue is beginning to be addressed by cloud-based
tools for writing, editing, and collaboration suchas Amazon Web Services (AWS), Google Suite,and Microsoft OneDrive used in combination with
Skype, Zoom, or another teleconferencing application. Not surprisingly, these approaches havegained in popularity during the recent closing ofschools during the global COVID-19 pandemic(Miller, 2020; Novet, 2020), and it seems likelythat they will continue to be used in tandem with
in-person teaching even after the pandemic.
2.5.3 The Internet of Things
A significant amount of technology-assisted adaptive learning focuses on cognitive skills.
However, our report proposes that adaptive learning should address the totality of human skills andlearning situations. One potential avenue for applying adaptive learning to the totality of humanskills is the proliferation of wearable, household,workspace and manufacturing items and equipment that are interconnected via the internet (theInternet of Things). The Internet of Things (IoT)
presents an opportunity for data-driven, interactive, and adaptive learning in varied contexts as
human activity data can be combined with tool,
environmental, and human-tool-environment interaction data. Opportunities are emerging to instrument, analyze, and enhance individualized
learning and collective cyber-human intelligencewithin all learning environments: the classroom,
the factory, the office, the studio, the farm, theroad, the hospital, and the meeting room. This
gives us the opportunity to better understand andsupport integrative personal and professional development.

2.5.2 Peer-to-Peer and Collaborative Learning
Another human-to-human issue that needs tobe addressed in interactive online learning is that

Opportunities are emerging
to instrument, analyze, andenhance individualized learningand collective cyber-human
intelligence within all learning
environments to better support
integrative professional andpersonal development.

The National Science Foundation (NSF) is
funding related research through the Future ofWork at the Human-Technology Frontier (FW51

CHAPTER II

HTF). One example is the Intelligent Cognitive
Assistants (ICA) research that is focused on thecreation of systems that demonstrate harnessing ofmachine intelligence to work collaboratively andenhance human cognitive and physical capabilities. This physico-cognitive systems research is
focused on contextual knowledge, sociotechnicalsystems, and natural human-ICA interfacing. As afollow up, the NSF has proposed using brain-likecomputing as the logic unit for ICAs.

ers to provide detailed longitudinal data.
IoT-supported training and learning can also
expand and leverage the emerging landscape ofsmart manufacturing and cyber-supported services. For example, the emerging idea of collaborative robots (cobots) aims to use worker expertisefor realization of higher-level tasks while passing
lower-level tasks associated with the 3 Ds (dirty,
dull, dangerous) to robots that are controlled by
the worker. This approach allows the worker tolearn new skills (operation, control, and maintenance of robots) while at the same time increasing efficiency, productivity, and safety (McAfee& Brynjolfsson, 2017). Caterpillar Inc. provides
technologies to companies for upskilling construction workers and supporting more efficient
production schedules. For example, construction
crews can combine drone supported scanning andmodeling of road sites with robotic construction
tools to reduce road construction time by 50%
while also significantly increasing fuel efficiency
and site safety (CAT, Inc., 2020). At the Adaptive Lifelong Learning Workshop held in October 2019, GE Appliances participants proposed a
seemingly futuristic scenario in which technicians
will use mobile 3D printers to create customized
appliance parts during troubleshooting and maintenance visits to homes thus eliminating waitingtime and follow up visits. The worker upskilling,
environmental sustainability, and service quality
potential of such approaches is significant.

The fast-evolving computing interfaces andmobile computing platforms will gradually allow
humans to interact with embedded computing intelligence in manners that are highly customized
to the environment. For example, in the Shirley
Ryan Ability Lab of Chicago, sensors in the roomsof patients use radio-frequency identification(RFID) tags to recognize which doctor has entered
the patient’s room and project information pertinent to the interaction of that doctor with a specificpatient on the patient’s health screen above theirbed. Doctors can customize consultation and treatment parameters. The doctor’s attention can shift
from the routine task of completing charts to thehigher-level tasks of interacting with the patientand making decisions. In a recent publication, Rikakis (2018) discusses current IoT applications
being developed by his team that allow therapists
to remotely supervise and adapt interactive rehabilitation at the home. These applications make itpossible for more patients to receive cost-effective
therapy while minimizing travel. The interactive,
data informed nature of the therapy engages patients in their recovery while also upskilling therapists to use IoT applications and high-dimensional
data for adaptive decision making. Rikakis also
recommends designing and supporting cyber-human learning in a way that leverages the ability ofexperts for interconnected decision-making acrossmultiple layers of skills and the ability of comput-

2.5.4 Virtual and Augmented Reality
Alongside the Internet of Things, virtual reality and augmented reality (VR and AR) are also
fast evolving computing interfaces that can enhance learning and improve collaboration (Henderson, et al., 2009). AR can provide just-in-timeassistance to any learner or worker performing
a complex task. For example, a digital image of52

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the components of a circuit and their functionality can be overlaid on the physical electric circuitthat someone is studying or fixing (Bohn, 2019).
Combined with remote assistance from experts formore complex challenges, AR-assisted tech support can allow each and every person to become
part of their own technical support team. This pluralized access to technology can get more young
people excited and empowered to join the techworkforce. Similar AR approaches can be used tocontinuously support and upskill current technicians on the job as tools and platforms continuously evolve and complexify. Critically, in thesescenarios, technology does not, and should not,replace the human technician. Rather, it allows anindividual to reskill and provide support to a large
number of clients as the need for tech support ofsmart infrastructure increases.

When technology-supported
learning is designed by learning
experts, and supported by cocreation processes, the resulting
data can be both big data andgood data.
eyeball movement and analyzing thousands ofsuch data sets. This can be combined with natural
language processing (NLP) and deep learning tooffer human brain-like functionality in assessing
writing skills, subjective responses to questions,and so on. Finally, it can help to predict paths andhelp with interventions to assist the realization of
the paths (Ginda, 2019; Madni, 2015).

Like augmented reality, virtual reality can provide immersive visualizations of physical spaces
to allow learners to develop skills using realistic
scenarios. For instance, VR can simulate certain
kinds of laboratories so that research can be conducted without risks typically associated with hazardous work environments (Thalheimer, 2015).
Likewise, for language learning VR can simulate
immersion in a faraway setting, e.g., a student in
Malawi can virtually visit Kyrgyzstan, minimizing
the logistical barriers of time, distance, and cost.
Moreover, VR applications have shown promisein creating educational experiences that benefit
students with special needs. The Jackson Schoolin Victoria, Australia, for example, has integrated
VR sessions with relaxation and/or meditative applications and experiences into its offerings withsignificant success (Herold, 2014). These technologies can also aid in detection and responsivenessto learning disabilities (e.g., dyslexia). Determinations as to the degree of attention required canbe made by storing large data sets associated with

2.5.5 Big and Good Data and AI-Supported
Learning
Each of the above technology-assisted learningand training scenarios rely on increased amountsof high-dimensional data for understanding human learning, its interactions with technology, andits interactions with the overall relational environment. When technology-supported learning is designed by experts, the resulting data can be both
big data and good data (data that can be used tounderstand and improve learning) (Koedinger etal., 2013).
Good data can lead to meaningful and impactful improvements in AI for adaptive learning. As
with the current intelligent tutors, we can develop
technology-supported learning where cyber andhuman intelligence work together to deal withsimple and complex skills in an integrative andadaptive manner. The aim of this type of learning
is to advance human capability (of the learner and53

CHAPTER II

the trainer) rather than replace their human capital. Combined with appropriate socioeconomic
mechanisms that address issues such as the digital divide and persistent inequalities of accessdue to gender, race, or ethnicity as well as othersocio-technical solutions to security and privacy(UNESCO, 2019), cyber-human adaptive learningat scale can increase access to learning and efficiency of learning (Georgia Tech, 2018a). In fact,
the World Economic Forum definition of Industry
4.0 calls for “smart factories that take advantageof the Internet of Things while also advancing inclusive and equitable growth of human capital”(Schwab, 2016).

dents back on track. Since the University initiatedthis technology-assisted advising in 2012, freshman fall-to-spring retention rates have increased
by 5% and graduating seniors are taking fewer
excess courses in completing their degrees. This
past academic year, the system generated morethan 55,000 individual meetings between advisers
and students to discuss specific alerts, all aimed atgetting students back on path to graduation (Georgia State University, 2020). It is important to notein this example that students and advisors workin tandem with technology to produce effective
adaptive learning pathways and experiences.
In addition to universities, companies like Autodesk (a software company that focuses on architecture, engineering, construction, manufacturing,and beyond) are shifting away from a “learn-to-do”
paradigm and preparing for a “do-to-learn” world
where the imperative for continuous professional
and personal growth drives the creation of new infrastructures to support seamless learning acrosssecondary and higher education and throughout
the arc of one’s career.

The growth of technology-supported learning
across all sectors of society and the economy canalso help produce data-supported advising for individualized learning pathways and careers. Data-supported advising is already showing promise
within universities helping to improve student
retention and degree completion for all students
including underserved populations. For example,
Georgia State University’s GPS Advising uses
predictive analytics and a system of more than
800 alerts to track all undergraduates daily, identify at-risk behaviors, and have advisers respond toalerts by intervening in a timely manner to get stu-

In Autodesk’s particular case, this means thatexpert tool-services must also become powerful
lifelong learning platforms. These platforms willallow users to simulate with data-rich visualizations what they know, don’t know, and need toknow to succeed. Essential to this research is thatusers and learners be able to securely self-simulate their potential futures by incorporating tool,
project, and team data as well as automated badging, external learning and credentialing systems(including universities), and aggregated industry
trend data.

Companies are shifting froma “learn-to-do” paradigm for
employees to a “do-to-learn”
approach across individuals’
careers. This means that expert
tool-services must also become
powerful lifelong learning
platforms.

Team knowledge and learning visualizations
are a critical component of Autodesk’s vision for
dynamic adaptive learning systems. Autodesk researchers understand the most complex work at a54

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Common cross-sector databases of up-to-date
workforce analytics that track and value the totality of skills can further enhance adaptive and inclusive career development and lifelong learning. It istherefore important to explore the potential for credentials to become a network of dynamic machinelearning agents that make learning recommendations based on the movement of learners throughthem. Blockchain technology offers a potential approach to organizing and credentialing integrated
professional and personal development learning
across all types of environments and experiences. Blockchain can track every learning instancewhen it occurs, creating an immutable record thatcan be easily verified and analyzed to assess thelearner’s interests and competences. This can help
create multiple pathways by breaking learning into
smaller bite-size chunks, which can be combinedin a myriad of ways. For example, institutions canoffer project-based education as an alternative tocollege courses and certify student work done via
Blockchain databases. This technology can also be
used to secure collaborations between universities
and industries that involve the use of shared repositories (e.g., student certification and achievementdata), introduce methods to design and continuously update global professional and personal development assessment mechanisms, and verify theauthenticity and accuracy of knowledge bases andrepositories. The data from these repositories canthen be shared with third parties such as employers or LinkedIn and integrated with learning platforms to help shape lifelong learning pathways.

The ability to assemble the“collective creative brain” ofa team will be crucial in the
coming years. This requires toolservices that can simultaneously
infer and visualize the proximal
learning potential of any given
team configuration.
company occurs on teams. While there has been
considerable experimentation with related organizational forms (e.g., agile development frameworks) and some progress with supporting technologies (e.g., Slack-like tools) there has been apaucity of research and productization in assembling teams with the optimal collective knowledge
to address specific complex project challenges.
Autodesk believes that the ability to assemble the“collective creative brain” of a team will be crucial in the coming years.
Autodesk researchers are addressing this issue
by developing tool-services that allow team managers to visualize the actual data-derived skills ofteam members relative to the specific constraintsof a project. Given the importance of teams today this function alone has considerable value,
but the ultimate goal of these services should be
to simultaneously infer and visualize the proximal
learning potential (lateral transfer of knowledge
between members) of any given team configuration. As we have discussed throughout this report,
knowledge in action is both personal and relational. In the near future, relational skills, such as theability of employees to teach and mentor on teams,
will be highly valued skills supported by a rangeof professional development opportunities.

The streamlined verification of integrative andcontinuing professional and personal development
can track and certify institutional and employee training and related achievements to facilitate
job transfers and career planning. For example,
Maryville University is currently implementing two strategic blockchain initiatives: the Ca55

CHAPTER II

reer-Focused Student Digital Profile and the Lifelong Student Digital Profile. The first initiative isbuilt based on the eight career competencies established by the National Association of Colleges andEmployers (NACE, 2019), which help Maryvillestudents develop the domain-specific and domain-general skills that employers have been
asking for. Once they complete the training, theblockchain solution will provide verifiable credentials with learning artifacts. The second initiative
will address lifelong learning needs and offer bothcurrent and former Maryville students the ability
to post, share, and verify their own learning records on Blockchain. New learning opportunities
will be presented based on the learners’ expressedneeds.

courses. Over the course of three years, the university
will create 50 new online or blended courses and 50
adaptive-learning courses. Professional developmenttraining will be provided to approximately 120 faculty
members from a minimum of five colleges and departments. Eight technology-enhanced, active-learning classrooms will be built.
The COVID-19 crisis has further emphasized
the need for well-structured alternatives to traditional
knowledge dissemination mechanisms and increased
the pressure for proactive and significant investments
in technology-assisted adaptive learning. Cross-sector partnership may be the most effective avenue tohandling the complexity, cost and urgency for suchlearning at scale. For example, the Carnegie Mellon
Simon Initiative aims to build a cross-sector learning
ecosystem supported by technological infrastructure
to improve educational practices and develop new“intelligent tools” that are easy for faculty and learners to use. The initiative aims to make all of the developed tools and methods available globally for any
individuals or institutions to adopt (Mission, 2020).

Together, AI and Blockchain have significant
synergistic potential not only for adaptive credentialing and advising but also for learning (Thibodeaux, 2018). For example, the Chinese adaptive
learning startup Squirrel AI claims that AI has
helped increase student test passing rate by 17%
and reduced the course dropout rate by 56%. So
far, Squirrel AI has developed over 30,000 “academic concepts” (Peng, 2018). Although not in
use in any formal education system yet, Amazon’s
Alexa has also developed over 100,000 skills andmany universities in the United States are using
the technology to create their own solutions suchas Oral Roberts University’s QM-mirror (Buckler,2019).

The promising tools and approaches surveyed inthis chapter are not without risks to their users andthe societies in which they flourish (Goel & Polepeddi, 2016; Kadel et al., 2019). These technologies holdthe potential to create much wider access to knowledge and learning. At the same time, they have thepotential to exacerbate existing stratifications withinsocieties if they are not available widely and equitably. For adaptive learning to facilitate the democratization of knowledge, opportunities to access and use
the tools and technologies must be universal. Neither
the networks nor the technologies that may facilitate
them are necessarily or intrinsically more participatory or democratic (Davies & Spicer, 2015) without
intentional commitments on the part of members tomake them so. Moreover, there are significant privacy
and security concerns as the amount and reach of data

To keep up with the fast pace of development oftechnology-assisted adaptive learning, employment
and training institutions will need to make intentional
investments and plans for updating content and tools
as well as professional development for existing faculty and staff. For example, in the fall of 2019, University of Central Florida (UCF) initiated a focused project to develop online, blended, and adaptive-learning
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collection continues to expand exponentially. Clear
policy and security approaches are needed to ensurethat this information is protected and that individuals“own” their records and data. Realizing the potentialof these approaches and tools requires serious discussion and action on the part of every member and sectorof society (government, industry, education, and communities) to ensure that the expansion and adoption ofsuch approaches do, in fact, expand equity, inclusion,and human flourishing, rather than re-entrench and intensify existing inequalities.

of cross-sector Point of Need Learning Platforms

In Chapter III we present a number of efforts under way to increase equitable access to adaptive learning. In Chapter IV we propose the future developmentbuild truly democratic learning societies by address-

that utilize and advance combinations of the learning
methodologies and technologies referenced in thischapter to support the inclusivity and adaptivity ofintegrative personal and professional development at
scale. As we look toward the future, we envision thatthe wide embodiment of IPPD-based adaptive learning will create participants who have deep commitments to the values of discourse, collaboration, andparticipation with which they will work with others to
ing all of the necessary social, economic, and politicalchallenges inherent in such a project.

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Chapter III:
Adaptive Learning Pathways: Examples
from Higher Education, Industry, andAcross Sectors

CHAPTER III

CHAPTER III

Adaptive Learning Pathways: Examples from Higher
Education, Industry, and Across Sectors
Authors: Rebecca Clark-Stallkamp, Shari Garmise
Co-authors: Thanassis Rikakis, Amy Arnold, Jared KeyelContributors: Andrew McCoy, Chip Blankenship, Colin Potts, Chrystal Harris, David Hare,
Jena Joo, Julie Greenwood, Kristin Wingfeld, Manny Contomanolis, Marsha Semmel,
Mukul Kumar, Randy Swearer, Robert Smith, Scott Bess, Sherrell Ashburn, Tom QuickIf we are to prepare people to meet theneeds of the 21st century workforce, wemust be able to offer multifaceted learning opportunities. The education we provide
must be customizable, just-in-time, and lifelong; and it must integrate professional and personal development within a pluralistic societal
context. This goal, however, cannot be met byhigher education alone. What we need are Quintuple Helix Knowledge ecosystems—cross-sector partnerships that span the five sectors ofeducation, industry, government, civil society,and socio-ecological environments (Carayannis,
2018; Rikakis, et al., 2019). The Quintuple Helix embodies what Ann Balsamo (2010) calls a“culture of participation” in which intelligenceis assumed to be distributed, multimodal, developed, practiced, and expressed through “the useof technologically-mediated informational andsocial networks” (Balsamo, 2010, p. 424).

To achieve distributed, adaptive
learning, we need cross-sector
partnerships that span the fivesectors of education, industry,
government, civil society, andsocio-ecological environments.
of learning and transparency of learning outcomes. This means being willing to cross traditional boundaries that artificially divide education, community, and economy into separate
sectors.
Fortunately, none of this is hypothetical or
futuristic. Very real pilots and trials exist in educational institutions, industry, and communities, and in many cases, they cut across sectors.
In this chapter, we survey a few of these pilots
and trials to provide evidence of what is alreadyoccurring and to exhibit what is possible. First,
we single out a few innovative college and university programs before turning to industry. Finally, we close the chapter by exploring a few
cross-sector programs.

To achieve this new kind of distributed,
adaptive learning, we will have to rethink current linear, fixed-term paradigms in educationand find ways to develop new models that afford
lifelong learning capabilities, increase accessthrough multiple modalities, expand alternative
cost structures, while enhancing transferability
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3.1 Adaptive Pathways in Higher Educationline courses and programs so that they can “reach
important milestones, improve skills, and engage
with a world of problem solvers like themselves”(EdPlus, 2018). This model of digitally-enhanced
education incorporates industry project-basedlearning, collaborative university programming,
lifelong learning support, and personalized professional development.

A number of universities recognize the critical role of adaptive and integrative education indeveloping lifelong learners who can easily navigate a more mobile and inclusive workforce. Realizing that the traditional higher education model
is one-size-fits-all, these universities are developing new pathways that align with the needs oflearners at any number of different points in theirlives, whether they are out of work, between jobs,
exploring upskilling or reskilling, or discovering
career possibilities during K–12. The fact is thatmost every learner now needs this adaptivity in order to continually develop new skills to stay aheadof perpetual change in business, technology, andindustry. These institutions are adjusting to meetthe unique needs, interests, and aspirations of today’s diverse body of learners. While we primarily
focus on North American universities, similar programs exist around the world.

By 2018 ASU’s EdPlus had graduated over
7,000 online students which has substantially risen
from the initial 1,200 enrolled in 2012. The program has grown exponentially in enrollment, managed programs, and collaborations. Besides the
Starbucks partnership, ASU has developed massive initiatives with the Mayo Clinic and Adidas
while expanding research being conducted in the
ActionLab, an innovative research space dedicated specifically to learning and teaching with technology integration. It is evident that ASU seeks
new ways to connect the learner to every opportunity available. For example, instead of competingfor enrollment increases, PLuS Alliance, which ispart of EdPlus, shares students between various
academic institutions. Instead of traditional enrollment competition, these universities work together
to leverage their resources for the learner to ensure
access to viable learning pathways regardless ofsocial, cultural, and economic background.

Multiple colleges and universities have developed innovative undergraduate programs that emphasize the discovery and development of personal knowledge for the 21st century. Here are just a
few examples:
Arizona State University (ASU). ASU has beenout in front in its efforts to serve the needs of learners everywhere. While developing ASU’s highly publicized partnership with Starbucks, which
launched in 2014, university leaders recognized
the growing need to deliver affordable, high-quality programs to underserved and underrepresented
communities from around the world. EdPlus wascreated to be the central enterprise unit at ASU
that focuses on the “design and scalable deliveryof digital teaching and learning models to increase
student success and reduce barriers to achievementin higher education.” EdPlus programs enable students, wherever they may be, to access fully on-

Bennington College. Bennington has madethe concept of field work central to its educational
programs since the college was founded in 1932.
Every Bennington student is required to complete
200 hours of qualifying field work each year. They
do so during a six-week Field Work Term (FWT),
which is held every January and February whenno academic classes are being offered on campus.
Students work in a variety of fields and geographic
locations pursuing interests that they discovered ordeveloped while at Bennington. The FWT allows
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students to “map a territory for study and practice that goes beyond the bounds of a traditional
major and hones their ability to thrive in a world
without givens, to tolerate ambiguity, and to findsolutions even when a path is not laid out beforethem” (Bennington College, n.d.). In the process,they are getting practical experience while making
professional connections that encourage them to“discover both their role in and responsibilities tothe world” (Bennington College, n.d.).

versity advances and implements the ideas aroundthe “sharing, experiential, entrepreneurial, subscription, and partnership” university and strives
to be a “Deliberately Innovative Organization,”
which focuses on whole person education, newadvising strategies and methods, and a distributed worldwide presence (Georgia Tech, 2018a, p.
6). The overarching focus of their work is a deep
commitment to lifetime education that reconceptualizes the university not as a physical place that
one enters and exits during predefined life stages
but rather as a platform for learners who are diverse across age, socioeconomic status, and otherbackgrounds.

Brown University. Brown’s Open Curriculum
is tailored to students who want “the freedom tostudy what they choose and the flexibility to discover what they love.” They are encouraged tobe the “architects of their own education” by developing their own personalized course of study.
The idea is that by making students responsible
for their own intellectual and creative development, they will become “deeply creative thinkers,
intellectual risk-takers, and entrepreneurial problem-solvers.” Brown expects graduates to leave
the university “prepared to thrive as independent,
innovative leaders no matter what path they pursue” (Brown University, n.d.).

Grinnell College. At Grinnell, all incoming students enroll in a one-semester, four-credit
course known as a First-Year Tutorial. Tutorials
are taught by faculty members from all academic departments who then become advisers to theirtutorial students until they declare a major fieldof study. It is the only required class at Grinnell
outside of the requirements to complete a major(Grinnell College, n.d.-a). As explained on Grinnell’s admissions page:

George Mason University (GMU) is working with Northern Virginia Community College(NOVA) to eliminate transfer barriers for community college students and create streamlined pathways toward bachelor’s degree completion in the
key sectors of technology, health, and education(George Mason University, 2019). NOVA students with less than 30 credits completed can join
the ADVANCE program at GMU and prepare totransfer into a GMU bachelor’s program (George
Mason University, 2019). NOVA and GMU arecollaboratively designing the joint degree pathways in close partnership with employers.

The rest is up to you. Because as you sharpen your strengths and your passions, you’llalso discover all the places your academic interests can lead you. This requires the freedom
to explore, along with focused guidance andmentorship for support. So take the lead shaping your studies—and know we’ll always haveyour back (Grinnell College, n.d.-b).
Hult International Business School is focusing lifelong learning efforts on building business,digital, and human skills for learners. Forty-fourskills were identified for this portfolio using employment data. For each of these skills a learner
can target a desired maturity level. The maturity
levels are drawn from the Lumina Foundation

Georgia Tech has also taken significant steps torethink the traditional university model. The uni61

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Model (one to eight levels), with Hult International Business School focusing on the first four levels(novice to independent) (Adelman et al., 2014).
Learners can adapt their learning journey based on
their current skill level, and the speed and breadth
they need in acquiring a new portfolio of skills.
The learning is focused on the learner demonstrating “what they can do” beyond what they know
via a range of practice and authentic assessment
activities.

language. Learners will also have the optionof taking on a project assignment from an individual professional anywhere in our global
network to master a specific skill—a flexible
alternative to a full course or co-op (2020,
para. 2–3).
Purdue University is collaborating with theCity of Indianapolis in partnership with community, industry, and academic leaders to bridge thegap between secondary and post-secondary education. This cross-sector partnership resulted in
Purdue Polytechnic High School (PPHS). The
developers of PPHS recognized that many highschool graduates were insufficiently prepared tosucceed in technical, STEM-related post-secondary programs and high-tech careers. PPHS was
designed to inspire and engage students throughan immersive STEM experience that delivers experiential, hands-on learning: “Students collaborate with fellow classmates, coaches, and industry
mentors to successfully complete projects that aredesigned by our industry partners” (Purdue University, 2019). As they develop critical thinking
and problem-solving skills—not to mention confidence—they leave high school with college credit,“in-demand industry credentials,” and preferredadmission to Purdue Polytechnic Institute.

Northeastern University. As part of its 2025
Plan, Northeastern is developing a network ofcampuses around the world to provide lifelong
learning opportunities to aspiring learners from allwalks of life. Each campus is designed to be anintercultural hub for learning and discovery in a
distinctly local setting. Learners become “members” of the Northeastern Lifetime Learning Network, which gives them access to the school’s professional programs from anywhere in the world
wherever they live and work. As members (notlimited to Northeastern graduates) they can form
customized pathways of learning via nearly 200
master’s and doctoral degrees, bootcamps, andcertificate programs. Much of the coursework andcurricula have been developed in cooperation withcorporate and nonprofit partner institutions andcan be delivered through multiple channels (onground, online, hybrid). Northeastern describes its
dedication to diversity of learning in its mission
statement as follows:

Another way that Purdue is expanding its
reach is through its non-profit public online university, Purdue Global, which provides personalized online learning experiences aimed specifically at working adults. Purdue Global concentrates
on delivering degree plans that are individually
tailored to those with prior learning experience—from college, work, and military. By allowing students to transfer eligible prior learning (transfer,experiential, and credit by exam) they can shorten
their term of study, increase the value of their priorknowledge, and save considerably on educational

Northeastern will expand the range and impact of global experiential learning to include
short-term experiences in heavily structured
majors such as engineering; semester-longexchange programs with global universities;
curriculum-based group projects abroad; anddegree programs that incorporate one or two
years of study and work in the host nation’s62

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The University of Waterloo. At Waterloo incoming undergraduates can choose an educational
pathway that allows them to pursue their interests
through a mix of classroom time and “learn by doing” experience. More than 120 courses includelabs, and the university offers a co-op programwith an extensive list of industry partnerships. For
instance, a student who might be interested in acareer in health care can choose from a variety of
programs that deliver the necessary science foundation while they explore their particular interests
in medicine, optometry, pharmacy, etc (University of Waterloo, 2019). It is expected that students
will refine their interests over the first two or three
years, after which they can apply to the professional program of their choosing.

fees and tuition. Indeed, according to the Purdue
Global website, online bachelor’s degree students
who graduated from Purdue Global 2018–2019
and applied eligible prior learning credits saved
an average of $29,000 toward the total degree(Purdue Global, 2020). This dedication to adaptive learning has certainly achieved Purdue’s goalof serving the educational needs of adult learners
who would otherwise not be able to return to a
traditional school setting or start new educational
pathways.
University of Central Florida (UCF). UCF
significantly increased access to its educational
programs by partnering with Florida’s state colleges (two-year public institutions) on a program
called Direct Connect. This program guarantees
admission to UCF upon completion of an associate (AA) degree or articulated (AS) degree fromone of the partner colleges, which, by policy, admit any high school graduate (University of Central Florida, n.d. -a). Over a decade of experience
with the program shows that the graduation rateof Direct Connect has been approximately thesame as that for students who were admitted directly from high school. Completion of the associate degree indicates that the student has alreadydemonstrated resourcefulness and resilience. The
percentage of UCF diplomas awarded to students
from underrepresented groups doubled as a resultof Direct Connect. More recently, UCF expanded
the Direct Connect concept beyond the region byoffering a direct pathway to online baccalaureate
degrees from UCF to graduates of partner community colleges and state colleges. In addition,
UCF Downtown opened in Fall 2019 as a physical partnership campus in Orlando where students
are taught their first two years by Valencia College
faculty and complete their degrees taught by UCF
faculty on the same campus (University of Central
Florida, n.d. -b).

Virginia Tech (VT). In addition to the examples above, hundreds of colleges and universities
have incorporated adaptive learning at the levelof an academic unit (department or school) rather
than the whole institution. For instance, the Myers-Lawson School of Construction at VT utilizes
a cross-sector curriculum with an innovative institutional structure and teaching approaches designed to improve adaptivity, mobility, and access.
The School bridges engineering and design education at VT and uses a transformative learning experience approach to change the way that students
learn Construction Management (CM). In place oftheory-laden, lecture-based instruction, educators
create a learning environment that favors visual
learning and working collaboratively with facts
and data on real world coursework (Holt et al.,2018). This approach allows CM students to reflect on learning styles, which is especially invaluable in cases where students might be struggling
in a course because the instructor’s teaching style
does not align with their learning styles (Holt etal., 2018).
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Western Governors University (WGU) is an
online, non-profit educational institution that appeals to working adults with clear career goals(Lohr, 2020). Conceptualized in 1997 by 19 governors wanting to increase constituents’ access tohigher education by making it more flexible andaffordable, WGU operates as a competency-based
university (Pichette & Watkins, 2018). This meansthat learning outcomes focus on “what students
know and can do” and are assessed based on learners’ performance of those competencies and/or
their project-based learning (Pichette & Watkins,
2018, p. 6). Other traits of competency-based education (CBE) offered by institutions like WGU
include self-pacing, credentialing for mastery, recognition of prior knowledge, and clear embeddingof competencies within the curriculum (Pinchette& Watkins, 2018). In a Gallup survey, alumni of
WGU stated that having a mentor as well as theability to choose programs they deemed as workforce relevant were two traits that led to their satisfaction (Etherington, 2018).

General Electric Appliances. Through its
GROW program, General Electric (GE) Appliances offers open employee workshops that are facilitated by leading experts on curated topics andtaught collaboratively by industry leaders—from
GE and beyond—as well as learning and development staff. The workshops focus on the four skill
domains of self-leadership, leading others, leading
teams, and leading businesses that are critical to
GE’s organizational goals and culture. These broad
skills correlate with GE’s desired work competencies, and they are the basis for measuring bothstrengths and areas of development for employees.
Most importantly, these workshops engage employees by providing opportunities to apply newly learned content in practical job contexts, thus
connecting broad skills development to task performance. Workshop offerings have increased in
number and expanded in scope from 2017 to 2019,and many of the courses offer digitally accessible
content or products enabling employees to have a
blended learning experience.

3.2 Adaptive Pathways in Industry

Boeing. Boeing’s approach to adaptive learning is based on designing an internal knowledgetransfer system that is enabled through the Boeing
Knowledge Network portal. It is capable of sharing information on program execution, researchachievements, and process changes while link-

In this section, we highlight a few examples
of industry-sponsored programs who apply theprinciples of adaptive and integrative learning.
These companies understand the need for theircurrent and future employees to develop targetedskills and competencies enabling them to meetthe demands of an evolving economy. Throughproviding new learning opportunities that aid
both personal and professional growth, they
ready their employees to adapt to new changes aswell as advance within the company. Each entity
singled out below supports an organizational culture promoting employee development because
company leadership recognizes that employee
development is critical to ongoing operational
success.

Companies apply the principlesof adaptive and integrative
learning to assist current andfuture employees in developing
targeted skills, preparing toadapt to new changes, andadvancing within the company.

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ing interface users to Boeing designated experts,
communities of practice, and resources such as
the Boeing Technical Journal. The Boeing Knowledge Network aims to provide continuous training
in the Boeing Values-Based Leadership (Boeing2020) model that is connected to specific educational content focused on the development ofmultilayer skills relevant to job functions. Someof the specifics are realized through the Degreed
program that emphasizes courses in project management, data analysis, and business processes.
Additionally, Boeing creates online content thatenables employees to pursue various learning certificates. Two examples are the MIT xPRO classon advanced manufacturing and the edX MicroBA
programs that will be completely online and cost
approximately $12,000 per employee. To upskill
the non-technical workforce, Boeing has provided a $10 million gift to establish a partnershipwith the National Science Foundation to accelerate training in crucial skill areas for the future US
workforce (National Science Foundation, 2018).
The resulting grants support design, development,
implementation, and analysis of online courses inmodel-based engineering, model-based systems
engineering, mechatronics, robotics, data scienceand sensor analytics, program management, andartificial intelligence. The intended outcome of the
grants is development of learning systems that can
maximize their effectiveness for a diverse base oflearners.

categories, mapped them onto competencies,
and aligned them to learning opportunities.
Individuals can go onto a personalized-learning system and see if their jobs are on the decline or on the rise. They can discover jobs
that they are interested in, see the associatedcompetencies, and take advantage of learning
opportunities that will enable them to make atransition. The transparency of AT&T’s system
is remarkable and empowering to employees(Alturi et al., 2017, pp. 5–6).
3.3 Adaptive Pathways that Cross Sectors
In the previous two sections we highlight examples of adaptive learning programs from the higher education and industry sectors. Here, we draw
attention to a number of innovative cross-sector
partnerships that are also taking place. These partnerships include K–12, higher education, community, industry, and government. The individuals
and organizations in each sector recognize thepower of collaboration for the purpose of creating
effective adaptive learning programs that meet arange of different needs. Out of these cross-sector partnerships arises research on how powerful
cognitive, psychomotor, and social-emotional
learning occurs, especially when implementing an
inquiry-based pedagogical approach.
Through the National Research Council, we
have consensus study reports summarizing research in cross-sector learning and guiding future questions for further inquiry (Hein, 2009;
National Research Council, 2000). Most importantly, the council’s reports connect cross-sector, inquiry-based learning to society’s ability toaddress complex issues, such as the 21st century
workforce, civil society, and issues of inclusionand equity. Cross-sector learning venues collectively cover many aspects of “lifelong, life-wide,and life-deep” learning (Dierking & Falk, 2016, p.

AT&T Inc. enables employees to personalize
learning to their specific needs and learning goals
through a mapped learning system. This enables
their employees to identify other jobs within thecompany as well as sign up for training opportunities that would facilitate advancement within thecompany. According to Julia Stiglitz of Coursera:
At AT&T, they have taken all of their job
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technology to manufacturing, construction, andhospitality. To do this, they shifted their focus towards graduating learners who were career ready.
To make such a focus a reality, they partneredwith engaged local businesses and industry, which
included GE, Norton Healthcare, United Parcel
Service, and Lantech. Out of these partnerships
emerged the Academies of Louisville.

Individuals and organizations
spanning K–12, higher
education, community, industry,and government recognize
the power of collaboration for
creating effective adaptive
learning programs.

3.3.1 Partnerships Bringing Together Industry and
Education

The Academies of Louisville launched in Fall2017 with the mission to “evolve public highschool education by equipping students with theskills and 21st century know-how needed to thrivein an ever-changing global economy” (Jefferson
County Public Schools, n.d., n.p.). JCPS’s academy model requires a high school senior to complete four core courses in a specific pathway ofinterest combined with access to other work certifications or direct work experiences. The integration of traditional core courses such as history, math, and English into the curriculum roundout each student’s chosen pathway. The program
got off to a good start in the 2017–2018 academic
year, with 11 of the 28 JCPS High Schools participating in the new model. Since then, the numberof academies has risen to 15, and business participation has expanded exponentially, from 20 employers to over 115 in Louisville. As a result, JCPS
now promises that after four years in an academy,
students will graduate with:

Industry and K–12•

Direct career and industry exposure

Located within North Central Kentucky, theJefferson County Public School District (JCPS)
provides a model of cross-sector collaboration.
JCPS serves the most populous county in the stateand encompasses the City of Louisville. In 2016school leaders embarked on an ambitious effort
to increase awareness of, and access to, pathways
outside of the traditional college degree route—everything from health services and information•

Industry and college field trips•

Job shadowing experience•

Junior- and senior-year internships throughSummerWorks•

Ability to earn college credits and industry
credentials•

Ability to earn work experience through co-2). The inclusive makeup of these partnerships ensures that individual participants are made awareof the multitude of learner-centered perspectives
and needs. An increased awareness leads to pluralistic discourse and adaptive learning ecosystems.
Cross-sector partnerships and interdependencies
between and among multiple sectors can provide
experiential learning opportunities creating virtuous cycles that support learners, industry, andsocietal development. For clarity of presentation,
we divide such partnerships into two subsections.
First, we highlight partnerships that involve industry and educational institutions (K–12 and higher
education). Then, we focus on partnerships thatspan community, industry, and academia.

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ops or apprenticeships•

Networking opportunities with local industry
professionals•

Success skills and a postsecondary transition
plantion of making-based pedagogies. Finally, the education group launched a major multi-divisional
initiative that builds advanced learning and credentialing systems for the purpose of integrating
learners’ experiences across educational segments
and their entire professional lives.
California Polytechnic State University (CalPoly) and Amazon Web Services (AWS), an Amazon.com company, partner to develop the Cal Poly
Digital Transformation Hub (DxHub) to provide
learners with real world problem-solving skills
while also developing cloud technologies essential
to addressing the digital transformation changes
in government, education, and non-profit sectors.
What makes DxHub unique from Amazon’s pointof view is that it is “adapting the AWS innovation
process to engage communities of stakeholders,
AWS resources, and Cal Poly and California State
University subject matter experts to quickly understand problems from the viewpoint of the customer and then formulate solutions that address
those needs” (Cal Poly, 2019, n.p.).

The United Way in Southwest Virginia
launched the Ignite Tech Talent program to develop a pipeline of industry-specific talent in the region. Their goal is to facilitate learners, beginningwith those in middle school, continuing throughhigh school, all the way to community and fouryear college programs, to engage in information
technology careers. Potential employers actively
participate in each stage of the learning process
via career fairs, internships, etc. Learning pathways are chosen by the learner, align to domain
specific and transferable skills and provide credit
while advancing education. These experiences andeducation culminate in full time information technology employment. To achieve this, the United
Way of Southwest Virginia leverages partnerships
across multiple school districts, community colleges, the workplace development board, and industries (United Way of Southwest Virginia, n.d.).

ASU established a partnership with Starbucksin order to provide tuition-free higher education
to eligible company employees. The program provides full tuition reimbursement for over 80 degree programs. In a similar vein, FedEx partners
with the University of Memphis to offer new pathways for their employees, 50% of whom do nothave credentials post high school. As part of the
program, eligible employees can earn high school
equivalency credits as well as college degrees.

Industry and higher education
Autodesk extensively partners with secondary and higher education institutions throughout
the world. The company has been able to growthese partnerships by creating a dedicated education group, while offering free full versions of all
software for students and faculty together with arobust learning platform called Design Academythat enables further collaboration. Additionally,
the Autodesk education group forms extensive
relationships with developers of external learning
platforms while partnering with community college systems and universities for the purpose of
supporting curriculum development and integra-

The Louisville chapter of the Kentucky Federation for Advanced Manufacturing Education(KY FAME) represents a partnership of regional
manufacturers whose goals are to implement career pathways and apprenticeship-style educational programs that create highly-skilled workers forthe 21st century. The KY FAME model allows as67

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sociated manufacturing employers to hire employees to work three days a week while attending a local educational partner for two days a week. Overa period of two years, the goal is for the employee
to simultaneously earn an associate’s degree while
gaining valuable work experience. Additionally,
the college credits earned by the employee aretransferable to a four-year college degree, thus
providing an additional pathway for the employee.

order to close the gap between needed skills by industry and future graduates with aligning interests,
the platform provides flexible, robust learning thatprovides obtainable skills directly related to robotics work. This platform allows educators and industry representatives to easily integrate new content. CS2N updates existing pre-apprenticeshipcommunity-college level certifications and associate degree programs from across the nation to address the evolving needs of its industry members.
CS2N also allows for “customizable online training materials that are available 24/7, micro-certifications that guide students toward a certification,
the ability for instructors to create classes, andautomated assessment features that enable instructors to track students’ progress” within the LMS(Carnegie Mellon University, 2019, n.p.). Throughthe CS2N, learners are able to track personal progress, peer assess work, and share accomplishments
on social media networks, personal web pages, orwith colleagues.

During the formation of KY FAME Louisville,
partners from manufacturing sought an ideal academic partner that would be local in proximity anddually serve as support for learners and also thecommunity. They chose Jefferson Community andTechnical College (JCTC) as a key partner. JCTC
responded by rapidly developing and implementing an advanced manufacturing technology curriculum. This reciprocal partnership serves boththe college and industry by providing workplace
opportunities for learners while aligning with local industries’ needs. In doing so, KY FAME generates a reputation for developing workers thatmeet 21st century skill requirements. Since 2015
the program has grown to 50 annual participants.
Likewise, the community college will open a new
facility in Fall 2020 dedicated entirely to advanced
manufacturing.

FirstBuild based in Louisville, Kentucky andbacked by GE Appliances, identifies as a “co-creation community” that serves as a cross-sector
partnership model between the greater Louisvillecommunity and GE Appliances. By moving part ofits innovation process beyond its brick and mortar
location to an open community of practice, where
community members learn to design and innovate
through participation in a makerspace, GE helps
to grow community talent and gain insight for innovation, beta testing, marketing, and manufacturing on behalf of its design department. As GE’s
projects undergo the feedback cycle with the local
community, the company harnesses the resulting
collective knowledge for product improvement.

Cross-sector partnerships may span both local
and national dimensions. For example, Advanced
Robotics for Manufacturing (ARM), headquartered in Pittsburgh, the home of Carnegie Mellon
University’s (CMU) National Robotics Engineering Center (NREC), serves as the nation’s largest
learning collaborative in robotics and workforce
innovation. ARM and CMU partner to build theCS-STEM Network (CS2N), an inexpensive, custom-built learning management system (LMS) toaddress national workforce development issues(Carnegie Mellon Robotics Academy, 2020). In

In the greater Washington, D.C. metropolitanarea, Alpha Corporation (Alpha), a woman-owned
engineering and construction consulting firm, has
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focused on building forums for cross-sector collaboration between startup communities, stateand local governments, academic intuitions, andother stakeholders in the built environment. Thisinitiative has emphasized providing practical andmutual opportunities for education, ideation, andcommercialization to organizations across thehighly complex and often ‘slow-to-adapt’ designand construction industry (Agarwal, Chandrasekaran, & Sridhar, 2016). In taking this approach,
Alpha looks to bridge the gap between theoretical solutions and industrial value by increasing
project-based learning environments to support
buildings, civil infrastructure, transportation, andutilities. This work has led to the creation of academic and commercial partnerships to foster theincreased integration, implementation, and adoption of digital solutions across architecture, engineering, construction, and project controls.

Initiative,” n.d.). As a result, early-stage organizations working to navigate the complex value chainof the built environment have a clearer path to realization while existing industry stakeholders areable to better understand the advancements andchanges to the industry.
3.3.2 Community, Academia, and Industry
Community partnerships integral to diversifying
and innovating learning pathways
The Institute for the Future’s (IFF) 2019 book,Partnership Power: Essential Museum Strategies
for Today’s Networked World provides guidance
for museum professionals wishing to create andsustain effective learning partnerships and collaborations. As such, the institute, located in Palo
Alto, California, collaborates with the Cincinnati,
Ohio-based non-profit KnowledgeWorks to produce regular “navigating the future of learning”
forecasts that identify drivers of change, thematic
provocations related to each driver, and examplesof actual projects currently addressing these drivers (KnowledgeWorks Foundation, 2020). Similar
collaborations that use systems theory as a foundation and have a goal of creating collective impact
have the ability to span geographic location for the
purpose of addressing complex challenges related
to today’s rapidly changing world.

The Northern Virginia Smart Region Initiative(NVSRI) focuses on strengthening the regional
technology cluster in Northern Virginia throughcollaborative learning for professionals, and in
2019 received an i6 Grant from the US Economic Development Administration (EDA). NVSRI
brings together local and national stakeholders in
the design and construction industry from acrossthe Northern Virginia region. These stakeholders
include Arlington City and the City of Fairfax,
Virginia Tech, Northern Virginia Community College, Amazon Web Services, Alpha, the Center for
Innovative Technology (CIT), Smart City Works
startup actuator, Refraction coworking community and Cushman & Wakefield. Together, NVSRI
is focused on mitigating the risk profile of early-stage construction and property technology
startups throughout the region, while at the sametime enabling easier access to project-based resources and pilot opportunities (Smart City Works,
Inc. et al., 2019; “Northern Virginia Smart Region

Universities have much to contribute to theircommunities, not only by building town-gown relationships but also by actively engaging throughcommunity service and volunteerism. One such
example is Fort Valley State University’s iHelp
Center. The iHelp Center is working with a network of community partners to “flood the streetswith iHelp scholars and volunteers” (iHelp Center, 2020). The university aims to address genuine
needs in the community while improving student
retention by making volunteerism compulsory
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CHAPTER III(Association of Public & Land Grant Universities [APLU], 2019). Using the concept of “communiversity,” iHelp prepares students to be service-centered leaders of the future (iHelp Center,2020). Community needs are also being addressed
through a partnership between the local Universityof California, Riverside; the Community Foundation; and Riverside Unified School District. The
partnership provides service-learning opportunities and community-based academic internships
for students, while providing the university with abetter understanding of the Riverside community,
thus increasing its capacity for affecting positivechange within the region (APLU, 2019).

school due to affordability issues can receive financial assistance. Once they are re-enrolled, students have access to bolstered academic advising,which helps keep them on track toward a degree(APLU, 2019). Not only does this program benefit
students, it helps the Cleveland area by increasing
the talent pool for local employers. After helping
230 former students return to their studies in its
first year, (Re)Connect to College is now scaling
up its efforts by implementing targeted outreachstrategies using historical data; providing morecomprehensive student support services; tracking
employment outcomes for participating students;
and developing new models for broadened outreach to students with some college credits but
no degree, including students who did not attend
Cleveland State University (APLU, 2019).

Community support for non-traditional learners
Wayne State University partners with the Detroit Regional Chamber of Commerce and othercommunity stakeholders to re-engage adult learners who have completed some college but left
school prior to degree completion. This partnership serves that specific audience by providing
new information and resources regarding higher
education opportunities in the area. Using artificial intelligence, prospective students use the platform to ask questions about college 24/7 throughFacebook Messenger. This effort is part of a muchbroader partnership between Wayne State University and the Detroit Regional Chamber that supports adult learners in making progress toward theDetroit-wide goal of boosting college attainment(Lumina Convening, 2019; Wayne State University, 2019b).

The Phoenix Rising Initiative at the University of Lynchburg is a grant-funded workforce program for young adults ages 18–24 who have been
involved in the criminal justice system and thus
are seen as disengaged youth. The program utilizes the Gallup StrengthsFinder assessment to determine the participants’ talents and strengths. Eachparticipant is then connected to Journeys, an online interface for career and technical education, to
explore career options (Journeys, n.d.). The “journey” is undergirded with a curriculum, co-developed for Phoenix Rising by Edmin.com and The
Learning Company in Durham, North Carolina.
The Journeys Map App was designed based on
the realization that there is a high ratio in K–12
of students to career counselors, specifically about
482 students to one counselor, and that many students are in danger of being left behind in termsof career guidance (American School Counseling
Association, 2015). Journeys is a learner-centric
platform designed to create personalized and highly relevant pathways based on an individual’s in-

In Northeast Ohio, Cleveland State University
and College Now Greater Cleveland collaborate
on a grant-funded project called (Re)Connect toCollege, designed to help “comeback” students
earn their degrees. Together they identify students
who left the university before graduating andhelp them re-enroll. Students who might have left
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terests, strengths and skills. Journeys also serves
as an aggregator of data from a wide range ofsources to ensure learners of all ages can explore
their options. Examples include O*NET OnLine,
College Scorecard, and Indeed.com so that a large
amount of data is provided with each search result.

COG efforts must center on collaboration between
a public university and an external organizationsuch as another university, community college,school district or local government (APLU, 2019).
All COG projects must align with at least one offive priority investment areas: Strengthening the
K–12 pipeline; rethinking financial aid; engaging
faculty; partnering with employers and workforce
organizations; and leveraging community assets(APLU, 2019). Since 2017, APLU and USU haveawarded grants to 19 institutions. Of those, 14 invest in some type of partnership that focuses on
three issues related to adaptive learning throughcross-sector approaches: Building new pathways;
better integrating experience into the curriculum;and creating better transitions in and out of school(APLU, 2019).

Non-profit-led cross-cutting partnerships forsharing resources
The Association of Public and Land Grant Universities (APLU) has a number of commissions
that bring together representatives from acrossmember universities to address critical issues ofthe day. The Coalition of Urban Serving Universities (USU) serves as one such commission. USU
is a network of public urban research universities
that leverages the intellectual capital and economic
power of their institutions in order to improve theircommunities. “Guided by the belief that public urban universities are anchors in their regions, USU
undertakes a variety of efforts to build a skilledworkforce, drive robust economic growth, address
inequities, and enhance community sustainability.
To achieve these aims, USU institutions partnerwith key stakeholders in their communities such
as K–12 systems, local businesses, health systems,
workforce organizations, community organizations and philanthropic foundations” (Associationof Public and Land Grant Universities & Coalitionof Urban Serving Universities [APLU & USU],
n.d., n.p.).

Ithaka S+R is a non-profit organization thatprovides research and strategic guidance to help
the academic and cultural communities serve thepublic good and navigate economic, technological, and demographic change. The organization
partners with higher education institutions, consortia, state systems, philanthropies, and othereducation organizations to collaboratively designand evaluate projects that make higher education
more accessible to diverse learner populations.
The Adaptive Learning Statistics (ALiS) is one
example of Ithaka S+R’s work. In 2017, Ithaka
S+R co-led a multi-year pilot initiative in Maryland which brought together faculty from multiple two- and four-year institutions to develop andadopt a common adaptive learning courseware toteach introductory statistics using active learningand flipped classroom pedagogical approaches.
The details of the project findings and lessons canbe found in the final report (Joo & Spies, 2019).
One lesson worth highlighting is that the cross-institutional collaborations created by the pilot enriched ongoing conversations about improving

One way the APLU-USU partnership advances its goals is through Collaborative Opportunity Grants (COGs), which support public urban
universities working to advance student success,degree completion, and community transformation. Institutions awarded COGs undertake a variety of nascent reforms touching virtually every
aspect of the student experience to establish theenvironment necessary for students to thrive. All
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math education, both within and across the participating institutions. The project also contributed tothe statewide discussions around developing andsharing of openly licensed instructional materials
and resources among faculty across Maryland colleges and universities. Ithaka S+R also recently
released a playbook on how to develop successful collaborative networks in and around higher
education to drive systemic change that will havepotential for far-reaching social impact (Joo, Selingo, & Alamuddin, 2019). The playbook provides
a conceptual grounding for large-scale collaborative networks that tackle cross-cutting challengesof student success, economic mobility, and racialand socioeconomic equity. It also unpacks a set ofcritical steps for starting and sustaining successful
networks, with rich examples from the field to illustrate.

or Advanced Placement courses during their highschool careers. Of these students, 95% attend college and 5% enter the military. Members of theclass of 2017 received $2 million in scholarshipfunds (Results, 2020).
CMR Institute, a non-profit healthcare education organization in Roanoke, Virginia, leverages
a variety of delivery strategies to provide partners
in the pharmaceutical and life sciences industries
with flexible, customized, and continuous learning opportunities. The CMR catalog of over 100
eLearning courses is extended through a variety
of instructional approaches, including microlearning, podcasts, videos, webinars, and the option of
in-person specialized workshops. In addition to
supporting industry partners through innovative,
technology-mediated strategies, CMR has alsocollaborated with higher education institutions todevelop credit-bearing learning programs for industry professionals.

An Achievable Dream (AAD) is a unique collaboration among public school systems and community and corporate partners in Eastern Virginia.
AAD, Inc., a 501 (c)(3), promotes the educational success of students that have been identified as
requiring additional interventions due to social
risk factors. AAD provides a holistic approach toeducation for those students who will best benefit from extended learning time, social and moral
learning, additional enrichment experiences, additional technology, and parent/student contracts.
AAD recruits and coordinates broad-based collaboration with health systems, local military, fire
department, emergency responders, law enforcement, colleges and universities, sponsoring corporations, families, local parks and recreation, local
businesses and civic groups, and private donors.
Students in these schools score as well as, or higher than, other students in the state of Virginia on
the state’s Standards of Learning (SOL) exams.
Other outcomes include a 100% graduation ratewith the majority of students enrolling in honors

3.4 On-Ramps and Off-Ramps
The development of various new pathways
between institutions, industry, community, andgovernment cannot be implemented without due
consideration of viable on-ramps and off-ramps
that facilitate transitions and cross-sector interdependencies for supporting learners’ extraneous
needs (Weise et al., 2019). On- and off-ramps needwell-designed entry and exit points in order to (a)advance learners’ economic mobility in the shortand long term, (b) supply high-demand industries with skilled workers, and (c) catalyze change
within society to re-envision traditional pathways
and redesign the structures that exist for a broader
array of learners (especially income constrained
learners and workers). These on-ramps consider
their learners’ needs with wrap-around support
systems such as transportation, childcare, careernavigation, basic needs, and financial aid. On72

CHAPTER III

ramps also acknowledge the need for a core curriculum for bridging or upgrading, as well as otherforms of professional development. Ramps needto encompass re-engagement services and strategies that would enable learners to achieve learning goals as they require them through on-the-job
experiential learning, competency-based assessments, and integration of career and academicplanning (Weise et al., 2019). Ultimately, ramps
bridge gaps between sectors and help leverage
partnerships to develop greater access and mobility. Many of the cross-sector pathway examples inthis report are effective because of built-in support
mechanisms developed as integral parts of the innovative changes being implemented.

or learning are a required necessity to work, live,
and contribute. Too many present-day institutions focus on the overserved and well-educatedpopulations of America, which makes them unaffordable to a large swathe of prospective learners(Goldrick-Rab, 2016). As The New York Times put
it in a recent opinion piece, the cost of college is“far greater than [even] tuition,” with many people deferring significant life events such as marriage or homeownership as a result of student loandebt, and many people completely forgoing further education altogether or seeking alternatively
undervalued pathways to learn (Is It Still Possible
to Pay for College?, 2019, para. 1). New financial
models that allow a diversified learner populationto access affordable and more flexible learning opportunities will decrease barriers to various modesof learning and to the overall knowledge economy.

3.5 Expanded Access and Reduced Cost
In order to create successful knowledge democracies that can cross all sectors of society,there must be effective intercommunication, exchanging of resources, and strong interdependent
relationships. Essentially, sectors operating insilos need to reach out and start dialogues about
how they can support accessibility to knowledge
for all their constituents. The examples given inthis chapter show that such collaborations alreadyexist and succeed while significantly advancing
inclusion. If a learner is unable to afford an institutional pathway such as a traditional four-year college degree, there are alternative paths that offer
equal value at a significantly reduced cost acrossdifferent sectors.

Inclusion necessitates varied pathways with alternative cost models as well as expanded admissions models for accommodating a more diverse
learner population and many types of personal
knowledge. Even moderate adaptations to admissions criteria and processes that are combined withsupport structures for different types of learners
can have significant effect on inclusion. ASU, forexample, is moving towards an earned admission
model. Instead of paying tuition up front or producing proof of suitability to study at the institution, ASU provides courses online to progress
towards admissions to an ASU degree. To enroll,
ASU requires no transcripts, no formal applica-

The cost issue must be faced head on, particularly because historically high income andwealth inequality directly impact many learners’
opportunities to access the education they need(Charlotte Report; Haveman & Sneeding, 2006).
Education is no longer required only for the advantaged few in the knowledge economy (APLU& USU, 2019). Instead, certain levels of training

Inclusion necessitates varied
pathways with expanded
admissions structures and new
financial models.

73

CHAPTER III

tion, and eight weeks of time to complete a course.
The most significant aspect is that ASU does not
require payment for a course until it is completed
and passed by the student, which reduces the risk
and financial stress associated with applying fora traditional four-year degree. Earned admission
allows students who have exited traditionally restrictive educational pathways with debt and low
GPAs to access learning on their own terms. Students can pursue a pathway of their own choosing while demonstrating the ability to succeed
based on personal merit and motivations. Moreover, when a student achieves admission to ASU,
earned admission credits are transferred towards
the degree pursued.

costs and access is through Open Education (OE).
OE has increased access to various pathways andaffordable learning credits by reducing direct material costs for the learner. One of the most promising aspects of OE are Open Educational Resources (OERs)—free textbooks and other learning
resources that can be retained, reused, revised,
remixed, and redistributed (Bliss & Smith, 2017)
thanks to the use of open licensing (e.g., Creative
Commons). Many US institutions are implementing OER usage through new approaches to instructional design. Librarians across institutions in
the US digitally curate OER repositories and promote usage of the materials in professional development workshops for faculty. As a result, OERs
are saving learners millions of dollars per annumin higher education (Bliss & Smith, 2017).

Purdue Global’s access model is saving its students significant amounts of money by allowing
the transfer of non-traditional credit via portfolio assessment. In 2018, incoming Purdue Global students who passed EL206 and submitted aportfolio for evaluation earned an average of 33
quarter credit hours toward their Purdue Global
undergraduate degrees. The National Universityof Singapore presents another example of rethinking financial as well as access models across an
ecosystem of institutions. In 2018 the university’s
programs were reassessed and restructured withseveral other local universities in eight priority or
emerging industries to provide better enrollment
access and reduced the financial burden for current students and alumni (APLU & USU, 2019). A
number of American universities are implementing adaptive approaches to admissions as well as
cost structures—including the UCF, Georgia State,
and the University of Maryland, Baltimore County(UMBC)—with a positive impact on the diversityof the student body as well as completion percentages (Georgia State University, 2019).

3.6 Cross-sector, Learner-Centric
Credentialing
A key feature coming out of the cross-sector
paradigm shift that we propose is the need for atransparent system of credentialing. The fast-paced
and changing nature of the 21st century economy
requires it. Learners at all life stages must be able
to skill up or re-skill quickly in order to smoothlytransition in, out, and across the workforce. This is
only possible if there is full transparency when it
comes to documenting skills attained from learning experiences. One assumed way to achieve thisis through stackable credentials or badges earnedin competency-based frameworks. Collins andHalverson (2018) explain that eventually course
streams and disciplines could be streamlined to reflect the competencies needed for jobs. Instead of
earning a degree, a learner would earn stackablebadges or credentials that employers require forcertain sectors (Collins & Halverson, 2018).
Stackable badging, however, is only one way
to reimagine credentialing—and it is limited byAnother important way to rethink educational74

CHAPTER III

the fact that it tends to reify internal institutional
credentialing issues. We need to shift the growinginterest in developing new forms of credentialing
beyond the narrow scope of training task performance or building specialized skills. Portable credentialing should address integrative personal andprofessional development (see Chapter I) and encompass sectors beyond the confines of academic
institutions. If the goal is to increase access andbuild seamless, integrated, and customizable education and training pathways across sectors, then ashift to competency-based or skill-based learning
is only a partial response to placing the learner at
the center of transparent credentials. Lee Rubenstein stresses the importance of alternative andlearner-centric forms of credentialing:

dentials, (b) organize and own the record of theircredentials, and (c) carry their credentials fromsector to sector throughout their lives (Whitney,
2010).
A major concern of alternative forms of credentialing is how to prove skill attainment andensure quality and mobility of control. To addressthese issues, the University of Melbourne is developing a blockchain-based credential systemdesigned and owned by learners (APLU & USU,
2019). Blockchain algorithms secure credential
information, learner data, and ensure the survivability of the learning record, allowing learners to
own their academic records and achievements andsuccessfully track them over multiple institutions
and many years (Knowledge Media Institute &The Open University, 2018). A unique feature ofblockchain is the ability to let learners post theirverifiable learning artifacts such as a video clip, apiece of music, or a computer programming code,
which can provide instantaneous audio and visual evidence of a learner’s mastery and proficiency
of certain knowledge subjects and skills. Blockchain can be used to provide a sharable and verifiable learning transcript that incorporates digitalbadges, certificates, awards, and micro-credentials
alongside transcripts. Other cooperatives such as
the Digital Credentials Consortium (DCC) led by
MIT are also focusing on transparency of learnerrecords. Comprising nine universities from fivecountries, DCC is working to create a shared platform and standards to issue and verify what students have learned across sectors—not just the educational institutions that they might have attended(McKenzie, 2019). In both examples, the goal is toincrease reporting of skills attained across sectors
and depict learning that engages both personal andprofessional development.

Leaders need to understand and value thealternative credentials that are available. If I’m
an employer, I need to be saying, “Here are
the 12 competencies that I need you to get. I
don’t care where you get them. You don’t needto spend $200,000 in four years to go do that.
You just need to show us some proof” (Alturi
et al., 2017, p. 4). The idea that you enter atthe bottom and four-plus years later you end at
the top and you’re done is a fiction. It doesn’tmean anything anymore. Learners need to beable to enter at any different point along theway, take what they need, and get going to do
whatever it is they wanted to do. We have totry to find a way to help alternative credentials
become a currency among learners that is respected and valued by employers (Alturi et al.,2017).
The learning transcript is currently owned anddetermined by the institution from which a learnerhas graduated. To advance inclusive and integrative personal knowledge, we must ask if there canbe a common platform for learners to: (a) earn cre-

A number of organizations and higher educa75

CHAPTER III

tion institutions are exploring the possibilities ofbroader based, all-encompassing platforms forcredentialing. For example, the American Association of Collegiate Registrars and Admissions
Officers (AACRAO) and the Association of Student Personnel Administrators (NASPA) channel
the idea of electronic medical records (Green &Parnell, 2017). Reasoning that if an electronic
medical record can follow a patient throughout the
medical system, then it is possible for an educational equivalent to track and detail all experiences and knowledge from various activities in work,
education, and community interaction (Whitney,
2010). Known as Comprehensive Student Records(CSRs) or Electronic Learning Records (ELRs),
the AACRAO and NASPA published a report in2017 for pilot projects in several universities on
CSRs (Green & Parnell, 2017). The results indicatethat CSRs demonstrate a broader set of competencies and skills to employers while easing employer risk in hiring. Most important, CSRs emphasize
learner access and control of their transcript whileallowing for transparency in educational reporting
throughout a learner’s lifespan (Green & Parnell,2017). While research is in its infancy, the goodnews is that interest in and need for these platforms is growing.

76

Chapter IV:
Point of Need Learning and Inclusive
Learning Societies

CHAPTER IV

CHAPTER IV

Point of Need Learning and Inclusive Learning Societies
Authors: Jared Keyel, Thanassis Rikakis, Anne KhademianContributors: Todd Nicewonger, Sylvester Johnson, Dale Whittaker, Michael Richey,
Taryn Cardone, Rebecca Clark-Stallkamp, Catherine Amelink, Ralph Hall, Matt HoltW

e conclude this report by returning
to the theme of social inclusion.
In previous chapters, we have discussed the interconnected nature of inclusion, adaptation, and integrative development. Figure 4.1
shows how this interconnectedness works in practice: Learning environments that leverage inclusive, relational knowledge provide support for the
integrated professional and personal developmentof individual participants. Integrative development
brings forth the different skills, competencies, andaspirations of learners, which drives learning adaptation. Adaptation supports difference, thus creating diverse relational contexts.

Developing learning societies in which members are committed to lifelong learning for all
requires addressing a number of complex challenges. It necessitates, for example, understanding and addressing the linkages between learning,
health, nutrition, and a safe environment (UNESCO, 2000). It also requires work at all levels andwithin all sectors of societies to rectify inequalities based upon gender, race, class, ethnicity, andreligion (UNESCO, 2019). Serious and ongoingquestions concerning the appropriate combinations and safe deployment of technologies, how to
train and support committed educators, and how tocreate high-quality learning materials must all be
addressed. Governments, industry, and civil society each have parts to play in the funding and development of learning throughout the lifespans of
all members of society. Moreover, the establishedmissions and related value systems of educational
institutions also need to be examined.

Throughout this report, we have elaborated
many promising examples of individuals, organizations, and institutions working to implement
adaptive lifelong learning. However, each of theseexamples on its own presents only one piece of the
puzzle. What is necessary, we believe, is a paradigm shift in social inclusion spurred by the wide
adoption of integrative and inclusive adaptive lifelong learning. Indeed, given sufficient time, wide
adoption of these learning practices can address
one of the many crucial dimensions that lead to theemergence of inclusive learning societies (Rees &Bartlett, 1999b; UNESCO, 2000).

In the remainder of this chapter, we explore
what it will take to get us on the path to a paradigm
shift in social inclusion. We propose leveraging
existing and emerging cooperative learning communities that engage all layers of skills in our Integrative Professional and Personal Development(IPPD) model. The next step is to create Point of78

CHAPTER IV

Figure 4.1

Inclusion, Integration, and Adaptation are Interrelated
Inclusive Relational
Knowledge

Adaptive Learning

Integrative Professional
andPersonal Development

Need Learning Platforms (PNLP) that can begin toconnect smaller communities of integrative learners into inclusive, adaptive learning networks. Theinteraction of novel learning practices in these
networks with established practices from existingorganizations can disrupt the current paradigm andgradually lead to societal change and an inclusive
knowledge economy.

of knowledge. As a result, participation in itself
becomes a form of knowledge. Adaptive learning
practices that incorporate participation as a meansof addressing diverse personal knowledge needs
have a much better chance of identifying—andvaluing—all types of knowledge. This, in turn,increases inclusion, which leads to further adaptation.

4.1 Participatory Knowledge and Flatter
Organizations

Pateman (1970) notes that as far back as the
18 and 19th centuries, thinkers including JeanJacques Rousseau and John Stuart Mill held that
democratic participation throughout society is itself a form of education. Both philosophers understood that participation—control over the process and outcomes of the decisions affecting one’s
life—can teach citizens to better understand theviewpoints and needs of others. In fact, the more
one participates, the better able one is to do so.
Daily interaction, dialogue, and co-creation withothers can open up new possibilities for pursuingand developing a wider array of knowledge andachieving self-actualization. Crucially as well,studies have shown that individuals are happierth

If learning and knowledge practices are tochange, it is vital that we expand our understanding of knowledge. We must move beyondsocietal and organizational biases that favor
only outcome-based, institutional, and standardized knowledge and instead engage with the full
spectrum of knowledge and its varied types andmanifestations (Hope & Martelli, 2019). Inclusive learning societies, as we envision them, arebuilt upon the process of participation in learning. Members of a learning society seek to embody process-oriented creation and dissemination
79

CHAPTER IV

and have higher levels of satisfaction when they
can participate deeply in the creative endeavors of
their workplace (Knudsen, Busck, & Lind, 2011;
Pateman, 1970; Rothschild-Whitt & Whitt, 1986).

Inclusive learning societies
are built upon participationin learning, which leads toflatter, relational structures thatincorporate a much wider set ofexperiences.

Learning through the process of inclusive participation leads to relational structures that are flatter, less rigid, and less hierarchical than traditionalorganizational approaches to knowledge. Because
everyone is learning from everyone else, the interactions and organizational structures becomeless hierarchical. Knowledge, in such settings, is
not viewed as power but rather as a fundamentalbuilding block of inclusive growth. The more eachmember of the community knows, and the greater access each has to knowledge co-creation, thebetter off all members become (Rothschild-Whitt,
1979, 1986). Less hierarchical modes of interaction can create a virtuous cycle in which individuals are able to learn with a commitment to valuing
and working across multiple knowledge practices, and continue to build deeper capacities to doso from their engagement with others (Pateman,1970). This builds reciprocal trust in and between
learners and learning institutions while facilitating
community building and the emergence of inclusive learning societies. Because these societies focus on the process of inclusive participation andtherefore facilitate much flatter interactions andrelationships within and across organizations, they

incorporate a much wider set of experiences. As
a result, this diversity of experiences, approaches,and understandings creates richness and dynamicity. When members exist and interact in the midstof complex and diverse networks, dialogue begins
to emerge that crosses and transcends boundaries
and fundamentally deconstructs pre-existing presuppositions (Osborne, 2015). Having said this,
it is important to explain that we are not arguing
against outcome-based knowledge practices. Rather, we are proposing that communities that achieve
inclusion through participatory processes are alsoable to produce transformative outcomes (Page,
2007; Schuler, De Cindio, & De Liddo, 2015).
In the Introduction, we presented a four-dimensional model of inclusive knowledge. We can
now add to this model a fifth, organizational dimension. If we think of organizational forms andpractices as existing on a continuum, then at the

Figure 4.2

Continua of Inclusive Knowledge
Outcome-focused

Process-focused

Institutionalized

Personal

SegregatedIntegrative

Standardized

Adaptive

HierarchicalCooperative80

CHAPTER IV

far left we would find strictly hierarchical structures under which members have rigid, narrowly
defined roles and tasks and all decision-making
processes flow from the top down. At the far right,
we would find organizations with completely flat
structures in which every member has equal opportunities for participation. Although the majority of current organizations occupy the middle toleft side of this continuum, a growing number oforganizations are experimenting with practices
on the right side of the continuum (Democracy at
Work Institute, 2018).

sive processes, maker communities as a whole are
beginning to redefine manufacturing for the 21st
century (Schmidt, 2017).
The desire for integrative approaches to grandsocietal challenges has led numerous universities
to explore transdisciplinary and trans-sectoral
COP over the past 15 years (National Academyof Science, 2004; Popowitz, 2018). In her 2008
paper, Klein identifies three main clusters of interdisciplinary and transdisciplinary discovery:(1) international networks of interdisciplinary research, (2) transdisciplinary team science, and (3)transdisciplinary, trans-sectoral problem-oriented
research with stakeholders in society. Realizing
cluster three is particularly challenging because of
its trans-sectoral nature, heterogeneity of practices, and expanded notion of expertise (e.g., expertise can arise from experience as well as formal
study). Traditional organizational structures in academia are almost orthogonal to these approaches.
Therefore, academia is adopting COPs as a pathway for jump starting much-needed trans-sectoral,transdisciplinary activity within higher education(Crow & Dabars, 2015; ESSENCE, 2016).

4.2 Communities of Integrative Learners as
Pilots for Learning Societies
Communities of Practice (COP) embrace characteristics that span the full breadth of the five dimensions of our knowledge representation, withemphasis on the right side of the continua. COPs
are social networks that develop a shared knowledge base and adopt a core practice or initiative(Barab et al., 2002; Wenger, 1998). Learning is
bi-directional between novices and experts, thus
promoting flat and diverse peer-to-peer relational
structures. Participatory learning leads to dynamic
concepts of the practices that facilitate further inclusion and adaptation. Collins (2006) argues that
COPs have historically existed in cultures where
apprenticeship was a key means of learning new
skills or competencies. Today, communities ofpractice exist both online and in traditional mediums. One type of COP that has gained a lot of
attention recently is the maker community. Maker
communities bring together practitioners from all
sectors of the knowledge economy in an effort toconnect age-old learning through crafts with someof the most cutting-edge fabrication and knowledge-sharing technologies. They are also definedby their emergent making practices rather thanthe homogeneous practices of a specialized cohort(Galaleldin & Anis, 2017). Through their inclu-

Over the past 50 years, transdisciplinarity has
tended to be seen as a pluralistic, process-focusedpractice that can synergize with and continuously
deconstruct (contextualize, decontextualize, andrecontextualize) the disconnected, domain-specific practices of academia (Derrida, 2004; Foucault, 1969; Nicolescu, 2002; Osborne, 2015).
Contextualizing specialized work within dynamic
multi-perspective discourse is seen as a promising avenue for collectively addressing complex
societal challenges (Darberllay, 2015). As early as 1972, Jantsch proposed a transdisciplinary
university that he conceptualized as a four-layer
hierarchy moving from the specific to the general(Jantsch, 1972). On the first two layers, learners
81CHAPTER IV

and researchers focus on domain-specific empirical and pragmatic knowledge. At the third layer
they turn to domain-general systems approaches, while at the fourth layer they consider societal purpose, meaning, and values. This multilayer
approach to knowledge integration acknowledges
the difficulty of connecting pluralistic societal discourse about life’s purpose and values directly todomain-specific discovery. It proposes a graduatedapproach to knowledge integration that is paralleled by a measured shift of focus from outcome toprocess and from concrete to abstract.

the organizational structure. With this in mind, we
believe that cooperative communities of learners
structured around transdisciplinary themes of societal impact that structurally engage all layers ofskills of the IPPD model are ideal for exploring therecommendations of this report.
An example of what we have in mind is the Beyond Boundaries initiative at Virginia Tech, whichdeveloped transdisciplinary themes as the fourthlayer of a hierarchical structure of knowledge discovery and dissemination (Bleizner, Grant, & Rikakis, 2016). The hierarchy progresses graduallyfrom the domain-specific to the domain-generaland from outcome-focused to process-focused.
Departments form the base layer followed by thecollege (layer two), the interdisciplinary team science (layer three), and transdisciplinary cross-sector discourse (layer four). The connectivity oftransdisciplinary themes with the disciplinary andinterdisciplinary structures of the university depends to a large extent on the participants (faculty,
students, community, and industry partners). These
participants move easily and continuously among
concerns of their disciplines, interdisciplinary
centers, and transdisciplinary societal purpose discourse. To emphasize the critical role of integrative

We know, however, that knowledge is both
personal and relational. Multilayered collective
intelligence requires learners to embody the different layers and be cognizant of the full complexity of societal problems and the need for collaborative solutions. In turn, learners must rely on
communities of trust that value and support integrative personal and professional development
across skill layers and differentiated contributions
to collaborative contexts. COPs have the potential
to facilitate this interconnectivity of multilayered
personal knowledge and multilayered relational
knowledge.
They provide a nexus for social learning where
highly abstract ideas (i.e., making as reflection),
domain-general ideas (i.e., design for additive
manufacturing), and highly specific processes(i.e., improving the filaments for metal 3D printing) can coexist and co-inform. By spanning multiple sectors of knowledge ecosystems, COPs gaina continuous flow of new and diverse perspectives
while also endowing members with new insights
and abilities, which they can then transfer to their
domain-specific and domain-general contexts aswell as other relational contexts (Wenger, 2000).
Therefore, mobility across skills layers and practices is central—both to the participants and toMultilayered collective
intelligence requires learners
to embody the different skill
layers and recognize the needfor collaborative solutions.
In turn, learners must rely on
communities of trust that value
integrative development andcollaboration.

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knowledge practitioners, multilayer COPs wereorganized around each transdisciplinary theme
and were tagged as talent “destination areas.”
Destination area COPs are envisioned as dynamic
social nexuses. They are deliberately designed not
to be independent units with buildings, directors,
or other organizational and bureaucratic structures
because this risks turning them into their own silos
or relics of the past that are hard to sunset once
new societal challenges have surfaced (Amelink &Nicewonger, 2019; Nicewonger & Amelink, 2019;
Popowitz, 2018). Transdisciplinary knowledge isembodied in the participants of the COPs, not in
an institutional unit, and engages all skill layers of
the IPPD model. The knowledge of the community and of individuals continuously adapts as new
perspectives emerge through pluralistic discourseand new members join the community. As newsocietal challenges emerge, these lifelong learners
can easily transfer their multilayered, transdisciplinary abilities to new contexts.

the process, this project provides a vehicle for thevoices of participants, who share stories and examples that touch on both the difficulties and misconceptions underlying these initiatives, as wellas the creative strategies that are emerging out of
this work. The work illustrates the importance ofhearing and reflecting on the experiences of people who are engaged in inter-/transdisciplinary activities and practices.
Besides universities, a number of other organizations (schools, businesses, and non-governmental organizations) have been exploring new
ways to engender cooperation with flatter decision-making, ongoing education, and reciprocal valuing of different types of knowledge andpractice. These examples, too, provide valuable
insights into developing inclusive learning societies. The much-studied Toyota Production System,
for example, incorporates a deep commitment toproblem-solving through continuous interchange,
communication, and experimentation among managers, production line technicians, engineers, andmany others. As Spear (2004) argues, the basic
Toyota philosophy is that “any operating system
can be improved if enough people at every level
are looking and experimenting closely enough.”
This practice allows employees to engage in continuous learning and sharing of information with
one another at all levels.

Although transdisciplinary COPs hold significant promise for advancing inclusive and integrative adaptive learning in higher education, the sustainability of these communities within traditional
academia remains a challenge (Popowitz, 2018).
The working groups that we will launch following this report will explore in depth the opportunities and challenges of transdisciplinary, adaptive
learning in academia. The groups will engage inquantitative and qualitative research informedby multiple sources and perspectives. One such
source will be an extensive ethnographic research
project being led by Todd Nicewonger that examines the sociocultural experiences of faculty involved in inter-/transdisciplinary initiatives in US
higher education. The project provides a criticallook at the issues these faculty and staff face as
they work on developing collaborations with colleagues from diverse disciplinary backgrounds. In

Many businesses are working to achieve participatory knowledge ecosystems through what
Rothschild and Whitt (1986) call demystification. This is the process by which “formerly exclusive, obscure, or esoteric bodies of knowledge
are simplified, explicated, and made available tothe membership at large” (p. 190). Such processes enable members to build a macro-picture of
their workplace, learning about an entire organization and the various tasks, facets, and functions
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CHAPTER IV

required to operate it. Wolff and Resnick (2012)
argue that building strong relationships among
different firms is a strategy to further increase
learning opportunities and sharing of knowledge
because it creates an ecosystem in which members
can learn from partners in other businesses andbuild connections for support and training acrossorganizations. A robust learning society can thus
emerge by connecting individual flat and dynamic
organizations into a knowledge network organizedaround a trans-sectoral practice or theme with potential for significant societal impact.

dragon invests heavily in education by, among otherthings, creating schools and training facilities that areopen to employees and non-employees alike (Heales
et al., 2017, p. 52). Many organizations around theworld have learned from Mondragon’s approach.
One example is the Evergreen Cooperative Initiative,
a network of employee-run businesses in Cleveland,Ohio, operating with a commitment to community
reinvestment and environmentally sustainable economic development in partnership with local institutions such as Case Western Reserve University andthe municipal government (Alperovitz, 2013).

The Mondragon Corporation in the Basque region of Spain is a well-known and successful example of a democratic business ecosystem. Founded in 1956, Mondragon is not a single business but
rather an interconnected complex of cooperatives
each producing different products and services
and each retaining the capacity to make its own
decisions. The majority of its 74,000 employees
have the right to vote on important business decisions and the corporation is known for its commitments to educational initiatives and community
development. Mondragon’s cooperatives operateaccording to the principle of “learning by doing,”
which is essentially the educational idea that people can learn to do something through practice andreflection—as long as they have access to resources, support, and training. It is also about “having
confidence in people that they can have successusing their labour through trial and innovation”(Heales et al., 2017, p. 31).

4.3 Point of Need Learning Platforms
Learning communities, either in education
or industry, that embrace flatter, participatory organizational structures provide ideal relational
contexts in which to explore the integrative andadaptive lifelong learning practices and recommendations of this report. We propose that Pointof Need Learning Platforms (PNLP) can connect
smaller participatory knowledge projects intolarge scale inclusive and adaptive learning networks. Indeed, based on all the work presented inthis report thus far, we argue that the key value
these platforms bring to the table is participation.
A successful PNLP can facilitate participation foranyone interested regardless of background or previous experience.
PNLPs can be developed by adopting, experimenting with, and evolving many of the recommendations of this report. We propose that PNLPs becreated and continuously developed by cross-sector communities of integrative learners spanning
K–12, higher education, industry, and community
organizations. Each PNLP can be structured arounda transdisciplinary, trans-sectoral collective intelligence theme such as the world economic forum
definition of Industry 4.0 that places technologicaland economic development within a systems con-Mondragon’s yearly revenues of €12 billion (approximately $13.2 billion), combined with its democratic organization, has enabled the corporation to accumulate sufficient capital to develop what has beencalled a “social innovation eco-system,” which includes a university, medical services, and other community supports (Heales et al., 2017, p. 45). Mon84

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to current and emerging training and employment pathways. PNLPs are continuously updated
through broad, cross-sector participation supported by high-dimensional workforce and learning
analytics. For example, if two very distinct activities—such as working at a motorbike shop andtaking an online math course—have repeatedly
been shown to assist learners in developing particular skills related to Industry 4.0, both experiences can be included as part of a PNLP on Industry
4.0 along with adaptive pathways that can maturethese skills and connect them to industry 4.0 competencies. The connection of these experiences
within a PNLP may also inform the redesign ofthe math course and the workflow in the bike shop.
PNLPs organize content in modules and provide
flexible connectivity between modules. Modules
utilize and combine different learning modalities
ranging from in-person, hands-on experiences to
distributed, asynchronous learning and team-based
explorations of complex problems. Learning is enhanced by using cutting-edge technologies such as
interactive content applications, cognitive tutors,
augmented reality, and robots. The use of these enabling technologies facilitates the development ofdescriptive and predictive analytics to help inform
mentoring and advising.

Point of Need Learning Platforms
are cyber-physical platforms
dynamically structured aroundtransdisciplinary and transsectoral themes of societal
impact. PNLPs contain modular
content developed by allparticipating sectors and allow
any learner to map their existingskills to current and emerging
training and employment
pathways.
text that also engages the support of the five Ps:
people, peace, planet, prosperity, and partnership.
As discussed in Section 4.2, these themes require
diverse perspectives and necessitate concurrent
application and development of interconnecteddomain-specific, domain-general, and life skillsby all participants. Because every active learnerhas domain-general and life skills, these skills canbecome their entry point into any transdisciplinary
PNLP. Some learners may start their participation
at the edge of a transdisciplinary theme and its corresponding PNLP. But as is the case with traditional
COPs, increased participation will assist each learner with interconnected development of customized
networks of life, domain-general, and domain-specific skills that can lead the learner to the core of thecommunity.

A PNLP promotes learner agency and mobility within and across personal knowledge layers(domain-specific, domain-general, life skills, andrelatedness), knowledge types (explicit, implicit,
and tacit), and learning domains (cognitive, affective, and psychomotor). PNLPs are thus well
positioned to accommodate and connect different
learning experiences with the needs of all typesof learners, including K–12, higher education, thecurrent workforce, those who are reskilling, andthose rejoining the workforce. By recognizing andleveraging the existing diverse skills of learners,
drawing resources (educators and trainers, learn-

PNLPs embrace all the structural characteristics of IPPD-based adaptive learning platforms
that are presented in Chapter II (Section 2.4). They
are cyber-physical/cyber-human platforms that allow diverse learners to map their existing skills
85CHAPTER IV

ers and learning content, labs and facilities) fromacross sectors, and connecting learners to accessible learning contexts (e.g., a partner facility
close to their home) the PNLP can minimize costto the learner. PNLPs reduce the need for lengthy
full-time residential learning and the need for thecreation of large, standalone, and expensive infrastructures of residential learning, which in certain
cases might also be duplicative if, for instance,
two higher education institutions in the same state
are developing similar expensive labs that end up
competing with each other. As an adaptive platform, the PNLP integrates multiple on-and-off
ramps and diverse forms of credentialing including individualized electronic learning records
owned and managed by the learner. We proposethat universal, free-at-the-point-of-use PNLPs
represent an adaptive, inclusive, efficient, and feasible approach to meeting the needs of a vast arrayof learners.

not a traditional online learning platform although
it can synergize with existing distributed learning platforms such as Coursera or EdX. A PNLP
places each module of learning in the context of
IPPD that can support collective intelligence foraddressing complex and current societal themes.
For example, a learner may engage calculus orprogramming in an Industry 4.0 focused PNLP,
but that domain-specific learning would be connected to domain-general skills (e.g., computational thinking) and life skills (e.g., collaboration)that help integrate specific knowledge into complex problem solving for Industry 4.0. In this case,
the PNLP helps develop an integrative learner who
can do computer science; it does not credential acomputer scientist. Furthermore, a PNLP recognizes and leverages all types of knowledge inaction (i.e., knowledge acquired through formal
training and life experiences) and combines allmodes of learning (e.g., hands-on apprenticeships
in facilities of partners, online modules with peer
mentoring, and team-based projects embedded insociety).

The business model for a PNLP is based on
extensive participation resulting from widespreaddemand. Entities and individuals from different
sectors join a PNLP because they want to be amember of a community that can tackle a transdisciplinary theme of societal impact by addressing the totality of the problem space (technical,
financial, societal, environmental, etc.). All participants realize that the continuous and multilayered integrative learning necessary for tackling
the theme requires broad participation across all
societal sectors. The largest contribution that individual participants bring is their knowledge andactive engagement. This model presupposes that
resource-rich entities will be open to subsidize
the participation of resource-constrained entities
because they value integrative learning throughcomprehensive participation.

The ARM initiative mentioned in Chapter III
may be an ideal context for establishing a PNLP
that connects many communities from different
sectors, all of which are engaged in robotics for
manufacturing research and training. As discussed
in the Resource section, the Calhoun Center is facilitating the creation of a cross-sector COP thataims to gradually develop a PNLP on Industry
4.0 for Sustainable Development. An ARM or Industry 4.0 PNLP could connect small exploratorycommunities within existing organizations into alarge trans-sectoral community that practices inclusive adaptive lifelong learning. As we discussin the next section, the resulting large community
can produce transformative knowledge paradigms
within the community itself and help graduallyshift some of the existing knowledge practices

It is also important to highlight that a PNLP is86

CHAPTER IV

of affiliated organizations towards more adaptive
and inclusive approaches. This combination of
disruptive and gradual change has the potential tosupport the emergence of an inclusive knowledge
economy.

2020). Our educational institutions are optimized
for a subset of learners and learning practices but
are not nearly dynamic enough to adapt to newlearning modes and expansive learning needs. The
learning societies and inclusive knowledge economy that this report is exploring would situate us tomore effectively mitigate and address these complex challenges.

4.4 Predictive Modeling of Practices Within an
Inclusive Knowledge Economy
Throughout this report, we have contrasted
the knowledge practices of the 20th century withthose that are demanded of us in the 21st century.
We have argued that the majority of institutionalized knowledge practices of the 20th century canbe found on the left side of our five-dimensional knowledge continuum (Rikakis et al., 2019).
Based on the notion that knowledge should bestandardized, outcome-focused, and disseminatedvia siloes, these practices have been safeguarded through strong gate-keeping mechanisms anddominant bureaucracies. The growth of interdisciplinarity over the past 50 years (Knight, 2013;
Sa, 2008; Sciences, 2005), as well as the more
recent expansion of adaptive and inclusive practices highlighted in this report have fostered a
gradual shift to the right. Still, this gradual shift
has been slow in producing the scope of change
necessary for developing an inclusive 21st century knowledge economy. Many employment needs(Hart, 2016), knowledge needs (Donovan, 2015;
Madrigal, 2017), and socioeconomic sustainability needs (Carayannis, 2019) remain unaddressed.
The 2020 COVID-19 pandemic is a recent example of the need to address interconnected issuesof health, socioeconomic and racial inequalities,
and exclusion from the learning and knowledge
enterprise. Established knowledge practices areproducing significant advances that are life-saving
and unimaginable even 25 years ago. However,the focus on segregated specialization has limited
our capacity to adopt integrative system approaches to complex socioeconomic problems (Basken,

As we have shown in this report, the best way
to engage successfully with the complexity of 21st
century socioeconomic problems is to first acknowledge and then cultivate the strong relationship between adaptive and integrative development of lifelong learners and pluralistic relational
contexts. At the same time, we have argued that
small pluralistic communities of adaptive learners
within otherwise traditional institutions may nothave the necessary synergies to succeed and scale
their activity. The fact is that adaptive and integrative learning practices do not synergize wellwith the dominant markers of the previous century—e.g., national rankings that promote exclusion as a sign of success, standardized testing thatrewards homogeneity of perspectives, and hiring
practices that focus primarily on knowledge as a
product and individual achievement (Crow & Dabars, 2020). Because the majority of institutionsof learning continue to focus on practices on theleft side of our five-dimensional representation, asingle institution or single learning/training unit
within an institution that attempts to shift its practices decidedly to the right may find itself excluded from the national learning establishment, andits members may find their career mobility significantly reduced (Adler, 2015).
In their recent book, Crow and Dabars (2020)
suggest that one solution to this problem is forlike-minded institutions to come together and form
alliances so that they can advance inclusive, in87

CHAPTER IV

tegrative and dynamic learning practices at scale.
This is certainly an intriguing idea, but it may beunrealistic to ask the majority of well-establishedprofessionals in current knowledge institutions toincorporate the adaptive learning recommendations of this report. In many cases, their personal
knowledge models are likely far away from themodels proposed in the report. Furthermore, there
is significant evidence to suggest that building exploratory transdisciplinary communities for adaptive learning on the foundation of institutionalized,
outcome-based, and siloed knowledge leads tothese communities failing or gradually morphing
into more traditional approaches and siloed practices (Popowitz, 2018; Samuels, 2015).

transdisciplinary). Traditional polarities (i.e., local
vs. global or adaptive vs. standardized) will coexist within these practitioners as synergistic pointsof view (Chaterjee, 2019). These “impartially-partial” knowledge practitioners (Chatterjee, 2019;
Oxford Consortium, 2019) will personify the philosophical concept of The View from Nowhere (Nagel, 1986). They will be partial (i.e., passionate)
about their experiences and points of view but also
impartial in that they are aware of the wide spectrum of possible experiences, the limitations ofindividual points of view, and the richness that results from the interaction of different experiences.
The acceptance of multiple realities by members of knowledge ecosystems (Nicolescu, 2002)
can in turn advance multi-perspective reflective
practice (Darbellay, 2015; Osborne, 2015). When
integral combinations of common and differentiated features are embodied by individual members
and communities of knowledge, high network den-Rather than building entirely new exploratorycommunities from scratch, we propose identifying individuals and communities within existingknowledge and employment institutions who are
already practicing adaptive learning within pluralistic relational contexts and find ways to connect
those individuals and groups with large networksof adaptive learning outside of their institutions.
The key to facilitating such connections is PNLPs,
which have the potential to greatly increase theimpact for these alliances, thus increasing theirpotential for committed participation and success.

Our model for predicting
institutional change allows
for informed discourse
between a radical paradigm
shift and the gradual change
processes embedded inexisting institutions. Combining
emerging and current
practices can lead to balanced
distributions of practices thatspan the full range of the fivedimensions of our inclusive
knowledge representation.

Combining emerging practices from networks of adaptive learning with current practices
from traditional learning units will lead to morebalanced distributions of practices that span thefull range of the five dimensions of our inclusive knowledge representation. The availabilityof an expanded palette of practices will encourage knowledge-practitioner mobility by enablinglearners to explore the different available practices and combinations. Mobile knowledge practitioners will gradually embody multiple perspectives (i.e., disciplinary, interdisciplinary, and88CHAPTER IV

sity across both homogeneous and heterogeneous
practices can emerge, leading to the transformation of existing knowledge organization and socioeconomic outcomes (Eagle, Macy, & Claxton,
2010; Grabher & Stark, 1997; Reagans & Zuckerman, 2001; Tegarden et al., 2009). Diversity inideas and practices will increase individual andteam creativity and help teams avoid getting stuck
on local maxima (Page, 2007). This pluralistic
discourse can then gradually establish at scale thenotions of inclusive knowledge discussed in our
introduction, thereby setting the stage for adaptive
lifelong learning at scale.

lectical bootstrapping (Herzog & Hertwig, 2009).
These individuals will have a heightened awareness of the relation of their individual knowledge
to the full scope of societal knowledge. They will
also be able to engage different viewpoints, which
will enable them to improve their personal knowledge continuously. The collective decision making of these individuals then becomes the base of
an updated “wisdom of crowds” model that is notbiased toward “shallow, lowest common denominator information, at the expense of novel or specialized knowledge” (Prelec, Seung, & McCoy,2017).

How should we think about this expansion ofknowledge production and dissemination acrossthe five dimensions of inclusive knowledge? One
possible approach is to model the expansion process as a one-dimensional random walk alongeach knowledge dimension the outcomes of which
are binomial at any step. The outcomes of a large
number of such steps can, under fairly general conditions, be shown to be approximately Gaussian asa result of the Central Limit Theorem (Gnedenko& Kolmogorov, 1954; Hermans & Lentz, 2013).
Although one can expect the knowledge features
used on each dimension to span a broad scope,
the overall distribution of feature usage, acrossall participating learners over time, will behave
in a manner consistent with a normal distribution,with a larger number of experienced features accumulating near the center. Figure 4.3 represents
the normal distribution outcome of this modelingprocess over each of the five dimensions.

A more intuitive way to understand the “random walk” and “wisdom of crowds” models ofknowledge expansion is to think of it in terms ofpeople making “satisficing” decisions in complexity (Simon, 1957). “Satisficing,” a combination of“satisfying” and “sufficing,” is an idea that dates
back to Ancient Greek philosophy. In short, theidea is that when people are facing problems, thesolutions to which span a large continuum, adopting solutions near the middle of the continuum isa great starting point for addressing the majorityof needs (Plato & Richards, 1966). Then, by taking gradual steps to the left and right of center,good solutions can be found for most problems(Dewey 1906, 1933). For example, various combinations of standardized and adaptive learning
pathways can produce quality control and accessat scale across many different types of learners.
As discussed in Chapter I, an experienced craftsperson and a college graduate may vary considerably in their personal knowledge when they need
to use derivatives for optimization. A PNLP thatbalances participatory process with outcome will
have pathways that, on the one hand, allow thecraftsperson to gradually translate tacit knowledgeof optimization into understanding of the notionof derivatives and, on the other, allow the college

Moreover, the expansion can also be modeled
as probabilistic decision making in uncertainty
through a “many in one” approach. This approachis based on the assumption that, by and large, learning societies of the 21st century will be serving an
inclusive citizenry capable of a high level of dia89

CHAPTER IV

Figure 4.3

21st Century Inclusive Knowledge Representation

Outcome-focused

Process-focused

Institutionalized

Personal

SegregatedIntegrative

Standardized

Adaptive

HierarchicalCooperative

graduate to translate symbol-based expertise inderivatives to real-world optimization problems.
By including both types of learners into the samecommunity, we provide opportunities for both toexchange perspectives and learn from each other.
The analytics and pathways of the PNLP serving
this community are further enriched through theparticipation and interaction of these learners leading to expanded inclusion capacity of the community. The normal distributions with high standard
deviation described in this section are not the result of uninformed compromise where different
biases cancel each other out. They are the resultof continuously improving societal wisdom thatemerges through multi-perspective reflective discourse supported by inclusive adaptive learningthat aims for IPPD.

for institutions to abandon a one-size-fits-all mentality when imagining their internal organization.
For example, universities can promote the coexistence of traditional disciplinary departments withinterdisciplinary centers and cross-sector transdisciplinary communities of practice. Each paradigm will come with its own customized learning, discovery, personnel, budget, and assessment
structures. Although such disruption may increase
entropy within organizations momentarily, ourmodel proposes that over time these separate paradigms will fuse into one coherent, expansive, anddynamic paradigm.
In short, what we are describing in this report
is not a new model that replaces existing institutions. We see networks of adaptive learning as amodel that can thrive alongside existing institutions and attract collaborators throughout society.
We propose that distributed networks of integrative learners should be based on practitioners who
embody or aspire to the pluralistic knowledge inaction principles of this report. Such practitioners
exist already within our institutions and are looking for opportunities to advance adaptive andintegrative learning within a different epistemo-

Our model for predicting institutional change
allows for informed discourse between a radical
paradigm shift (distributed networks of diverse
integrative learners supported by PNLPs) andthe gradual change processes embedded in existing institutions. By institutional change, we mean
both change within organizations and change inthe wider realm of societal knowledge. This calls
90CHAPTER IV

logical context. We see increased demand among
young people for a more inclusive and sustainableknowledge economy. We have a unique opportunity to scale the training of adaptive learners and,in the process, mature adaptive learning mechanisms. Advancement of adaptive lifelong learningat scale can provide a disruptive paradigm that
promotes a calibration of knowledge practices toward an inclusive, collaborative, and sustainableknowledge economy.

91Working Groups

WORKING GROUPSWORKING GROUPS

I

Proposed working groups include:n August 2020, we will be launching a series of working groups with learners, educators, and professionals across sectors(K–12, Higher Education, Industry, etc.). Organized around specific themes, these groups will
explore, critique, and evolve the recommendations of this report. We envision working groups
as opportunities for participatory assessment of
the report as well as bridges to form partnerships
for actionable items such as grant-funded pilot
programs and new education modules, tools, andplatforms. Although working groups will begin
virtually, we anticipate the possibility of holding
in-person workshops in the spring of 2021. The
insights gained from these events will be analyzed
and incorporated into a digital book on Inclusive
and Integrative Point of Need Learning to be published by Virginia Tech Publishing in the second
half of 2021. At that time we will also start theimplementation of a Point of Need Learning Platform for Inclusive and Sustainable Industry 4.0

1. From School, to Manufacturing Employment, to Lifelong Learning (with a focus on
pathways in advanced manufacturing)
Coordinator: Amy Arnold
Current Participants: Dave Hare, Kristin
Wingfeld, Chip Blankenship, Robert Smith,
Lisa McNair
This working group will leverage knowledge from a number of initiatives mentioned
in Chapter III to (i) bring together people andentities that have successful experiences inthese types of learning pathways, (ii) leverageongoing work in places like the Academies ofLouisville and FAME for developing adaptive pathways in high school curricula thatcan lead directly to successful employment
in advanced manufacturing for learners fromvarious backgrounds, and (iii) begin to define
a point-of-need approach for lifelong learningin advanced manufacturing that can provide
upskilling and career development opportunities to all levels of workers. This group willsynergize with the Future Talent Council Advisor Boards on the Future of Talent in Manu-

Participation in working groups is open
through application. The participant lists given
below are therefore continuously updated. If you
are interested in participating, please contact the
Calhoun Center at cchei@vt.edu
93WORKING GROUPS

facturing and Employer & Educator Relationships.

This working group will bring together
people and entities that have successful experiences in implementing adaptive and integrative learning in K–12 with a focus onunderserved areas. The goal is to make recommendations and build partnerships for scaling
this work. The group is also planning a workshop on collaborative self-discovery exercisesthat can expose young learners to an adaptive
learning framework, help them discover theirstrengths, and allow them to have some ownership of the adaptive learning process by connecting these strengths to future aspirations
through customized pathways. This working
group will bring together two focus groups of
50 10th grade students from Newport News,
Virginia and Lynchburg, Virginia.

2. Adaptive and Integrative Learning in Global Academia—the International Academic
Forum (IAFOR), the Association of Public andLand-grant Universities (APLU), and the Future Talent Council (FTC)
Coordinators: Joseph Haldane, Shari Garmise,John Flato, Jared Keyel
Current Participants: Daniel Kjellsson, Paul
Heilker, Dale Whitaker, Juliet Greenwood,
Rebecca Clark-Stallkamp, Marianna Savoca,
Peter Sforza
This working group will engage a diverse
group of educators and scholars from aroundthe world with a focus on the IAFOR, APLU
and FTC networks. The group will gather
emerging practices in developing adaptive andintegrative professional and personal development (IPPD) curricula across the globe andform partnerships for the exchange of lessons
learned and/or coordination of efforts acrossinstitutions. The group will also look into faculty and staff development issues as well as
technology development issues for delivering
adaptive lifelong learning. The group will focus on the enabling technologies discussed in
Chapter III and the combinations of gradualand transformative change discussed in Chapters III and IV.

4. Cross-Sector Summit on Adaptive Learning
for an Inclusive Workforce at the Intersection of Humans and Technology
Coordinators: Renee Schlechta, Michael Richey,
Jay Chance, Shahab Sagheb, Amy Arnold,
Catherine Amelink
Participants: By invitation
In manufacturing and engineering industries, several key technologies are impacting
the workforce’s knowledge development.
These include robotics and automation; industrial Internet of Things and advanced sensing;digital twins (corresponding data packages
for each design and part); cyber security for
production systems; augmented and virtual
reality, e.g., for inspection tasks; and additive
manufacturing technologies; among others.
Taken in total, these technologies are posed totransform manufacturing capabilities, enabling
greater operational flexibility (in the form ofreconfigurable production assets), strategic

3. Adaptive and Integrative K–12 Preparationin Underserved Areas—Trusting the Young
Learner
Coordinators: Owen Cardwell, Chrystal Harris,
Chris Glover, Scott Bess, Karen Eley Sanders,
Amy Arnold
Current participants: To be determined
94

WORKING GROUPS

flexibility (in the form of granular, data-driven
business intelligence), and advanced knowledge management (in the form of knowledge
graphs and data lakes).

Jared Keyel, Thanassis Rikakis, Shahabedin
Sagheb, Mike Kretser, Alkan Soysal, Robert
Smith, James Ivory, Chip Blankenship, Joan
Banks-Hunt

The development and implementation ofthese technologies within a systems context ofthe five Ps (People, Peace, Planet, Prosperity
and Partnership) can facilitate much neededsocioeconomic sustainability. This summit
will focus on the structuring of partnershipsthat can coordinate the commitment of significant resources towards sociotechnical systems
approaches that increase manufacturing capability and flexibility while also advancing inclusive and equitable growth of human capital.
The summit will bring together experts fromindustry, academia, government, and community to explore training and production systems that leverage cyber-human intelligence totackle these complex goals. The summit will
also explore the potential of cross-sector Pointof Need Learning Platforms (PNLP), as presented in this report, for educating, reskilling,
and upskilling all related members of the current and future workforce to utilize and leverage these technologies. Since PNLPs advancetargeted domain-specific skills while also leveraging and advancing diverse domain-generaland life skills, they can become a key mechanism for inclusively enhancing the professional and personal development of human capitaland driving the five Ps of Sustainable Development Goals. The summit will be hosted at
the Boeing Leadership Center in St. Louis,
Missouri.

This working group will focus on a threeyear assessment of the Calhoun Discovery
Program (CDP) as a pilot for an IPPD-based
adaptive learning curriculum within existing
structures in higher education.
6. An Inclusive Workforce Development Workshop with Virginia Mayors—Focus on Industry 4.0
Coordinators: Anne Khademian, Scott Weimer,
Jared Keyel
Current participants: To be determined
The overarching goal of this working
group is to ask mayors across cities of varied
sizes and demographics to identify (i) current
skills, built through both formal training andlife experiences, that exist in their community; (ii) current and future skills needed in theircommunity; and (iii) training mechanisms(including learning mechanisms and support
structures) that can leverage existing skills to
train an inclusive workforce for the future in
their city. The working group will focus on
mapping diverse “knowledge-in-action” skills
that exist in current cities to an inclusive Industry 4.0 workforce.
7. Institutional Partnerships with Local Employers in Rural Settings
Coordinator: Catherine Amelink

5. Integrating IPPD Adaptive Learning in
Current Higher Education Structures—
Calhoun Discovery Program

Contributor: United Way of Southwest
Virginia

Coordinators: Lisa McNair, Amy Arnold,

Current participants: To be determined
95

WORKING GROUPS

Starting in the summer of 2020, this working group will explore how student internships
with local employers in a rural setting coupledwith project-based classroom work provided
by local employers can help to provide opportunities for adaptive learning and help to further expand this model to other communities
and learning contexts such as community colleges.

This working group will leverage work in
all other working groups to draft a model of a
PNLP that can advance an inclusive approach
to workforce training and overall sustainable
development for Industry 4.0. The group willaddress:

8. Transdisciplinary Relational Knowledge forIntegrative Development and Revaluing the
Humanities and Arts•

A systems approach that advances pointof-need learning that places technology
development within the five Sustainable
Development Goals of Industry 4.0.

•

Dynamic cross-sector workforce analytics
that explore domain specific, domain general, and life skills involved in competencies for Industry 4.0 and Sustainable Development.

•

Cross-sector development of modular,
just-in-time training content that leverages
knowledge mapping of existing integrativeskills of all types of learners to emerging
Industry 4.0 needs.

•

An Industry 4.0 credentialing system thatis owned by the learner and tracks and details all Industry 4.0 related experiences
and knowledge of each learner from various activities in work, education, and community interaction.

•

Technologies and computational tools forsupporting a PNLP for Industry 4.0 witha focus on Industry 4.0 enabling technologies as discussed in Chapter III.

•

Cross-sector collaborations to reduce costand increase access.

•Applications of Industry 4.0 PNLP to smart
construction or construction 4.0.

Coordinators: Sylvester Johnson, Ico Bukvic,
Catherine Amelink, Thanassis Rikakis, Roger
Reynolds
Current participants: To be determined
This working group will explore structured
trans-sector, transdisciplinary discourse as arelational context for advancing inclusive definitions of knowledge and promoting adaptive
and integrative learning. The working groupwill also explore how transdisciplinarity as arelational context for IPPD can bring forward
and revalue humanities and arts as appliedlearning experiences that develop critical domain-general and life skills in tandem with inclusive collective intelligence.
9. Towards a Point of Need Platform for Inclusive and Sustainable Industry 4.0
Coordinators: Thanassis Rikakis, Sylvester
Johnston, Jenna Joo, Randy Swearer, Robert
Smith, Mike Kretser, Anne Khademian, Kim
Carslon, David Tegarden, Michael Richey,
Chip Blankenship, Andrew McCoy, Mukul
Kumar, Ronan Mac Domhnaill, Tazio Grivetti,
David Tinnaple, Jared Keyel, Amy Arnold
Current participants: To be determined
96Appendix A:
The Calhoun Discovery Program A Pilot IPPD curriculum

APPENDIX A

APPENDIX A

The Calhoun Discovery Program—A Pilot IPPD
Curriculum
Author: Thanassis Rikakis
Co-authors: Lisa McNair, Shahabedin Sagheb, Alkan Soysal, Mike Kretser, Robert Smith,
Neal Henshaw
Contributors: Michelle Kovac, Paul Knox, Paul Heilker, Tom Martin, Akshay Sharma, Lara
Khansa, Mark Embree, Sylvester Johnson, James Ivory, Anne-Lise Velez, Nikki Lewis, Luke
Lester, Chip Blankenship, John Tracy, Amy Arnold, Les Duffeld, Howard HainesT

he Calhoun Discovery Program (CDP)
is set up as a pilot for embedding an
Integrative Professional and Personal
Development (IPPD) curriculum, as outlined inthis report, within existing institutional structures
at Virginia Tech. The goal of the program is to help
prepare integrative, lifelong learners who:•

Inclusive social learning that includes a highly
structured collective intelligence component,•

Learning experiences that connect domain-specific skills to domain-general skills,•

Learning experiences that connect domain-general skills to life skills,•

Can move easily across knowledge domains
and pick up diverse new skills in a just-in-time
approach,•

Coordination of learning across experiences
so as to facilitate integration of different skills
within the learner, and•Can connect their specialized knowledge tocomplex collaborative contexts for problem
setting and problem solving,•A co-creation approach, between instructors,
partners, and students, spanning all of the CDP
learning experiences.

•

Use complex relational and collaborative contexts for self-discovery and personal fulfillment, and•Connect personal fulfillment to advancing anequitable and sustainable society.

CDP instructors aim to develop a student’s
self-authorship for the purpose of carrying independence in tandem with collective awarenessover a lifetime of learning, while also developing
the complex networks of skills necessary for integrative professional and personal development
within diverse relational contexts (Baxter Magolda, 1999). Using the strategies outlined earlier inthe report can aid students in finding their voices,
engaging in content more meaningfully, and realizing they may always adapt transferable skills

The CDP helps learners develop these competencies through integrative development of
domain- specific, domain-general, and life skills.
The connectivity and integration of these skills aresupported by:98

APPENDIX A

to new settings. The curriculum asks the instructor to meet the students where they are, regardless of what development stage they may be exhibiting (Kegan, 1994), by welcoming them andasking for their input. As mentioned in Chapter
II, we recommend validating the students (Baxter
Magolda, 1999) by acknowledging what they already have in their repertoire and respecting theirdiverse ways of knowing (Chickering & Reisser,1993). This is done in addition to lessening what
Moore (1993) describes as transactional distance,“the psychological and communication space between the teacher and learner” (p. 22). Secondly,
CDP course design values the learners’ experience (Baxter Magolda, 1999; Brown, Collins, &Duguid, 1989). This is done by connecting thelearning to students’ life experiences or situatinga problem in a real-life context, as well as providing alternative options for students to advance.
Including students’ experiences in the learning
environment aids in their ability to connect new
information and engage in interdependent learning(Baxter Magolda, 1999). Lastly, all voices, including student-to-student and student-to-instructor,
collaborate to construct shared meaning (Baxter
Magolda, 1999). Students participate more when
the instructor engages in dialogue rather than lecture (Shor & Freire, 1987). A related strategy that
fosters a co-creation paradigm is for the instructor
to take on the role of ‘guide on the side’ by physically moving to the students’ location and guiding
the discussion rather than giving away all knowledge (Baxter Magolda, 1999). These strategies aredevised to enable students to realize that they playa necessary role in knowledge creation.

inclusive relational context, the CDP aims to attract learners with many different life experiences
as well as instructors from academia and industry with different areas of specialization. Thanks
to significant industry and philanthropic support,
all CDP students receive tuition scholarships andadditional grants for experiential learning. Admission to the CDP is based on a holistic review of
GPA, learning skills exams, essays, portfolios ofwork, as well as interviews that explore the interests of the students in adaptive and collaborative
learning. In the first two years, this approach has
produced gender-balanced cohorts with 25% of
the students being from underserved and/or underrepresented backgrounds.
The CDP invited ten programs at the university to engage based on their expressed interestin combining disciplinary learning with collaborative experiential learning that spans professional and personal development. Students applying
to the CDP choose paths in business information
technology, business management, computationalmodeling and data analytics, electrical and computer engineering, industrial design, industrial andsystems engineering, communication, environmental policy and planning, smart and sustainable
cities, and creative technologies.
Additionally, the CDP invited institutional
partners from industry and the non-profit sectors.
Qualifiers for engagement include (a) interest in
supporting an integrated approach to personal andprofessional development of students; (b) commitment to an inclusive workforce; and (c) willingness to embed experts from their companies
into the program as visiting faculty. In the firstyear, Boeing, General Electric, Caterpillar, andthe non-profit Share Charlotte participated. Morenon-profit and industry partners will be added in
the future.

As proposed in this report, inclusive, collective learning can help develop life skills (communication, collaboration, versatility, complex thinking, and creativity) that are critical for success inthe 21st century knowledge economy. To realize an99

APPENDIX A

Recruiting this diverse set of students and institutional partners was critical for the CDP to achieve
an inclusive social learning environment. The next
step was to establish an inclusive transdisciplinary
theme for the CDP that would facilitate the structuring of collective intelligence among the diverse
participants. The selected theme needed to achieve
four goals in parallel:

systems approaches (Miller, 2010). The CDP aims
to build on this work while adding the componentof sustainability (socioeconomic and environmental), thus emphasizing the societal impact of the
program.
We refer to the four components of the CDP
systems approach to collaborative sociotechnicalinnovation as sets. From an industry perspective,
the four sets can represent the following simplified elements of a solution concept for a problem
space: (1) desirability aligns with a definable realneed from a use case; (2) feasibility aligns with atechnical approach that exists and has some maturity; (3) viability aligns with how the technical approach can be manufactured reliably and repeatedly, is testable, and can be accomplished for a costthat is reasonable to the desirability constraint;,and (4) sustainability aligns with a solution concept that embraces societal benefits such as being
eco-friendly, policy compliant, regulation compliant, life-cycle cost supportable, and promotes
inclusive economic prosperity. As shown in Figure A1, some elements of these four sets overlap.
Systems approaches to sustainable sociotechnicalsolutions need to address the interrelations and interdependencies among all the key elements of thefour sets through extensive collaboration of people with different experiences and knowledge.

1. Engage the specific interests and abilities of allacademic and industry participants regardlessof disciplinary background or industry specialization;
2. Promote integrative development of domain-specific, domain-general, and life skillsby the participants so as to allow them to tackle collaborative work within the theme;
3. Enable educators to employ a systems approach to collaborative sociotechnical innovation that could facilitate the connection ofdifferent individual knowledge to collective
intelligence;
4. Engage a sociotechnical area of current importance so as to leverage the strengths and fulfill
the mission of Virginia Tech as a land-grant
institution.
As we began to structure a collaborative sociotechnical innovation theme for the program, it
was important to consider the significant body ofresearch over the past 15 years in engineering systems/design thinking approaches to collaborativetechnology innovation. The goal of the researchis to systematize an integrative approach to collaborative innovation that addresses the technicalcomponents (feasibility) along with the business(viability) and design (desirability) components(De Weck et al., 2011; IDEO, n.d.). A further goal
is to structure learning methodologies that train
experts who can work in teams to implement these

The CDP chose to focus on the sociotechnicalinnovation theme of Industry 4.0 for Sustainable
Development. The theme meets the goals of the
CDP and interests of the participants while being well suited to the systems approach describedabove. Industry 4.0 is defined by five core technologies that have evolved into 13 enabling technologies (Habib & Chissom, 2019), which aresupporting five Sustainable Development Goals(SDG) for the year 2030 (Schwab, 2016). The
SDG outcomes require that technical development
100

APPENDIX A

Figure A1

Integrating the Four Sets for Sociotechnical Innovation with the Participation ofStudents from 10 Different Programsof the enabling technologies be placed in a systems context of the five Ps: People, Peace, Planet,
Prosperity and Partnership. The World Economic
Forum’s definition of Industry 4.0 elaborates further on the SDG goals by focusing on the productive coexistence of human and machines: Smartfactories that take advantage of the Internet ofThings while also advancing inclusive and equitable growth of human capital (Schwab, 2016).
Implementation of such systems approaches to atechnology-enabled, sustainable society requires
the valuing of the technical, social, methodological, and personal competencies of the Fraunhofer
Report model discussed in Chapter I (Hecklau
et al., 2016). The complexity and dimensionalityof the SDG requires that lifelong IPPD learners
come together to generate collective intelligenceand leverage that collective intelligence for further
integrative development. Within the CDP systems
model, exploration of the Industry 4.0 for Sustainable Development theme requires each individual
participant to embody domain-specific proficiency
along with domain-general knowledge across thefour sets and mature life skills. This allows all participants to (1) have an integrative understandingof the problem space and (2) collaborate successfully with people that have significant expertise indifferent domain-specific elements of the four sets.
The CDP has chosen to concentrate on six
components of the Industry 4.0 for Sustainable
101

APPENDIX A

Development theme based on the particular interests of our faculty and partners. Around each component, we are developing a work cell: a hands-on
lab in the university that hosts student, faculty, andpartner activity that spans the four sets of the systems approach. The first four work cells focus on
the maturation of a key enabling technology at theworker/machine interface:planet through the use of enabling technologies,
and bring prosperity to individuals throughout theecosystem in an equitable and inclusive manner.
With this in mind, we developed two more work
cells that relate to all four enabling technologies:

1. Cyber Physical Systems-Smart Factory, Focus: Human Augmentation

6. Inclusive Human Capital Development

5. Digital Thread and Supply Chain Synchronization

A more detailed presentation of our systems
approach to Industry 4.0 for Sustainable Development is provided in the Resources section.

2. Design for Advanced Manufacturing
3. Factory and Equipment Upgrade and Retrofitting

A significant part of the learning process in
the CDP throughout each year of study is realized
through collaborative, hands-on projects connectedto the work cells. Students are thus guaranteed real-world problems and real-world data as well as
expert multidisciplinary, multi-sector supervision
for their projects. All student projects embrace asystems approach and are realized by student teams
with expertise that spans the four sets. Projects areoffered at the concept, prototype, and applied levelwith multiple possible pathways between the different projects at each level. Students structure pathways of projects based on their emerging interests
and through assistance from faculty and industry
mentors. Through projects in students’ chosen pathways, they gradually learn how to collaboratively
understand complex problem spaces and embracesolutions spanning the four sets. Students realize
collaborative projects through studio-based courses, internships, and externships. Senior capstones
are realized in a similarly collaborative manner.
Student teams realizing collaborative innovations in
the work cells can be hired as individuals or teams
to further implement these innovations within an industry partner organization after graduation. Alternatively, student teams can start their own venturethat leverages their ideas and collaborative skills.

4. Semi-Automated Inspection, Focus: DroneBased Inspection
As enabling technologies mature, a Point-ofNeed Learning Platform (PNLP) will be required
to educate and upskill all related members of theworkforce in order to utilize and leverage thetechnologies. The PNLP advances targeted domain-specific skills while also leveraging and advancing diverse domain-general and life skills. It
thus becomes a key mechanism for enhancing theprofessional and personal development of humancapital and driving the SDG outcomes. It is highly
likely that point-of-need learning may utilize an
enabling technology, such as augmented reality,
to provide a learning delivery system that is symbiotic with maturing the ecosystem (see Chapter
II). An additional key element of the ecosystem
required to support the SDG outcomes of Planet,
Prosperity and Partnership is a stable supply chain.
The supply chain includes the people, machines,
and materials that allow the worker-machine interface to be realized. A collective intelligence approach to a sustainable supply chain for Industry
4.0 aims to create global partnerships, reduce theecological footprint, promote sustainability for the102

APPENDIX A

It is important to note that because work cellprojects combine academic and industry experience, they bridge these two relational contexts
for the students, thus further assisting their transition to the workforce. Industry and academia
have teamed for decades to provide experiential
learning opportunities. Industry has aligned collegiate hiring outcomes to students who participate
in experiential learning. However, in a traditional experiential learning setting, students work in
disciplinary-based teams that aim to improve ordevelop a discipline-specific capability for a product. For example, a cohort of aerospace engineering students will develop a drone for a Design,
Build, Fly program or a cohort of mechanical engineering students will improve the mechanisms,
structure, and engines for a car. In such situations,the outcome usually focuses on only one of thesets (i.e., feasibility). Because a student must havesome knowledge within their discipline, their participation in these experiential learning opportunities requires them to be at least a second-year
student, and often a third- or fourth-year student.
More recently, we are seeing teams composed of
students from different disciplines (i.e., engineering and business) covering two sets (i.e., feasibility and viability). But even in these contexts, thestudents predominantly perform work in their chosen disciplines.

in the program is designed to engage all components of sociotechnical innovation, which meansthat it also engages many different types of domain-specific knowledge. The CDP embeds students in such experiences throughout their studies,
expecting them to produce systems-level solutions
at every level. The students can see how different domain-specific expertise can complement
each other within a collective intelligence context.
They also learn, in practical terms, how to connect domain-general knowledge to different typesof domain-specific knowledge. They realize thatsuch connectivity requires that every participant
embody both domain-specific and domain-generalknowledge and that, in many cases, they need topossess working knowledge of the domain-specific knowledge of their peers. Furthermore, students
realize the critical role of life skills in dealing withcomplexity and ambiguity of sociotechnical systems in a collaborative manner that leads to collective intelligence. This CDP relational knowledge
framework advances personal knowledge alongwith an ever-expanding overlap of skills among
participants, as well as greater awareness of systems approaches and increasing collective intelligence ability by all members. The overall social
learning at the CDP also incorporates structured
and unstructured informal exchanges between
program participants from different disciplinesand different backgrounds. All participants (students, faculty, industry partners) engage together
as learners in a co-creation paradigm.

The CDP shifts the paradigm by giving students experiential learning opportunities that aresituated within a sociotechnical systems approachto building collective intelligence (the cross-sector
context of Industry 4.0 for Sustainable Development work cells). The CDP thus brings together
students, faculty, industry, and community partners to form transdisciplinary communities ofpractice (COP) in which members develop shared,
relational knowledge around core practices (Barab et al., 2002; Wenger, 1998). Every experience

In parallel with their collaborative projects, allstudents follow one of the ten disciplinary curricula that participate in the CDP. Each disciplinary
curriculum has a fairly fixed plan through first- andsecond-year courses, but by the third-year students
are expected to branch out into different pathways,
which further enhances the students’ self-discovery process. For example, students in electrical103

APPENDIX A

and computer engineering can choose one of eight
possible concentrations after their second year.
Additionally, all students in CDP are assigned anhonors faculty mentor with experience in transdisciplinary work and expertise in the student’s chosen discipline. The mentor works with the student
on integrating the domain-specific skills arisingfrom their discipline with the domain-general andlife skills that are emphasized in the collaborative
projects.

within a social learning context. A one-credit general education module is offered on each key elementof the four sets. Each module is taught in a mannerthat maps the domain-general knowledge associated with the elements of the sets to the domain-specific knowledge of participating disciplines. Each
module is also designed to map to one of the fourdomain-general skills of the Virginia Tech Pathways general education model: quantitative thinking, discourse, social science, and design/arts. For
example, the module on hardware-software interface is mapped to feasibility and to quantitative
thinking. All modules are offered asynchronously
and utilize interactive content applications and as

The structuring of the general education experience of the CDP assists learners’ integration of
domain-specific, domain-general, and life skills
Figure A2

The CDP Curriculum Promotes Collective Intelligence for Systems Approaches toSociotechnical Innovation (Image by Shahab Sagheb and Emily Harmon)

104

APPENDIX A

needed meetings with peers and instructors. As thestudents are realizing collaborative Industry 4.0
for Sustainable Development projects and advancing in their discipline, they discover which modules can help them develop domain-general skills
that complement their domain-specific skills. This
helps them solve complex problems through collaborating more effectively with students from other disciplines. Modules are offered at the novice,
capable, and skilled levels. Novice-level modules
have very few prerequisites given that the students
are generally relying on the transfer of previously learned knowledge from their domain-generalskills (rather than on disciplinary preparation). If anovice-level module sparks the interest of a particular student to learn more about the concept, thatstudent can complete relevant modules in the capable and skilled levels that gradually incorporate
more domain-specific knowledge. This means thatstudents are shaping their own pathway in a justin-time fashion by choosing the general education
modules that complement their domain-specificknowledge and collaborative learning aspirations.

large hub of domain-specific skills from their discipline, which are then connected to domain-general skills by collaborative project experiences
and mentoring. Students also have smaller hubs of
domain-specific skills beyond their discipline. The
CDP cross training modules leverage knowledge
mapping to domain-general skills to support thedevelopment of the smaller domain-specific hubs.
The overarching domain-general skill of the CDP
is systems thinking, and this skill is deeply integrated across the feasibility, viability, desirability andsustainability sets of sociotechnical systems. Discourse, quantitative thinking, societal understanding and human experience, and design thinking
are the other four domain-general skills associatedwith the CDP and Pathways general education. All
CDP domain-general skills are strongly supported by the customized modular general education
structure. Work-cell-based transdisciplinary andtrans-sector collaborative projects facilitate theconnection of life skills to domain-general skills.
The CDP focuses on the key life skills of collaboration, communication, reflection and self-discovery, agility in complexity, leveraging diversity,and creativity. Figure A3 emphasizes the learner’s
skills thus denoting that integrative knowledge accumulates in the person and not in the curriculum.
Given what we have outlined in this report, we expect the adaptive integrative approach of the CDP
to lead each student in developing differentiatedskill strengths and skill connectivity supported byvaried collections of modules, projects, and courses. This variation cannot be shown in the figure
due to limitations of a static image. In the Resources and Working Groups sections we discuss in detail the continuous and collaborative assessment
and improvement process we are implementing in
the CDP.

Figure A2 depicts how disciplinary preparation, general education, and collaborative experiential learning come together in the CDP as one
systems-level experience that promotes collective intelligence for collaborative sociotechnicalinnovation. Figure A3 shows how this collective
intelligence promotes and leverages IPPD of thelearner that spans domain-specific, domain-general, and life skills. In Figure A3, skills are shownas circles of different size (denoting variable skill
strength) that are connected through links of different strength denoted by width in the connectorlines. Learning experiences (modules, collaborative projects, and disciplinary courses) are shownas triangles (novice level), squares (capable level)and polygons (skilled level) connected throughmultiple possible pathways. All students have a105

APPENDIX A

Figure A3

CDP Skill Connectivity and IPPD Facilitation by a Highly-Structured CollectiveIntelligence Context

Collective Intelligence

Life Skills
Collaboration
Communication
Reflection and Self Discovery
Agility in Complexity
Creativity
Leveraging Diversity

Domain General Skills
Systems Thinking
Feasibility
Viability
Desireability
Sustainability
Discourse
Society and Human Experience
Quantitative Thinking
Design Thinking

Domain Specific Skills

106References

REFERENCESREFERENCES
Abes, E. S., Jones, S. R., & McEwen, M. K. (2007). Reconceptualizing the model of multiple dimensions of identity: The role of meaning-making capacity in the construction of multiple identities.
Journal of College Student Development, 48(1), 1–22.
Adelman, C., Ewell, P., Gaston, P., & Schneider, C. G. (2014). The Degree Qualifications Profile: A
learning-centered framework for what college graduates should know and be able to Do to earn
the associate, bachelor’s or master’s Degree. Lumina Foundation for Education. https://www.
luminafoundation.org/files/resources/dqp.pdf
Adler, R. (2015). Navigating continual disruption. Aspen Institute. https://csreports.aspeninstitute.org/
documents/NavigatingDistruption.pdf
Advanced Robotics for Manufacturing Institute. (n.d.). Driving the future of manufacturing throughcollaboration. https://arminstitute.org/about/Agarwal, R., Chandrasekaran, S., & Sridhar, M. (2016). Imagining construction’s digital future. Our
insights. http://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/
imagining-constructions-digital-future
Allison, S. T., & Goethals, G. R. (2011). Heroes: What they do and why we need them. Oxford University Press.
Alperovitz, G. (2013). What then must we do? Straight talk about the next American Revolution. Chelsea Green Publishing.
Alturi, V., Dietz, M., & Henke, N. (2017, September). Learning innovation in the digital age. McKinsey
Quarterly, (3). https://www.mckinsey.com/business-functions/organization/ our-insights/learning-innovation-in-the-digital-age
Amelink, C.T., & Nicewonger, T. (2019, October). Advancing integrative learning opportunities
through transdisciplinary communities. American Association for Colleges and Universities,
Transforming STEM Higher Education, Chicago, IL.
American School Counseling Association. (2015). State-by-state student-to-counselor ratios report: A
10-year trend. https://www.schoolcounselor.org/asca/media/asca/Publications/ratioreport.pdf
American Montessori Society. (2020). https://amshq.org/
108

REFERENCES

Anderson, E. C. (2005). Strengths-Based educating: A concrete way to bring out the best in students—
and yourself: The confessions of an educator who got it right—finally! Educational Horizons,
83(3), 180–189. https://files.eric.ed.gov/fulltext/EJ685057.pdf
Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman.
Anderson, J. R., Reder, L. M., & Simon, H. A. (1996). Situated learning and education. Educational
Researcher, 25(4), 5–11. https://doi.org/10.3102/0013189X025004005
Aoun, J.E. (2017). Robot-proof: higher education in the age of artificial intelligence. MIT Press.
Argyris, C. & Schön, D. A. (1978): Organizational learning. A theory of action perspective. Addison-Wesley Pub. Co.
Association of American Colleges and Universities. (2011). The LEAP vision for learning: outcomes,
practices, impact, and employers’ views. Association of American Colleges and Universities.
Association of American Colleges and Universities. (2020). VALUE: What is value? https://www.aacu.
org/value
Association of Public & Land Grant Universities (APLU). (2019). University-community student
success partnerships. https://www.aplu.org/members/commissions/urban-serving-universities/
student-success/cog.html
Association of Public & Land Grant Universities (APLU) & Coalition of Urban Serving Universities(USU). (n.d.). USU initiatives. https://www.aplu.org/members/commissions/urban-serving-universities/student-success
Association of Public & Land Grant Universities (APLU) & Coalition of Urban Serving Universities(USU). (2019). Delivering 21st century skills [White paper]. https://www.aplu.org/members/commissions/urban-serving-universities/usu-publications/APLU_USU_21stCentury_.pdf
Autor, D.H. (2013). The “Task Approach” to labor markets: An overview. Journal for Labour Market
Research, 46(3), 185–199. https://doi.org/10.2139/ssrn.2211349
Autor, D.H. (2015). Why are there still so many jobs? The history and future of workplace automation.
Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3
Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An
empirical exploration. The Quarterly Journal of Economics, 118(4), 1279–1333. https://doi.
org/10.1162/003355303322552801
109

REFERENCES

Autor, D.H., & Price, B. (2013). The changing task composition of the US Labor Market: An update ofAutor, Levy, and Murnane [Working paper].
Avis, J. (2002). Social capital, collective intelligence and expansive learning: Thinking through theconnections, education, and the economy. British Journal of Educational Studies, 50(3), 308–
326. https://doi.org/10.1111/1467-8527.t01-1-002051
Balcar, J., Homolová, E., Karásek, Z. et al. (2011). Transferable skills across economic sectors: Roleand importance for Employment at European level. Publications Office of the European Union.
Baldwin, T. T., & Ford, J. K. (1988). Transfer of training: A review and directions for future research.
Personnel Psychology, 41(1), 63–105. https://doi.org/10.1111/j.1744-6570.1988.tb00632.x
Balsamo, A. (2010). Working the paradigm shift: Educating the technological imagination. In D. Araya& M. A. Peters (Eds.), Education in the creative economy: Knowledge and learning in the ageof innovation (pp. 423–446). Peter Lange Publishing.
Bandura, A. (1986). Social foundations of thought and action. Prentice Hall.
Bandura, A. (1997). Self-efficacy: The exercise of control. Freeman.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology,
52(1), 1–26. https://doi.org/10.1111/1467-839X.00024
Banerji, S. (2007). Report: Employers say college graduates lack essential skills to succeed in today’s
global Economy. Diverse Issues in Higher Education, 23(26), 18.
Barab, S. A., Barnett, M., & Squire, K. (2002). Developing an empirical account of a community ofpractice: Characterizing the essential tensions. The Journal of the Learning Sciences, 11(4),489–542. https://doi.org/10.1207/S15327809JLS1104_3
Bartlett, W., & Rees, T. (2000). The variable contribution of guidance services in different types oflearning societies. In F. Coffield (Ed.), Differing visions of a learning society (pp. 139–166).
Policy Press.
Baxter Magolda, M. B. (1999). Creating contexts for learning and self-authorship: Constructive-developmental pedagogy. Vanderbilt University Press.
Basken, P. (2020, April 23). From crisis, US researchers see prospect of durable gains: Partnershipapproach during pandemic raises hopes of bursting scientific silos. Times Higher Education.
https://www.timeshighereducation.com/news/crisis-us-researchers-see-prospect-durable-gains#

110

REFERENCES

Bedwell, W. L., Salas, E., & Fiore, S. M. (2011). Developing the 21st century (and beyond) workforce:
A review of interpersonal skills and measurement strategies. In NRC Workshop on Assessing
21st Century Skills. https://www.academia.edu/998931/Developing_the_21_st_Century_and_
Beyond_Workforce_A_Review_of_Interpersonal_Skills_and_Measurement_Strategies
Benner, P. (2004). Using the Dreyfus model of skill acquisition to describe and interpret skill acquisition and clinical judgment in nursing practice and education. Bulletin of Science, Technology &Society, 24(3), 188–199. https://doi.org/10.1177/0270467604265061
Bennington College. (n.d.). Field Work Term. https://www.bennington.edu/academics/field-work-term
Bhattacharyya, S., Junot, M., & Clark, H. (2013). Can you hear us? Voices raised against standardized testing by novice teachers. Creative Education, 4(10), 633–639. https://doi.org/10.4236/
ce.2013.410091
Blair, P. Q., & Deming, D. J. (2020). Structural increases in skill demand after the Great Recession(No. w26680). National Bureau of Economic Research. Interactive Media in Education, 1,
1–25. https://ssrn.com/abstract=3522329
Bleizner, R., Grant, A., & Rikakis, T. (2016). Envisioning Virginia Tech Beyond Boundaries: A 2047
Vision. http://hdl.handle.net/10919/79633
Bliss, T. J., & Smith, M. (2017). A brief history of open educational resources. In R. S. Jhangiani & R.
Biswas-Diener (Eds.), Open: The philosophy and practices that are revolutionizing educationand science (pp. 11–28). Ubiquity Press.
Bloom, B. S. (1956). Taxonomy of educational objectives, handbook I: The cognitive domain. David
McKay Co. Inc.
Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16. https://doi.
org/10.3102/0013189X013006004
Boeing. (2020). Our values. https://www.boeing.com/principles/values.page
Bohn, D. (2019, February 24). Microsoft’s Hololens 2: A $3,500 mixed reality headset for the factory,
not the living room. The Verge. https://www.theverge.com/2019/2/24/ 18235460/microsoft-hololens-2-price-specs-mixed-realityar-vr-business-work-features-mwc-2019
Boulet, G. (2015, October 17). The difference between knowledge and skills: Knowing does not makeyou skilled. eLearning Industry. https://elearningindustry.com/difference-between-knowledgeand-skills-knowing-not-make-skilled111

REFERENCES

Brown University. (n.d.). The open curriculum. https://www.brown.edu/academics/undergraduate/
open-curriculum
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42. https://doi.org/10.3102/0013189X018001032
Brown, A., & Keep, E. (Eds.). (2000). Review of vocational education and training research in the
United Kingdom. Office for Official Publications of the European Communities.
Bruner, J. (1990). Acts of meaning. Harvard University Press.
California Polytechnic. (2017). Cal Poly launches world’s first university-based cloud innovation center powered by Amazon Web Services. Cal Poly News. https://calpolynews.calpoly.edu/news_releases/2017/october/amazon
Cardone, T. (2018). Embracing customization in higher education: Leveraging personal learning design to promote design thinking and self-authorship. About Campus, 23 (4), 11–18. https://doi.
org/10.1177/1086482218817533
Carnegie Mellon Robotics Academy. (2020). CS-STEM network. CS2N. https://www.cs2n.org/
Carnegie Mellon University. (2019). Advanced robotics for manufacturing (ARM) partners with Carnegie Mellon University’s NREC and CMRA to grow a skilled, technical workforce. National robotics engineering center. https://www.nrec.ri.cmu.edu/nrec/media/news-stories-pages/
news-stories-2019/cmra-arm-smart.html
Carnegie Mellon University. (n.d.). The future of manufacturing is here. Advanced manufacturing.
https://www.cmu.edu/advanced-manufacturing/
Carnegie Mellon University. (n.d.). Undergraduate programs. Computer science department. https://
csd.cmu.edu/academic/undergraduate/bachelors-curriculum-admitted-2018
Carroll, J.B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge University Press.
Carayannis, E. G. (2014). Developed democracies versus emerging autocracies. Journal of Innovationand Entrepreneurship, 3(12), 1–23. https://doi.org/10.1186/s13731-014-0012-2
Carayannis, E. G., & Campbell, D. (2019). Smart quintuple helix innovation systems: How social ecology and environmental protection are driving innovation, sustainable development and economic growth. Springer.
Chatterjee, D. K. (2019). Human rights in honors education [Paper presentation]. Honors Education in
Research Universities, University of Utah, Salt Lake City, United States.
112

REFERENCES

Chickering, A. W., & Reisser, L. (1993). Education and identity. Jossey-Bass Inc.
Clark, R. E., & Voogel, A. (1985). Transfer of training principles for instructional design. Educational
Communication and Technology, 33(2), 113–123.
Clifton, D. O., Anderson, E., & Schreiner, L. A. (2002). StrengthsQuest. The Gallup Organization.
Coffield, F. (1999). Breaking the consensus: Lifelong learning as social control. British Educational
Research Journal, 25(4), 479–499. https://doi.org/10.1080/0141192990250405
Coffield, F. (Ed.). (2000). Differing visions of a learning society: Research findings (Vol. 1). Policy
Press.
Coghlan, D., & Brydon-Miller, M. (Eds.). (2014). The SAGE encyclopedia of action research. Sage.
Collins, A. (2006). Cognitive apprenticeship. In K. R. Sawyer (Ed.), The Cambridge handbook of thelearning sciences (pp. 47–60). Cambridge University Press.
Collins, A., & Halverson, R. (2018). Rethinking education in the age of technology: The digital revolution and schooling in America. Columbia University-Teacher’s College Press.
Collins, R. (2002). Credential inﬂation and the future of universities. In S. Brint (Ed.) The future of thecity of intellect (pp. 23–46). Stanford University Press.
Costa, A., & Kallick, B. (2014). Dispositions: Reframing teaching and learning. Corwin.
Costa, H. M., Nicholson, B., Donlan, C., & Van Herwegen, J. (2018). Low performance on mathematical tasks in preschoolers: the importance of domain-general and domain-specific abilities.
Journal of Intellectual Disability Research, 62(4), 292–302. http://doi.org/10.1111/jir.12465
Council, S. S. R. (2018). To secure knowledge: Social science partnerships for the common good.
https://www.ssrc.org/to-secure-knowledge/
Creative Commons (CC). (2019). Education/OER. https://creativecommons.org/about/program-areas/
education-oer/Crow, M. M., & Dabars, W. B. (2020). The fifth wave: The evolution of American higher education.
Johns Hopkins University Press.
Darbellay, F. (2015). Rethinking inter- and transdisciplinarity: Undisciplined knowledge and theemergence of a new thought style. Futures, 65, 163–174. http://dx.doi.org/10.1016/j.futures.2014.10.009

113

REFERENCES

Davies, J. S., & Spicer, A. (2015). Interrogating networks: Towards an agnostic perspective on governance research. Environment and Planning C: Government and Policy, 33(2), 223–238. https://doi.org/10.1068/c11292
Deci, E. L., & Ryan, R. M. (2008). Facilitating optimal motivation and psychological well-being
across life’s domains. Canadian Psychology/Psychologie Canadienne, 49(1), 14. https://doi.
org/10.1037/0708-5591.49.1.14
Dede, C. (2019). The 60 year curriculum: Developing new educational models to serve the agilelabor market. The evolution: A destiny solutions illumination. https://evolllution.com/revenue-streams/professional_development/the-60-year-curriculum-developing-new-educational-models-to-serve-the-agile-labor-market/
Democracy at Work Institute. (2018). State of the sector: US worker cooperatives in 2017. Journal ofParticipation and Employee Ownership, 2(3), 190–201. https://doi.org/10.1108/JPEO-09-20190023
Derivatives. (2019, June 19). In Wikipedia. https://en.wikipedia.org/wiki/Time_derivative
Derrida, J. (2004). Eyes of the university: Right to philosophy 2. Stanford University Press.
De Weck, O. L., Roos, D., & Magee, C. L. (2011). Engineering systems: Meeting human needs in acomplex technological world. Mit Press.
Dewey, J. (1906). The child and the curriculum. University of Chicago Press.
Dewey, J. (1910). How we think. D.C. Heath & Co. Publishers.
Dewey, J. (1934). Art as experience. Routledge.
Dewey, J. (1938). Experience and education. Collier.
Dewey, J. (1966). Democracy and Education. Free Press.
Dewey, J. (1964) What psychology can do for the teacher. In R. Archambault (Ed.), John Dewey on
education: Selected writings. Random House.
Dierking, L. D., & Falk, J. H. (2016). 2020 Vision: Envisioning a new generation of STEM learning
research. Cultural Studies of Science Education, 11(1), 1–10. https://doi.org/10.1007/s11422015-9713-5
Donovan, S. (2015). Multi-agency science and technology priorities for the FY 2017 budget. Office of
the President.
114

REFERENCES

Dourish, P. (2001). Where the action is: The foundations of embodied interaction. MIT Press.
Dreyfus, H. L., & Dreyfus, S. E. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. Free Press.
Duncan, C. M. (2001). Social capital in America’s poor rural communities. In S. Saegert, J. P. Thompson, & M. R. Warren (Eds.), Social capital and poor communities (pp. 60–88). Russell Sage.
Duncan-Andrade, J. M. R., & Morrell, E. (2008). The art of critical pedagogy: Possibilities for movingfrom theory to practice in urban schools (Vol. 285). Peter Lang.
DuPre, C., & Williams, K. (2011). Undergraduates’ perceptions of employer expectations. Journal of
Career and Technical Education, 26(1), 8–19. https://doi.org/10.21061/jcte.v26i1.490
Eagle, N., Macy, M., & Claxton, R. (2010). Network diversity and economic development. Science,
328, 1029–1031. https://doi.org/10.1126/science.1186605
EdPlus (2018). Who we are. Arizona State University. https://edplus.asu.edu/who-we-are
Eraut, M. (1985). Knowledge creation and knowledge use in professional contexts. Studies in Higher
education, 10(2), 117–133. https://doi.org/10.1080/03075078512331378549
Eraut, M. (2004). Transfer of knowledge between education and workplace settings. In H. Rainbird, A.
Fuller, & H. Munro (Eds.), Workplace learning in context (pp. 201–221). Routledge.
Ericsson, K.A., Krampe, R.T., & Tesch-Römer, C. (1993). The role of deliberate practice in theacquisition of expert performance. Psychological Review, 100(3), 363–406. https://doi.
org/10.1037//0033-295X.100.3.363
ESSENCE (2016). Planning, monitoring and evaluation framework for research capacity strengthening. ESSENCE on Health Research. World Health Organization. https://www.who.int/tdr/publications/Essence_frwk_2016_web.pdf
Etherington, Cait. (2018, April 22). New Gallup study finds student satisfaction is above average at
WGU. ELearningInside News https://news.elearninginside.com/new-gallup-study-finds-student-satisfaction-average-wgu/
Fadel, C., Bialik, M., & Trilling, B. (2015). Four-dimensional education. Center for Curriculum Redesign.
Feuerstein, R., Rand, Y., Hoffman, M. B., & Miller, R. (1980). Instrumental enrichment: An intervention program for cognitive modifiability. University Park Press.

115

REFERENCES

Florida, R. (2002). The rise of the creative class: And how it’s transforming work, leisure, communityand everyday life. Basic Books.
Flowers, W. (2009, May 8). Engineer of the future 2.0. Summit on transforming engineering education.
https://www.youtube.com/watch?v=F84LtXvLTtA
Foucault, M. (1969). L’Archéologie du savoir. Éditions Gallimard.
Ford, J. K., Smith, E. M., Weissbein, D. A., Gully, S. M., & Salas, E. (1998). Relationships of goal
orientation, metacognitive activity, and practice strategies with learning outcomes and transfer.
Journal of Applied Psychology, 83(2), 218. https://doi.org/10.1037/0021-9010.83.2.218
Furrer, C., & Skinner, E. (2003). Sense of relatedness as a factor in children’s academic engagement
and performance. Journal of Educational Psychology, 95(1), 148. https://doi.org/10.1037/00220663.95.1.148
Galaleldin, M., & Anis, H. (2017). Impact of makerspaces on cultivating students’ communities of practice. Conference Proceedings from the 2017 ASEE Annual Conference & Exposition. https://www.asee.org/public/conferences/78/papers/20041/view
George Mason University. (2019). NOVA ADVANCE. https://www2.gmu.edu/admissions-aid/advanceGeorgia Tech Commission on Creating the Next in Education. (2018a). Deliberate innovation, lifetime
education. Georgia Tech Office of the Provost. https://provost.gatech.edu/sites/default/files/documents/deliberate_innovation_lifetime_education.pdf
Georgia Tech Commission on Creating the Next in Education (2018b). Initiative 1: Whole-person education. Georgia Tech Office of the Provost. https://provost.gatech.edu/educational-innovation/
reports/lifetime-education/initiatives/whole-person-education
Georgia Tech Commission on Creating the Next in Education (2018c). Whole-person development.
In Creating the next in education, supplement (pp. 1–6). https://provost.gatech.edu/commission-creating-next-education
Ginda, M., Richey, M. C., Cousino, M., & Börner, K. (2019). Visualizing learner engagement, performance, and trajectories to evaluate and optimize online course design. PLoS One, 14(5), 1–19.
https://doi.org/10.1371/journal.pone.0215964
Gnedenko, B. V., Kolmogorov, A. (1954). Limit distributions for sums of independent random variables. Addison-Wesley Publishing Company.
Goel, A. K., & Polepeddi, L. (2016). Jill Watson: A virtual teaching assistant for online education.
Georgia Institute of Technology.
116

REFERENCES

Goldrick-Rab, S. (2016). Paying the price: College costs, financial aid, and the betrayal of the American dream. University of Chicago Press.
Goldstein, I. L., & Ford, J. K. (2002). Training in organizations. Wadsworth.
Georgia State University. (2020). GPS advising. Student success programs at Georgia State. https://success.students.gsu.edu/gps-advising/
Grabher, G., & Stark, D. (1997). Organizing diversity: Evolutionary theory, network analysis and postsocialism. Regional Studies, 31, 533–544. https://doi.org/10.1080/00343409750132315
Green, T., & Parnell, A. (2017). Comprehensive student record project: Final report. American Association of Collegiate Registrars and Admissions Officers (AACRAO) and the Associationof Student Personnel Administrators (NASPA). https://www.aacrao.org/docs/default-source/
signature-initiative-docs/clr/comprehensive-student-record-project-final-report-9_2017---pubversion.pdf
Grinnell College. (n.d.-a). First year tutorial. Academics. https://www.grinnell.edu/academics/experience/tutorial
Grinnell College. (n.d.-b). Grinnellians map their own academic journeys. Academics. https://www.
grinnell.edu/admission/why-grinnell/academics
Guattari, F. (1972). Psychoanalysis and transversality. Semiotext(e).
Guest, D. (1991, September 17). The hunt is on for the Renaissance man of computing. The Independent.
Habib, M. K., & Chimsom, C. (2019). Industry 4.0: Sustainability and design principles. 2019 20th
International Conference on Research and Education in Mechatronics (REM) (pp. 1–8). IEEE.
Hall, B. L., & Tandon, R. (2017). Decolonization of knowledge, epistemicide, participatory researchand higher education. Research for All, 1(1), 6–19. https://doi.org/10.18546/RFA.01.1.02
Harnecker, C. (2007). Workplace democracy and collective consciousness. Monthly Review, 59(6),27–40. https://doi.org/10.1521/siso.2009.73.3.309
Haveman, R.H., & Smeeding, T.M. (2006). The role of higher education in social mobility, The Futureof Children, 16(2), 125–150. https://doi.org/10.1353/foc.2006.0015
Hart, R. A. (2016). Falling short? College learning and career success. NACTA Journal, 60(1), 1–6.
Heales, C., Hodgson, M., & Rich, H. (2017). Humanity at work: MONDRAGON, a social innovation
ecosystem case study. The Young Foundation.
117

REFERENCES

Hecklau, F., Galeitzke, M., Flachs, S., & Kohl, H. (2016). Holistic approach for human resource
management in industry 4.0. Procedia CIRP, 54(1), 1–6. https://doi.org/10.1016/j.procir.2016.05.102
Hein, G. (2009). Learning science in informal environments: People, places, and pursuits. Museums &Social Issues, 4(1), 113-124.
Hermans, J., & Lentz, B. (2013). Equilibria and kinetics of biological macromolecules. Wiley Online
Library.
Herzog, S. M., & Hertwig, R. (2009). The wisdom of many in one mind: Improving individual judgments with dialectical bootstrapping. Psychological Science, 20(2), 231–237. https://doi.
org/10.1111/j.1467-9280.2009.02271.x
Hevner, A., & Chatterjee, S. (2010). Design science research in information systems. In Design research in information systems (pp. 9–22). Springer.
Hlatshwayo, S., & Spence, M. (2014). Demand and defective growth patterns: The role of the tradable
and non-tradable sectors in an open economy. American Economic Review, 104 (5), 272–77.
https://doi.org/10.1257/aer.104.5.272
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Hoffman, R. R., Ward, P., Feltovich, P. J., DiBello, L., Fiore, S. M., & Andrews, D. H. (2014). Accelerated expertise: Training for high proficiency in a complex world. Psychology Press.
Holt, E., Shaurette, M. and Chasek. C. (2018). A Comparison of construction management and engineering student learning styles, 2016 American Society of Engineering Education, 2016 Annual
Conference & Exposition.
Hope, D., & Martelli, A. (2019). The transition to the knowledge economy, labor market institutions,and income inequality in advanced democracies. World Politics, 71(2), 236–288. https://doi.
org/10.1017/S0043887118000333
Hutchins, E. (1995). Cognition in the wild. MIT Press.
IDEO. (n.d). Design thinking defined. IDEO Design Thinking. https://designthinking.ideo.com/
Is it still possible to pay for college? (2019). New York Times. https://www.nytimes.com/interactive/2019/09/19/opinion/paying-college-tuition.html
118

REFERENCES

Jackson, Y., & McDermott, V. (2015). Unlocking student potential: How do I identify and activate students’ strengths? ASCD.
Jantsch, E. (1972). Inter- and transdisciplinary university. Higher Education, 1(1), 7–37. https://doi.
org/10.1007/BF00145222
Jassel, P. K., & Clark, H. (2016). The evolution of a new learning economy. In K. Winters (Ed.), The
New learning economy and the rise of the working learner: An anthology of recent evidence(pp. 14–22). ACT Foundation and ACT Center for Equity in Learning. https://pages2.act.org/riseofworkinglearners.html#_ga=2.135915894.610323121.1567628866-2066686857.1567628866
Jefferson County Public Schools. (n.d.). Academies of Louisville. JCPS. https://www.jefferson.kyschools.us/academies-louisvilleJensen, E. (1998). Teaching with the brain in mind. Association for Supervision and Curriculum Development.
Johnson, W., & Bouchard Jr, T. J. (2005). The structure of human intelligence: It is verbal, perceptual,and image rotation (VPR), not fluid and crystallized. Intelligence, 33(4), 393–416. https://doi.
org/10.1016/j.intell.2004.12.002
Jonassen, D., Cernusca, D., & Ionas, G. (2007). Constructivism and instructional design: The emergence of the learning sciences and design research. In R. A. Reiser & J. V. Dempsey (Eds.),
Trends and issues in instructional design and technology (2nd ed., pp. 45–52). Pearson.
Joo, J., & Spies, R. R. (2019, November 7). Aligning many campuses and instructors around a common adaptive learning courseware in introductory statistics: Lessons from a multi-year pilot inMaryland. https://doi.org/10.18665/sr.312073
Journeys. (2019). Your learning map for endless possibilities. https://journeysmap.com/
Kadel, R. S., Gazi, Y., Harmon, S., Goel, A., & Courville, T. (2019). Toward a Road Map for scalable
advanced learning ecosystems (SALES). International Journal on Innovations in Online Education, 3(1). https://doi.org/10.1615/IntJInnovOnlineEdu.2019030903
Kegan, R. (1994). In over our heads: The mental demands of modern life. Harvard University Press.
Kelly, K. (2016). The inevitable: Understanding the 12 technological forces that will shape our future.
Viking.
Kinghorn, J. R., & Womack-Smith, W. (2013). Nontraditional honors. Journal of the National Collegiate Honors Council, 14(1), 15–21.
119

REFERENCES

Klein, J. T. (2008). Evaluation of interdisciplinary and transdisciplinary research: a literature review.
American Journal of Preventive Medicine, 35(2), S116–S123. https://doi.org/10.1016/j.amepre.2008.05.010
Knight, D. (2013). Curricular and organizational features of undergraduate interdisciplinary programs.
Innovative Higher Education, 38(2), 143–158. https://doi.org/10.1007/s10755-012-9232-1
Knowledge Media Institute & The Open University. (2018). Researching the potential of blockchains.
OpenBlockchain. Knowledge Media Institute, The Open University, UK. Retrieved from http://
blockchain.open.ac.uk
KnowledgeWorks. (2020). Thought Leadership Resources. https://knowledgeworks.org/resources/
Knudsen, H., Busck, O., & Lind, J. (2011). Work environment quality: the role of workplace participation and democracy. Work, Employment and Society, 25(3), 379–396. https://doi.
org/10.1177/0950017011407966
Koedinger, K., McLaughlin, E. A., & Stamper, J. C. (2014, May). Data-driven learner modeling to understand and improve online learning: MOOCs and technology to advance learning and learning
research. Ubiquity, 3. https://dl.acm.org/citation.cfm?id=2591682
Koestler, A. (1967). The ghost in the machine. Penguin Group.
Kohlberg, L. (1976). Moral Stages, Moralization: The Cognitive Developmental Approach. In T. Lickona (Ed.), Moral development and behavior. Holt, Rinehart, Winston.
Kohlberg, L. (1981). The philosophy of moral development. Harper & Row.
Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1956). Taxonomy of educational objectives: Theclassification of educational goals; Handbook II: Affective domain. David McKay Company,
Incorporated.
Lattuca, L. R., & Stark, J. S. (2011). Shaping the college curriculum: Academic plans in context. Wiley& Sons.
Lillard, A. S., Heise, M. J., Richey, E. M., Tong, X., Hart, A., & Bray, P. M. (2017). Montessori preschool elevates and equalizes child outcomes: A longitudinal study. Frontiers in psychology, 8,
1783. https://doi.org/10.3389/fpsyg.2017.01783
Lin, S. W., Murphy, B., Clauer, E., Loewen, U., Neubert, R., Bachmann, G., Pai, M., & Hankel, M.
(2017). Architecture alignment and interoperability: An industrial internet consortium and plattform industrie 4.0 joint whitepaper. Industrial Internet Consortium.
120

REFERENCES

Lopata, C., Wallace, N. V., & Finn, K. V. (2005). Comparison of academic achievement between Montessori and traditional education programs. Journal of Research in Childhood Education, 20(1),5–13. https://doi.org/10.1080/02568540509594546
Lu, W. F., Yang, J. K., & Chu, H. T. (2017, April). Playing Mastermind game by using reinforcement
learning. In 2017 First IEEE International Conference on Robotic Computing (IRC) (pp. 418–
421). IEEE.
Madhaven, K., & Richey, M. (2016). Problems in big data analytics in learning. Journal of Engineering
Education, 105(1), 6–14. https://doi.org/10.1002/jee.20113
Madni, A. M., Paulson, C., Spraragen, M., Richey, M. C., Nance, M. L., & Vander Wel, M. (2015, October). Model-based optimization of learning curves: Implications for business and government[Conference paper]. INCOSE International Symposium, 25(1) 1070–1084.
Madrigal, A. (2017, October 12). What Facebook Did to American democracy and why it was so hard
to see it coming. The Atlantic. https://www.theatlantic.com/technology/archive/2017/10/whatfacebook-did/542502
Mahiri, J. (1998). Shooting for excellence: African American and youth culture in new century schools.
National Council of Teachers of English.
Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., Ko, R., & Sanghvi, S. (2017, November). What the future of work will mean for jobs, skills, and wages. McKinsey & Company.
https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
Maslow, A. H. (1968). Toward a psychology of being. Van Nostrand.
Matusovich, H., Carrico, C., Harris, A., Sheppard, S., Brunhaver, S., Streveler, R., & Lester, M. B. M.
(2019). Internships and engineering: Beliefs and behaviors of academics. Education+ Training,
61(6), pp. 650–665.
McAfee, A., & Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. W.
W. Norton & Company.
McKenzie, Lindsay. (2019). Seeking a shared global standard for digital credentials. Inside Higher Ed.
https://www.insidehighered.com/digital-learning /article/2019/04/24/mit-and-8-other-universities-partner-shared-digital-credential
Miller, R. (2010). From the ground up: Rethinking engineering education for the 21st century [Conference paper]. Symposium on Liberal Education, Union College, New York.
121

REFERENCES

Mooney, C. G. (2013) An introduction to Dewey, Montessori, Erikson, Piaget & Vygotsky (2nd Ed.).
Redleaf Press.
Moore, M.G. (1993). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of
distance education (pp. 22–38). Routledge.
Muro, M., Maxim, R., & Whiton, J. (2019). Automation and artificial intelligence: How machines areaffecting people and places. Brookings Institute. https://www.brookings.edu/research/automation-and-artificial-intelligence-how-machines-affect-people-and-places/
Nagel, T. (1986). The view from nowhere. Oxford University Press.
National Academy of Engineering. (2005). Educating the engineer of 2020: Adapting engineering education to the new century. National Academies Press.
National Academy of Science. (2004). Facilitating interdisciplinary research. National Academies
Press.
National Association of Colleges and Employers (NACE). (2017). Career readiness defined. https://www.naceweb.org/career-readiness/competencies/career-readiness-defined/
National Nanotechnology Initiative. (2015). A nanotechnology-inspired grand challenge for futurecomputing. Nano.gov. http://www.nano.gov/futurecomputing
National Research Council. (2000). How people learn: Brain, mind, experience, and school: Expanded
edition. National Academies Press.
National Research Council. (2009). Surrounded by science: Learning science in informal environments.
National Academies Press.
National Research Council (U.S.). (2013). Education for life and work: Developing transferable knowledge and skills in the 21st Century. National Academies Press.
National Science Board (NSB). (2019). The skilled technical workforce: crafting America’s science& engineering enterprise. National Science Foundation. https://www.nsf.gov/nsb/publications/2019/nsb201923.pdf
National Science Foundation. (2018). Boeing, National Science Foundation announce partnershipfor workforce development and diversity in STEM. https://www.nsf.gov/news/news_summ.
jsp?cntn_id=296700
National Society for Minorities in Honors. (n.d.). http://www.nsfmih.org/

122

REFERENCES

Nicewonger, T., & Amelink C. (2019, April 30). Expanding transdisciplinary capacity: Creating
connections across STEM and Non-STEM Disciplines. National Alliance for Broader Impacts.
Tuscon, AZ.
Nicolescu, B. (2002). Manifesto of transdisciplinarity. SUNY Press.
Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom:
Applying self-determination theory to educational practice. Theory and research in Education,
7(2), 133–144. https://doi.org/10.1177/1477878509104318
Northeastern University. (2015). Northeastern 2025. https://www.northeastern.edu/academic-plan/
Northeastern University. (2019). Lifetime learning membership. https://www.northeastern.edu/graduate/
admissions-information/lifetimelearning/Northeastern University. (2020). Global Mission. GEO. https://www.northeastern.edu/geo/aboutus/mission/
Oakley, J. (2018). Intelligent cognitive assistants (ICA) workshop summary and research needs. National Science Foundation. https://www.nsf.gov/crssprgm/nano/reports/ICA2_Workshop_Report_2018.pdf
Organization for Economic Co-Operation and Development (OECD). (2018). The future of educationand skills: Education 2030. http://www.oecd.org/education/2030-project/#:~:text=OECD%20
Future%20of%20Education%20and,Economic%20Co%2Doperation%20and%20Development&text=The%20Future%20of%20Education%20and,in%20and%20shape%20their%20
futureOsborne, P. (2015). Problematizing disciplinarity, transdisciplinarity problematics. Theory, Culture &Society, 32(5–6), 3–35. https://doi.org/10.1177/0263276415592245
Osterberg, L. G., Goldstein, E., Hatem, D. S., Moynahan, K., & Shochet, R. (2016). Back to the future:what learning communities offer to medical education. Journal of Medical Education and Curricular Development. https://doi.org/10.4137/JMECD.S39420
Oxford Consortium. (2019). Oxford Consortium on Human Rights. https://www.oxfordconsortium.org
Page, S. E. (2007). The difference. Princeton University Press.
Pateman, C. (1970). Participation and democratic theory. Cambridge University Press.
Perkins, D. N., & Salomon, G. (1989). Are cognitive skills context-bound? Educational Researcher,18(1), 16–25. https://doi.org/10.3102/0013189X018001016
123

REFERENCES

Piaget, J. (1954). The construction of reality in the child (M. Cook trans.). Basic Books.
Piaget, J. (1963). The origin of intelligence in children. Norton.
Pink, D. H. (2009). Drive: The surprising truth about what motivates us. Riverhead Books.
Plato, & Richards, I. A. (1966). Plato’s republic. Cambridge University Press.
Polanyi, M. (1958). Personal knowledge: Towards a post-critical philosophy. University of Chicago
Press.
Popović, K. (2014). The skills: A chimera of modern European adult education. In M. N. Gravani & G.
K. Zarifis, Challenging the European area of lifelong learning (pp. 17–29). Springer.
Popowitz, M., & Dorgelo, C. (2018, February 13). University-led grand challenges. https://escholarship.org/uc/item/46f121cr
Posey, T. (2019). Different cultures cause me to hesitate. In G. Harper (Ed.), Diversity, equity and inclusion in honors education. Cambridge Scholars Publishing.
Purdue Global. (2020). Transfer students. Purdue University Global. https://www.purdueglobal .edu/
transfer-students/
Purdue Polytechnic High School. (n.d.). https://pphs.purdue.edu/about
Purdue University. (2019). A revolutionary school backed by a pioneering university.
Purdue University–Purdue Polytechnic Institute. (2020). Hands-on education. Real-world success.
https://polytechnic.purdue.edu/
Prelec, D., Seung, S. H., & McCoy, J. (2017). A solution to the single-question crowd wisdom problem.
Nature, 541(7638), 532–535. https://doi.org/10.1038/nature21054
Reagans, R., & Zukerman, E. (2001). Networks, diversity, and productivity: The social capital of
corporate R&D teams. Organizational Science, 12(4), 502–517. https://doi.org/10.1287/
orsc.12.4.502.10637
Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of experimental psychology: General, 118(3), 219–235. https://doi.org/10.1037/0096-3445.118.3.219
Rees, T. & Bartlett, W. (1999a) Adult guidance services in the European learning society: A Scottish
case study. Studies in the Education of Adults, 31(1), 21–34. https://doi.org/10.1080/02660830.1
999.11661399
124

REFERENCES

Rees, T., & Bartlett, W. (1999b). Models of guidance services in the learning society: The case of theNetherlands. In F. Cofﬁeld (Ed.), Why’s the beer always stronger up north? Studies of lifelong
learning in Europe (pp. 21–30). Bristol.
Reeve, J. (2002). Self-determination theory applied to educational settings. In E. L. Deci & R. M. Ryan
(Eds.), Handbook of self-determination research (pp. 183–203). University of Rochester Press.
Results. (2020). Achievable Dream Academies. https://achievabledream.org/our-program/results/
Rhodes, T. (2010). Assessing outcomes and improving achievement: Tips and tools for using rubrics.
Association of American Colleges & Universities.
Rhodes, T. (2019). The changing nature of work and careers: Higher education as a hub for establishinga lifelong learning System. Liberal Education, 105(3–4), 6–11.
Rikakis, T., Kelliher, A., Nicewonger, T., & Swearer, R. (2019). Transdisciplinary and transsector
knowledge ecosystems advance knowledge democracies [keynote presentation]. Proceedings ofEuropean Conference on Education 2019, London, UK.
Rikakis, T., Kelliher, A., Sundaram, H., & Huang, J. B. (2018). Progressive cyber-human intelligence.
ACM Interactions, (25)4.
Rothschild, J. & Whitt, J. A. (1986). The Cooperative workplace: Potentials and dilemmas of organizational democracy and participation. Cambridge University Press.
Rothschild-Whitt, J. (1979). The collectivist organization: An alternative to rational-bureaucratic models. American Sociological Review, 44(4), 509–527. https://doi.org/10.2307/2094585.
Rothschild-Whitt, J. & Whitt, J. A. (1986). Worker-owners as an emergent class: Effects of cooperative
work on job satisfaction, alienation and stress. Economic and Industrial Democracy, 7, 297–
317. https://doi.org/10.1177/0143831X8673004
Ruijs, N. (2017). The effects of Montessori education: Evidence from admission lotteries. Economics of
Education Review, 61, 19–34. https://doi.org/10.1016/j.econedurev.2017.09.001
Sa, C. (2008). ‘Interdisciplinary strategies’ in U.S. research universities. Higher Education, 55(5),537–552. https://doi.org/10.1007/s10734-007-9073-5
Salomon, G., & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanism of a neglected phenomenon. Educational psychologist, 24(2), 113–142. https://doi.org/10.1207/
s15326985ep2402_1
Salomon, G., & Perkins, D. N. (1998). Chapter 1: Individual and social aspects of learning. Review of
Research in Education, 23(1), 1–24. https://doi.org/10.3102/0091732X023001001
125

REFERENCES

Samuels, E. (2015). How faculty understood their implementation of a cluster-hiring initiative. University of Michigan, Ann Arbor. https://deepblue.lib.umich.edu/handle/2027.42/113474
Sawyer, K. (2007). Group genius: the creative power of collaboration. Basic Books.
Schleicher, A. (2015). Why Rethinking the What of Education Matters So Much. In Fadel, C., Bialik,
M. & Trilling, B., Four-dimensional education: The competencies learners need to succeed (pp.
1–4) [Prologue]. Center for Curriculum Redesign.
Schmidt, M. (2017, July 3). Manufacturing’s maker movement revolution. https://www.aem.org/news/
manufacturings-maker-movement-revolution/
Schneider, W. J., & McGrew, K. S. (2012). The Cattell-Horn-Carroll model of intelligence. In D. Flanagan & P. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rded., pp. 99–144). Guilford.
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
Schön, D. A. (1987). Educating the reflective practitioner. Josey-Bass.
Schuler, D., De Cindio, F., & De Liddo, A. (2015, June). Encouraging collective intelligence for thecommon good: how do we integrate the disparate pieces? In Proceedings of the 7th International Conference on Communities and Technologies (pp. 157–159).
Schwab, K. (2016). The fourth industrial revolution. Crown Business.
Semel, M. (2019). Partnership power: Essential museum strategies for today’s networked world. Rowan & Littlefield.
Senge, P. (1990). The fifth discipline: The art & practice of the learning organization. Random House
Business.
Senge, P. M., Cambron-McCabe, N., Lucas, T., Smith, B., & Dutton, J. (2012). Schools that learn (updated and revised): A fifth discipline fieldbook for educators, parents, and everyone who cares
about education. Crown Business.
Sepkowitz, K. (2020). Why is Covid 19 death rate so low in Germany? CNN Opinion. https://www.
cnn.com/2020/03/24/opinions/germany-low-death-rate-for-coronavirus-sepkowitz/index.html
Shor, I., & Freire, P. (1987). A pedagogy for liberation: Dialogues on transforming education. Bergin& Garvey.
Shushok Jr, F., & Hulme, E. (2006). What’s right with you: Helping students find and use their personal
strengths. About Campus, 11(4), 2–8. https://doi.org/10.1002/abc.173
126

REFERENCES

Simon, H. A. (1957). Models of man: Social and rational. John Wiley and Sons, Inc.
Simonton, D. K. (2000). Creative development as acquired expertise: Theoretical issues and an empirical test. Developmental Review, 20(2), 283–318. https://doi.org/10.1006/drev.1999.0504
Snell, D., Gekara, V., & K. Gatt. (2016). Cross-occupational skill transferability: Challenges andopportunities in a changing economy. National Center for Vocational Education Research(NCVER). https://www.ncver.edu.au/research-and-statistics/publications/all-publications/cross-occupational-skill-transferability-challenges-and-opportunities-in-a-changing-economy
Spear, S. J. (2004). Learning to lead at Toyota. Harvard Business Review, 82(5), 78–86+151.
https://hbr.org/2004/05/learning-to-lead-at-toyota
Spence, M., & Hlatshwayo, S. (2012). The evolving structure of the American economy and the employment challenge. Comparative Economic Studies, 54(4), 703–738. https://doi.org/10.1057/
ces.2012.32
Spohrer, J. C. (2006). Services sciences, management, and engineering (SSME): An emerging multidiscipline. Proceedings of the frontiers in service conference. https://doi.org/10.1007/978-0-38776578-5
Starbucks. (2020). Future leaders start here. Careers. https://www.starbucks.com/careers/working-at-starbucks/education
Sternberg, R. J. (2006). Recognizing neglected strengths. Educational Leadership, 64(1), 30–35.
Szreter, S. (1999). A new political economy for Labour: The importance of social capital. Political
Economy Research Centre, University of Sheffield.
Tegarden, D. P., Tegarden, L. F., & Sheetz, S. D. (2009). Cognitive factions in a top management team:Surfacing and analyzing cognitive diversity using causal maps. Group Decision and Negotiation, 18(6), 537–566. https://doi.org/10.1007/s10726-007-9099-1
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331(6022), 1279–1285. https://doi.org/10.1126/science.1192788
Thibodeaux, W. (2018). AI is awesome, blockchain is a powerhouse. But here’s what combining them
could do. Inc.com. https://www.inc.com/wanda-thibodeaux/ai-is-awesome-blockchain-is-apowerhouse-but-heres-what-combining-them-could-do.html
Thornton, T. (2013). Clinical judgment, tacit knowledge, and recognition in psychiatric diagnosis. In
K. W. M. Fulford, M. Davies, R. G. T. Gipps, G. Graham, J. Z. Sadler, & G. Stanghellini (Eds.),
The Oxford handbook of philosophy and psychiatry. Oxford University Press.
127

REFERENCES

Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. John Wiley & Sons.
Tschannen-Moran, M., & Tschannen-Moran, B. (2011). Taking a strengths-based focus improves
school climate. Journal of School Leadership, 21, 422–448. https://doi.org/10.1177%
2F105268461102100305
Tsui, A. B. (2012). The dialectics of theory and practice in teacher knowledge development. In J.
Hüttner, B. Mehlmauer–Larcher, S. Reichl, & B.Schiftner (Eds.), Theory and practice in EFL
teacher education: Bridging the gap (pp. 16–37). Multilingual Matters.
U.S. Bureau of Labor. (2020, June 18). Unemployment insurance weekly claims report. Bureau of Labor Statistics. https://www.dol.gov/newsroom/releases/eta/eta20200618
UNESCO. (2000, April 26–28). The dakar framework for action: education for all—meeting our collective needs [paper]. World Education Forum, Dakar, Senegal.
UNESCO. (2019). Leave no one behind: Participation, equity and inclusion. UNESCO Institute forLifelong Learning.
United Nations. (2015). General assembly resolution 70/1. Transforming our world: the 2030 agenda
for sustainable development—A/RES/70/1. United Nations.
United Way of Southwest Virginia. (n.d.). Ignite tech talent development program. https://unitedwayswva.org/technology-talent-development-program/
University of Central Florida. (n.d. -a). Direct connect to UFC. https://directconnect.ucf.edu/
University of Central Florida. (n.d. -b). Orlando’s university. UCF downtown. https://www.ucf.edu/
downtown/
University of Detroit Mercy. (n.d.). Response to the U.S. Department of Education’s request for information about promising and practical strategies to increase postsecondary success: Modular
math at University of Detroit Mercy. www2.ed.gov/documents/college-completion/modular-math.doc
University of Waterloo. (n.d. -a) Co-op programs. Undergraduate programs. https://uwaterloo.ca/future-students/co-op
University of Waterloo. (n.d. -b) Steps to careers in health and medicine. Undergraduate programs.
https://uwaterloo.ca/future-students/careers-health
University of Waterloo. (2019). Our differentiators. https://uwaterloo.ca/about/differentiators

128

REFERENCES

Van Herwegen, J., Costa, H. M., Nicholson, B., & Donlan, C. (2018). Improving number abilities in
low achieving preschoolers: Symbolic versus non-symbolic training programs. Research indevelopmental disabilities, 77, 1–11. https://doi.org/10.1016/j.ridd.2018.03.011
Virginia Tech. (2017). The Myers-Lawson School of Construction. https://www.mlsoc.vt.edu/
Vygotsky, L. S. (1978). Mind in society. Harvard University Press.
Walsh, J. D. (2020, May 11). The coming disruption: Scott Galloway predicts a handful of elite cyborg
universities will soon monopolize higher education. Intelligencer. New York Magazine. https://nymag.com/intelligencer/2020/05/scott-galloway-future- of-college.html
Wan, C. Y., & Schlaug, G. (2010). Music making as a tool for promoting brain plasticity across the life
span. The Neuroscientist, 16(5), 566–577. https://doi.org/ 10.1177/1073858410377805
Wayne State University. (2019a). Lumina convening shines as Spotlight on Wayne State, Detroit. Today@Wayne. https://today.wayne.edu/news/2019/04/24/lumina-convening-shines-a-spotlighton-wayne-state-detroit-31628
Wayne State University. (2019b). Program partners. C2 Pipeline. https://c2pipeline.wayne.edu/ partners/program-partners
Weber, L. (2019). Why companies are failing at reskilling. The Wall Street Journal. https://www.
wsj.com/articles/the-answer-to-your-companys-hiring-problem -might-be-right-under-yournose-11555689542
Weise, M. R., Hanson, A. R., Salisbury, A. & Qu, K. (2019). On-ramps to good jobs: Fueling innovation for the learning ecosystem of the future. Strada Institute for the Future of Work and Entangled Solutions. https://go.stradaeducation.org/on-ramps
Weise, M. R., Hanson, A. R., Sentz, R., & Saleh, Y. (2018). Robot-ready: Human skills for the future ofwork. Strada Education Network. https://www.stradaeducation.org/press-release/robot-ready-labor-market-analysis-finds-human-skills-in-high-demand/
Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University
Press.
Wenger, E. (2000). Communities of practice and social learning systems. Organization, 7(2), 225.
https://doi.org/10.1177/135050840072002
Whitney, P. (2010). Learning in the creative economy. In D. Araya & M. A. Peters (Eds.), Educationin the creative economy: knowledge and learning in the age of innovation (pp. 448–467). Peter
Lange Publishing.
129

REFERENCES

Wilber, K., Patten, T., Leonard, A., & Morelli, M. (2012). Integral life practice: A 21st century blueprint for physical health, emotional balance, mental clarity, and spiritual awakening. Shambhala Publications.
Wolff, R.D., & Resnick, S.A. (2012). Contending economic theories: neoclassical, keynesian, andmarxian. The MIT Press.
Woolfolk, A. W., & Margetts, K. (2013). Educational psychology (3rd ed.). Pearson Australia.
World Data Lab. (2019). World poverty clock. http://worldpoverty.io/
World Economic Forum. (1990). The world competitiveness report. World Economic Forum.
World Economic Forum. (2016). The future of jobs: Employment, skills and workforce strategy for the
fourth industrial revolution. World Economic Forum.
World Economic Forum. (2017). Accelerating workforce reskilling for the Fourth industrial revolution:
An agenda for leaders to shape the future of education, gender and work. World Economic
Forum.
World Economic Forum & Boston Consulting Group (BCG). (2018). Towards a reskilling revolution: A
future of jobs for all. World Economic Forum.
Xenakis, I. (1971). Formalized music: thought and mathematics in composition. Indiana University
Press.
Zarya, V. (2017). What do 65% of the most powerful women have in common? Sports. Fortune. https://
fortune.com/2017/09/22/powerful-women-business-sports/
Zucker, L., & Hicks, T. (2019). Alternative assessments, unintended consequences: The promise andperil of digital badges. Transformations: The Journal of Inclusive Scholarship and Pedagogy,
29(1), 113–123. https://doi.org/10.1353/tnf.2019.0008

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Other Image Credits
Appendix Figures A1 and A2 by Emily Harmon and Shahab Sagheb

Photo Credits
Executive Summary photo by Boeing
Introduction photo by Thinkabit Lab, Virginia Tech
Chapter I photo by Calhoun Discovery Program, Virginia Tech
Chapter II photo by Erica Corder for Virginia Tech
Chapter III photo by Pixabay
Chapter IV photo by Calhoun Discovery Program, Virginia TechWorking Groups photo by Erin Williams for Virginia Tech
Appendix A photo by Calhoun Discovery Program, Virginia Tech
References photo by Calhoun Discovery Program, Virginia Tech

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The Calhoun Center for Higher Education Innovation
Virginia Tech Publishing
The International Academic Forum
Future Talent Council

DOI: https://doi.org/10.21061/
adaptive-learning-report