Symposium and Workshops

The Challenge of Demographic Change
Sustainable Life-Long Learning and Digital Media

Symposium
OKAMOTO Toshio: Introduction to the Symposium: The Challenge of
Demographic Change – Sustainable Life-Long Learning and Digital Media(ppt-presentation)
SAITO Haruka: Education and ICT in Japan from the Perspective of Life-long
Learning Policy (ppt-presentation)
Christian WILK: Technology Enhanced Learning – Change of European Research
Perspectiv (ppt-presentation)
Nicolas APOSTOLOPOULOS: E-Learning Support-Structures in Traditional
Universities (ppt-presentation)
NISHINOSONO Haruo: Sustainable Life-Long Learning at the Kyoto School ofProfessional Learning (ppt-presentation)
OKAMOTO Toshio: The Organizational Knowledge Circulated Management Systemon e-Learning and Human Development (ppt-presentation)
Klaus TOCHTERMANN: The Role of Knowledge Transfer in the Future Internet(ppt-presentation)Workshop 1
OKAMOTO Toshio: Introduction to the Workshop: Comprehensive Learning
Interactive and Group Acitivities as New Ways of Learning (pptpresentation)
HONDA Toshiaki: Web Based Learning Ecology (WBLE): Suggestion to ePedagogy(ppt-presentation)(HONDA Toshiaki: abstract)
Denis HELIC: Adapting Web 2.0 Technology in Online Learning: Challenges andExperiences (abstract)

Joachim NIEMEIER: Freeform eLearning – Approach and Building Blocks (pptpresentation)
NAGATA Naomi: The Quality Assurance Related to e-Learning Contents andLearning Design (ppt-presentation)(NAGATA Naomi: abstract)
KASHIHARA Akihiro, NAGATOME Keisuke and HASEGAWA Shinobu: Hyperblog
for Sharing and Inheriting Kowledge from Research Activities (pptpresentation)(KASHIHARA Akihiro: abstract)
Herbert MÜLLER PHILIPPS SOHN: Social Situation and Demand for Further
Education. Requirements for eLearning Systems (ppt-presentation)
Ralf KLAMMA: Virtual Campfire – Digital Media Discourses between Cultures,
Continents and Generations (ppt-presentation)
WARAGAI Ikumi and OHTA Tasuya: Digital Media and Foreign Language Learning(abstract)
HAYASHI Yuki, KOJIRI Tomoko and WATANABE Toyohide: Interaction-Oriented
CSCL Environment Based on Focusing Intentions of Learners (pptpresentation)(HAYASHI Yuki: abstract)
Aljoscha BURCHARDT: From Learning in the Net to Learning Networks (pptpresentation)(Aljoscha BURCHARDT: abstract)
Workshop 2
NAGAOKA Keizo: What Capabilities Are Emerging Among the Next Generation?
Based on a Comparative Survey of Japan and South Korea (pptpresentation)(NAGAOKA Keizo: abstract)
Ingo DAHN: Lifelong and Lifewide eLearning – Fire Fighters and Forest Rangers inRhineland-Palatinate (ppt-presentation)(Ingo DAHN: abstract)
KAYAMA Mizue, NAGAI Takashi, and ITOH Kazunori: A Basic Study on a DrawingSkill Learning Support System (ppt-presentation)(KAYAMA Mizue: abstract)Hermann KÖRNDLE, Felix KAPP, Susanne NARCISS, Antje PROSKE: Supporting
Self-Regulated Learning of Scientific Concepts through Interactive
Learning Tasks – Product and Process Findings (ppt-presentation)
Maria BANNERT: Promoting Self-Regulated eLearning through Prompts (pptpresentation)(Maria BANNERT: abstract)
MATSUI Tatsunori, HORIGUCHI Yuki and KOJI Kazuaki: A Study for Explorationof Relationships between Behaviors and Mental States of Learners for an
Automatic Estimation System (ppt-presentation)(MATSUI Tatsunori: abstract)
Dietrich ALBERT: The Concepts of Competences and Self-Regulation in TeacherTraining and Life Long Learning (abstract)
Bastian BENZ und Berhard SCHMITZ: Scaffolding Self-Regulated Learning on theWorld Wide Web (ppt-presentation)(Bastian BENZ: abstract)
Cord HOCKEMEYER: Multi-Modal Competence Assessment Based on Users’
Performance on Complex Tasks (ppt-presentation)(Cord HOCKEMEYER: abstract)
NAKABAYASHI Kiyoshi: Practices of Technology Supported Learning in JapaneseIndustry – From the Activities of e-Learning Cosortium Japan (pptpresentation)
Martin WOLPERS: Personalized Learning Environments – Today and in the Future(ppt-presentation)(Martin WOLPERS: abstract)
Program of the Symposium
List of AuthorsEinführung
The Joint Symposium & Workshop Between Germany & Japan
10-11 September,2009
in BERLIN
at the JDZBThe Challenge of Demographic Change Sustainable life-long Learning and Digital Media
Greeting & Rationale
Toshio Okamoto
University of Electro-Communications, Tokyo

The principles of e-Pedagogy
from Social computing
Demand Driven
Social Activity and Identity
One Top Access to Real World and Data
Constructional Conjunction for Semantics
and Concept by Interactive activity

Autonomous Functionality
Cubic Model ofγ

Teacher’s Eye
ＩCT utilization
Investigation
Analysis
Design & Integration
Evaluating
Documenting & Reporting

Pedagogic Power

Shape：Teaching Style andBeliefCapacity：Degree ofExpertise and Learning
Resources
Coordinates：Social Identity

αLearner’s Eye
Significance of Learning
Readiness
Confirmed
Needs & MotivationβAcademic
Learning Style

Attainment
Social Identity and Contributions
α：Basic Competency
β：Balance
γ：Establishing Independence

Situational Eye
Respect, Pride & ShameContributions & Responsibility
Social Context

The Conditions of Learning
Organization
Learning
Competitive
Advantage
Sustainable
Stock & Reuse

META-data
LOG-data

nowledge Mining*Student Model*Diagnose Progress*Perturbation

How
What

Who

KNOW

Why
Who guarantees it

If

Where
When

Thank you very much

Education and ICT in Japan
from the Perspective ofLife-long Learning Policy
Haruka SAITO
Director, Educational Media and Information Policy Division,
Life-long Learning Policy Bureau,
Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan
Japanese-German Center Berlin
September 10, 2009

1. Introduction
2. School Education and ICT
2.1 Primary and Secondary School Stage
2.2 Higher Learning Stage

3. Social Education (Education Outside of Schools) and ICT
3.1 Support for a Life-long Learning Platform that Utilizes ICT
3.2 El-net
3.3 Providing Opportunities for Learning through Media

4. Education for Information Morals/Ethics
5. Conclusion

Actual and Projected Population of Japan
Japan’s population is decreasing. The low birthrate and longevity continue unabated.

The total population in 2005 was 127 million. In 50 years （2055), it will be 90 million. The population of children (agedunder 15) will be 7.5 million ( 8.4% of the total population); the working-age population (15~64 ) will be 46 million (51.1%of the total population); and the aged population (65 and over) will be 36 million ( 40.5% of the total population).
Population Trends of Japan（Projected in December of 2006 : Medium Variant）
Unit：thousands
Dotted lines represent previous
projection in January of 2002

Working-age population（ 15～64 ）ActualProjected

Elderly population（aged 65 and over）
Child population（aged under15）

Source: National Institute of Population and Social Security Research, “Actual and Projected Population of Japan ”

1Process behind Japan’s IT Strategy◆ Basic Law on the Formation of an Advanced Information and Telecommunications
Network Society (Jan 2001)◆ Establishment of the IT Strategic Headquarters (Jan 2001)(Director-General : Prime Minister Members : Ministers and Experts ）ｉ－Japan Strategy2015(Jul 2009)
New IT Reform Strategy( Jan 2006)
e-Japan Strategy Ⅱ(Jul 2003)
e-Japan Strategy(Jan 2001)

2001

2003

200６

200９

～

2

School ICT Installation and UseTime of researchStudent-computer
ratio

JAPAN

U.S.A.

U.K.

Republic of Korea

March of 2009

Autumn of 2005

June of 2008

April of 2008

8.7 : 1
6.8 : 1
5.2 : 1
7.2 : 1

primary school

58.4%
lower secondary school 60.7%
upper secondary school 87.2%
overall
64.0%

primary school（over 30Mbps）（over 1.5Ｍbps）

60.2%
lower secondary school 61.7%
upper secondary school 59.6%
overall
60.5%

primary school

primary school
lower secondary school
upper secondary schooloverall

Percentage ofschools connectedto school LANS

Ultra high-speed
Internetconnectivity rate

Source:primary school

primary school

secondary schooloverall

4.1 : 1
3.3 : 1
3.8 : 1

primary school
secondary school

6.25 : 1
3.6 : 1secondary schooloveralloverall100%

lower secondary school
upper secondary school

as of Jan. 2008

93%
95%
94%

overall

6.2 : 1
6.0 : 14.1 : 1
5.4 : 1

primary school

primary school
secondary school

85%
92%

as of Dec. 2005
※percentage of computers thatconnect to the internet

secondary schooloverall

Mean speed

97 %
99 %
97 %

primary school
secondary school（over 2Mbps）

3.2 Mbps
15.7 Mbps（U.S.A） U.S. Department of Education (Nov.2006) : Internet Access in U.S. Public Schools and Classrooms：1994- 2005.
（U.K.） Harnessing technology : school survey 2008
BESA Information and Communication Technology in UK State Schools October 2008 Summary Report（Korea） Ministry of Education and Human Resources Development : Education in Korea 2007~2008
Ministry of Education , Science and Technology & KEDI : Brief Statistics on Korea Education 200897％

as of Dec. 2005

3

ICT Environment in Primary/Secondary Education in Japan
Target of ‘New IT Reform Strategy’ and‘i-Japan Strategy 2015’ (~ March of 2011)

Mar 2009

Student-computer
ratio

primary school
lower secondary school
upper secondary schooloverall

8.7 ： １
6.8 ： １
5.2 ： １
7.2 ： １

3.6 ： １

Computers
available forschool duty/affair

primary school
lower secondary school
upper secondary schooloverall

55.8%
56.2%
85.3%
61.6%

1 teacher : 1 computer

Percentage
of schools
connected toschool LANS

primary school
lower secondary school
upper secondary schooloverall

58.4%
60.7%
87.2%
64.0%

Ultra high-speed
internetconnectivity rate

Approximately 100％（over 30Mbps)

primary school
lower secondary school
upper secondary schooloverall

60.2%
61.7%
59.6%
60.5 %（over 30Mbps)

Approximately 100％

4Comparative Study of the Effects of ICT in Classes (based on objective tests)

76.2
82.1

primary school:mathprimary school:social
studies

66.6
73.3

primaryschool:science

82.1
86.8

lower secondary
school:math

72.9
78.8

lower secondary
school:social studies

did not use ICT
used ICT

unit: point

61.4
0

20

40

60

71.9
80

100

Results of objective tests that were conducted after classes demonstrate the effectiveness of ICT
in the following areas: “skills & presentation (e.g., arithmetic)” and “knowledge & comprehension(e.g., the growth of butterflies , the structure of society)”
Number of subjects : 2,991
Source: National Institute of Multimedia Education, “Research on the Effects of Classes Utilizing ICT Utilization to Foster Academic Ability” (March, 2006)

5

An Electronic Blackboard in Use in the Classroom

6

Revisions to the Course of Study(March of 2008 & March of 2009)
Education for information-utilization is extremely important to a child’s developmentfrom the standpoint of “thriving in an environment of life-long learning”

e.g. : Requirement for Elementary School• Teaching basic computer operation• Utilizing ICT in classes for various subjects• Teaching information morals during Ethics classes

7

NICER（National Information Center for Educational Resources ）For further information, pls. visit:
http://www.nicer.go.jp

8Percentage of Departments & Research Coursesthat Utilize ICT for Remote Education over the Internet
FY2006

FY2007

FY2008

3,570

3,669

3,778

Departments & researches courses that utilize
ICT for remote education over the internet

589

669

853

Percentages

16.5％

18.2％

22.6％

All departments & research courses

Number of Universities that Utilize Remote Education
Implemented by Domestic/Foreign Universities
FY2006

FY2007915

910

Number of universities that utilize remote education
implemented by domestic/foreign universities

109（11.9%）

126（13.8%）

Number of universities that utilize internet, etc. forthe above-mentioned purpose

82（9.0%）

103(11.3%)

Number of responses of higher learning

Source: National Institute of Multimedia Education : Report on education using ICT including e-Learning

9

The Open University of Japan

Age
Students of the Faculty of Liberal Arts
（as of 2nd semester, 2008）

Occupation
Alumni of the Faculty of Liberal Arts
（as of March, 2008）

http://www.u-air.ac.jp/eng/index.html
10Life-long Learning ICT Platform (Toyama Internet School for Citizens)
Participating Operation, Using as User
Local
Government

Citizens’
Teacher

Corporate ＮＰＯ etc
University Corporation

Family School

Language School

Participants

Media School Business School
Hometown School Entrepreneur Training
Life Up School

ＩＴ Supporter

Screening, Experience,Local activity

11

El-net: Education and Learning Network
MEXT delivers educational content over the internet. El-net makes learning possible regardless of location, solong as one connects to the internet. A diverse range of educational content is delivered over channels 1 through10.
10 channels
１ch From MEXT
２ch NEW!
３ch For Children
４ch Extension Courses
５ch Science Channels
６ch Events
７ch Symposium on Science and Technology
８ch Contests, etc.
９ch Information Morals/Ethics
10ch Digital Content

Visit: http://www.elnet.go.jp
12Education for Information Morals/Ethics
Revised the Course of Study
Opened the Information Morals
Portal Site
(http://kayoo.info/moral-guidebook-2007/index.html)
e-Net Caravane-Net Caravan(http://www.e-netcaravan.jp/)(workshops for parents, teachers, and other child-care professionals
on ways to guide children in safe ways of utilizing the internet andcell phones)

13

Conclusion
MEXT aims for the realization of a society abundant in opportunities for life-long learning.
For this purpose, ICT plays a critical role through both school and social education.
ICT shows considerable success in enhancing academic performance in schools,
and providing learning opportunities in social education.
Diffusion and upgrading of the school ICT environment, the acquisition of computer skills,
the cultivation of instructors’ teaching abilities, etc. are important.
Consideration of positive and negative aspects of ICT is imperative for the attainment ofa sustainable life-long learning system.

14

Technology Enhanced Learning – Changeof European Research Perspective

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

ICT for Education and Training:major initiatives at EU level
Policy Areasi2010, The European Qualifications Framework, e-Skills …

Financial Instruments

Lifelong Learning Programme (€7bn)
FP7 7th Research Framework Programme (€9bn ICT)

Research and Technological development:
Technology-enhanced learning

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

Unit E.3•

Unit E.3 manages the funding of research projects underFP7, programme Information and Communication
Technologies (ICT). 'Technology-enhanced learning' is
one objective (4.2) under Challenge 4 “Digital libraries
and content”••

Call 1: 6 TEL Projects (started 02-04/2008),
Call 3: 7 TEL Projects (currently in contract
preparation phase)
FP6, 32 TEL Projects (some will run until 2010)•

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

What we mean by
Technology Enhanced Learning•

TEL is about– studying how technologies improve the way
individuals, organisations and communities learn– how we apply the acquired knowledge to oursituations, to solve our problems and challenges•

The overall aim is to increase learning efficacy and tocreate a body of evidence as to which approach works,
under which circumstances

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

Context of Objective 4.2
Technology Enhanced Learning• Knowledge Society: The changing
nature of our society and the way we dobusiness• Modes of interaction: The way we willlearn and the way we will experience lifein the future• Requirements: The skills and knowledge
needed to operate in very different
environments
Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum BerlinRationale• Overall– Meeting the Demands of Education in 21st Century – Contributing to fight learning disengagement (e.g.
science, math)– Learning and Innovation, Creativity, Productivity– Foster Competitiveness of European Players• Research– From research to innovation: Support for technology
transfer and take-up– Validation – showcasing, best practices– Mobilising a more extended research community– Overcoming barriers for new entrants
Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum BerlinKey Elements of the Work Programme
2009-2010
1. Learning in the 21st Century
2. Reinforce Links between Individual and Organisational
Learning
3. Adaptive and Intuitive Systems
4. Revolutionary Learning Appliances, including Toys
5. Interdisciplinary Networks
6. Awareness building and Knowledge Management

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

a) Learning in the 21st Century• Topics– Future Classroom– Individualization and Collaboration– Foster Creativity and Expressiveness– Increasingly active, reflective & independent learning
activities• Research– Innovation in Learning and Teaching– Take change processes into account– Relevant new summative and formative assessment
methods
Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlinb) Links between individual andorganisational learning– Embedding learning experiences in organisational
processes and practices– Solutions which cover talent, knowledge, workflow,
collaborative innovation and competence
management– Effectiveness of learning content– New forms of collective intelligence– Deepened understanding of the role of ICT for
creativity, informal learning and collaboration

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlinc) Adaptive and Intuitive
Systems for Learning– New forms of assessing learning outcomes– Feedback and guidance mechanisms (innovative
diagnostic techniques)– Advances in the combination of simulation, story
telling and collaborative learning– May relate to serious games and immersive
environments

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlind) Revolutionary Learning
Appliances, incl. toys
– Promote specific cognitive processes or abilities– Address specific social and learning problems– In the field of science, technology and mathematics– Or specific tasks that impose high cognitive
demands

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

e) Interdisciplinary Networks– On specific emerging trends (e.g. serious games,
mobility and learning, sense making)– Linking established excellences and learning labs
– Using appropriate mechanisms for cross-fertilisation
between disciplines– Should leverage national research activities– Achieve demonstrable visibility at international level

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlinf) Awareness building andknowledge management– On results of EU RTD projects in the field– Exploratory and road-mapping activities for
fundamentally new forms of learning– Identification of Grand Challenges– Socio-economic evaluations– Establishment of a pan-European network of living
schools for validations, demonstrations andshowcases

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum Berlin

Contacts andfurther information
DG INFSO Unit E3
Cultural Heritage and Technology
Enhanced Learning
FP7: http://cordis.europa.eu/fp7/ict/telearn-digicult/Technology-enhanced learning
infso-telearn@ec.europa.eu

Die Herausforderung des demografischen Wandels – Nachhaltiges lebenslanges Lernen und digitale Medien
10. Und 11. September 2009 – Japanisch Deutsches Zentrum BerlinE-LEARNING SUPPORT STRUCTURESIN TRADITIONAL UNIVERSITIES

Prof. Dr. Nicolas Apostolopoulos
Freie Universität Berlin
Center for Digital Systems

The Freie Universität Berlin (FU)E-Learning Support Structures2

FU facts and figures*
34,000 students, 60% women, 16% international• 400 professors• 1,700 academic staff, 40% research funded• 2,200 additional staff• 12 departments, including the Charité• State budget: 290 million euros p.a.
• Third-party funding: 60 million euros p.a.
• Excellence Initiative: 150 M€ (for five years)•* Figures exclude human medicine (Charité)
E-Learning Support Structures3

About Learning and Technologies

What isTEL?
A phone?

E-Learning Support Structures5

About Learning and Technologies

What isTEL?
A Telecom Company?

E-Learning Support Structures6

About Learning and Technologies

What isTEL?
An acronym for„Technology Enhanced
Learning“?

E-Learning Support Structures

7

Excellence at Universities

Teaching

Learning

Research

Gerhard Casper, former President Stanford University
E-Learning Support Structures8

About lifelong learning …

E-Learning Support Structures9FIT: IT at the Freie Universität
President‘s
Office
StC eL

CIO

FIT
CeDiS

Admin
IT

DigitalLibrary

Data
Center

IT-Security
IT-Plenum

Data Security
Employee
Representatives

Decentralized
IT-Units
Departments

E-Learning Support Structures

CentralInstitutes

CentralServices

CentralAdministration

Other
Divisions

10

FIT Strategic Alliance

CIO

eAS

E-Learning Support Structures

11

CeDiS – Structure

Media
and Design
Internet
Technology

E-Learning Support Structures12

Outline I
I.
II.
III.
IV.
V.
VI.
VII.

First steps in e-Learning
e-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Open issues

E-Learning Support Structures

15

Multimedia “made simple“

E-Learning Support Structures

16

The DIALECT Model

Computer
Navigation
Hyperlinks

Basics

TheoryExpertInterviews

STORY
ModelsMotivation/
Didactics

Practice
Case studies
Simulation

Literature

Internet/
SearchVisualization
Simulation

Computer

E-Learning Support Structures18

Outline II
I.
II.
III.
IV.
V.
VI.
VII.

e-Learning as an experimente-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Open issues

E-Learning Support Structures

19

BMBF Project New Statistics
13 Departments at 10 German Universities

E-Learning Support Structures-

European-University ViadrinaFrankfurt/Oder-

University of Applied Sciences Cologne-

University Hagen-

Free University Berlin-

Friedrich-Alexander University
Erlangen-Nuremberg-

Humboldt University Berlin-

University of Bielefeld-

University of Bremen-

University of Hamburg-

University of Konstanz-

Virtual University of Applied Sciences20„Traditional“ versus „New Statistics“

Statistics: yesterday and today

E-Learning Support Structures

Statistics: today and tomorrow

21

New Statistics: Multimedia Learning Environment

Animations

Learning Modules
Case studies

Statistical Lab

Java-Applets
Exams
Exercises
E-Learning Support Structures

22

Manufacturing Learning Modules
examineexplainGlossary, Bibliography

Editing
Repository (SCORM)
WWW

LMS
uploaduploadtransform

XML

XML

XML

XML

XSLT
learning module (HTML)previewlearning module (XML)exportrequestintegrate

Media Production
E-Learning Support Structures

Learning Module
Learning Module
EditorAuthor 2
Author 3
EditorAuthor

XMetaL25

Economics of E-LearningIt‘s the Economy, Stupid …

E-Learning Support Structures27

Outline III
I.
II.
III.
IV.
V.
VI.
VII.

e-Learning as an experimente-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Open issues

E-Learning Support Structures28

Vision: Is e-Learning easy to do!?

Source: www.uni-potsdam.de/agelearning/
E-Learning Support Structures29

e-Learning Environments“Not now honey,I‘m learning
online.”A significant advantage of e-Learning is the creation ofindividualized learning environments.....
Source: www.open-academy.com/de/elearning/lernende_/index.html
E-Learning Support Structures30

e-Learning everywhere?

E-Learning Support Structures31

Digital Technology in Education: Future Vision…

re
u
t n
u
F sio
Vi

FutureVisionE-Learning Support Structures

32

Digital Technology and the Reality

E-Learning Support Structures33

Outline IV
I.
II.
III.
IV.
V.
VI.
VII.

e-Learning as an experimente-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Unresolved issues

E-Learning Support Structures

34

Media and Design

Media & Design

E-Learning Support Structures

35

CeDiS – CMS

Content
Management
SystemCMS

E-Learning Support Structures

37

CeDiS - LMS

Learning
Management
SystemLMS

E-Learning Support Structures

39

LMS – a Central Learning Platform for TeachingStudent Access to the Central LMS

Team work

Community

University
Library

Learning
Materials
ForumsCourseExam

Self-tests

CourseEvaluation
Chat

CourseCourseCatalog

Information

Central Entry
Point

! ! !
E-Learning Support Structures40

FU e-Learning Grants

FU e-Learning Grants

E-Learning Support Structures42

FU e-Learning Grants - Growth

StC eL

Multiplicator effectFinancial Support

Know-How

Project 1

Project 2

Project 1

Project 2

Project

Project n

Project n

Project

Project

Freie Universität Departments

E-Learning Support Structures43

FU e-Learning Grant Program – Workflow
StC eL

Instructor
Application

Application

submission

Application

decisionrecommendation+ -advicee-Learning Projectis growing

Know-how

E-Learning Support Structures

Grant

44

FU-wide e-Learning Dissemination
FU Berlin

President’s
Office

CI
dep

DEP

Project

DEP

Project

StC eLCI

dep
Project

CI

dep

CI

DEP

Project

dep

Project

DEP

Project

Project

Project

CI

Project

ProvostProject

DEP

DEP

Project

Project

Project

DEP

CI

Project

dep

DEP

Project

Project

CIO

E-Learning Support Structures

dep

DEP

Project

dep

DEP

Dean

Project

Project

Project

dep

DEP

dep
CI

CI

dep

dep

dep

DEP

Project

Project

CeDiS

45

Advancing e-Learning

The project FUeL
(FU e-Learning)

E-Learning Support Structures50

Establishing Blended Learning

Local Structuresand ExpertiseInterdisciplinary
Working Groups

FUeL Strategy
CentralServices

E-Learning Support Structures

e-Learning
Funding Program

Departments
Central Institutes
Continuing Education

Evaluation52

e-Learning Consulting

Central LMS
Blackboard

Content
creation

Supporte-Learning adviser
one regular contact personfor each department andeach teacher

Teachers

Kooperation
Co-operation
Deans

Funding
Program(Media-)Didactics…

E-Learning Support Structures

53

From the Traditional Classroom to Blended Learning
OnlineClassroom
Lectures
Exercises

Courses
Tutorium

Literature
Internship

Online Surveys
Multimedia

E-MailChat

Digital Materials

ForumsSelf-tests
Lectures

Blended Learning

Lectures

Lectures

LecturesMultimediamaterial
Tutorials

Tutorials

Librarye-MailWithout LMS

Informations

Library
Informations

Materialcollection

Materialcollection

Blended Learning I»Introduction«

Blended Learning II»Extended«

E-Learning Support Structures

Exam
preparation
Tutorials

Tutorials
e-TutorLibrary

Lecturese-TutorLibrary
Informations

Multimediamaterial
Exam
preparation
Tutorials
e-TutorLibrary
Informations

Materialcollection

Materialcollection

Blended Learning III»Maximum«Online-Courses
54

1.3 Bereich E-Learning
Degree of Utilization
19633
18496
16172

18147

16535

12162
9935

5284

1621

1679

1730

1359
1245

2865

870

700

Students (in 100)

Co urs es

535
290

23

145

Summe rWi nt e r

Summe rWi nt e r

Summe rWi nt e r

Summe rWi nt e r

Summe rSumme r04

0 4/ 05

05

0 5/ 0 6

06

06/ 0 707

07/ 0 808

09

E-Learning Support Structures55

IT-Integration

Integrating the Central LMS
with the IT-Infrastructure of
the FU Berlin

E-Learning Support Structures56

IT-Integration
FUDIS

SAP/CM

FU Identity andDirectory Service- student records- teacher records- authentication

Campus Management- courses- course participants- marks, credits
Admin ITStreaming
ServerCentralLearning
Management
SystemBlackboard

ALEPH, Metalib

CeDiS- video- audio

Data Center- online-Catalogue- digital Media

CeDiS

Library

Central Content
Zentrales CMS
Management
Systemin usein development- Lernmaterial
Infopark
NPS- learning materials

CeDiS

planning stage
E-Learning Support Structures57

Outline V
I.
II.
III.
IV.
V.
VI.
VII.

e-Learning as an experimente-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Unresolved issues

E-Learning Support Structures58

Student Portal

Personalized Informationand Services for Students

E-Learning Support Structures

59

For Students…

E-Learning Support Structures60

Student Portal
Material Exchange Marketplace?

?
?

Exchange Marketplace

E-Learning Support Structures

62

“Web 2.0” / Social Software
CeDiS Blog Services
Blog availability- personal blog for all FU members- (multi-user) blog for Blackboard courses- Selected System: WordPress

CeDiS Wiki, RSS Services
Wiki availability- Wikis for all FU members- Wikis for Blackboard courses- Selected System: Confluence

RSS feeds- Announcements from Blackboard courses(Podcasts, Social Bookmarking, ...)
E-Learning Support Structures65

Outline VI
I.
II.
III.
IV.
V.
VI.
VII.

e-Learning as an experimente-Learning Engineering
e-Learning at a traditional University
Coordinated action plan
The Web 2.0 Initiative
Lessons learned
Open issues

E-Learning Support Structures

68Digital Technology in Education: Involve…
… »computer specific« features (storing, searching, calculating)… visualization techniques… media enriched contents… extensive use of tutorials & help functions… multiple navigation and tracking… instructor’s »presence«… problem based approach… »real« AND virtual (i.e. hybrid) reality… extensive personalization… common sense intelligence (things that teach)?
… user controlled privacy and security!
… »Create humane applications«

E-Learning Support Structures69

Digital Technology in Education: Avoid …
… new incomplete systems… additional complexity… incompatible environments… slow responding applications… poor design… poor interaction… »surprising« features… »faked« security… poor personalization

E-Learning Support Structures70e-Learning lessons – Summary-

e-Learning is a long-term project
Executive support is necessaryCompetence Center
Close cooperation with the departments
Decentralize know how
Stepwise Migration
Offer grants and incentives
Central LMS leads to high synergy effects
Open content and commercial content helps saving costs
Multimedia authoring is challenging
Reuse of learning modules is ...
Reduce technical complexity (KIS)

E-Learning Support Structures71

Nicolas Apostolopoulos
napo@cedis.fu-berlin.dewww.cedis.fu-berlin.dewww.e-learning.fu-berlin.deNachhaltiges Lebenslanges Lernen an der
Kyoto School of Professional Learning
における持続可能な生涯教育

Pro. em. Haruo NISHINOSONO
Kyoto University of Education
Institute of Learning Development

The present policy of higher education in Japany The International Covenant on Economic, Social

and Cultural Rights, which was approved andsigned by the Japanese Government in 1979,y It recognises the right of everyone to an education,and calls for the provision of free, universal
education, including equal access to higher
education.
y The Japanese government has reserved the right todefer implementation of article 13 2(c) supporting
free higher education due to the importance of thenumerous private universities nationwide.
y Tuition fees have skyrocketed since the 1970s andwe have been unable to stop their rise or to develop
an appropriate higher education system that will
foster sustainable life-long learning.

Thousand yen

Tuition fee of Japanese Universities

Investment to“New Professional Human Capital”
The third component is defined as consisting of
the following groups of people:
y Unemployed and their families
y Households receiving welfare benefits
y Lowest-income households
y Immigrant workers and their families

Three components of KSPLK yoto S chool of Professional Lea rning (K SPL)

Learning Management
Learning developers,
Learning supporters/
mentors

Development

S teering Com mittee:
Learners, citizens,enterprises, unions

N ew Professional
H uma n Ca pital：
Unemployed peoples,
Protected households ofreceiving welfare check,
Lowest income households,
Immigrant workers

NPO
Knowledge network of
Stakeholders,E xperts in enterprises

NPO
Institute of Learning
Development

Foundation
Financial organization forsupporting KSPLManagement;
Public investment,
Donation from Citizens

Supports from concerned enterprises andtraining institutes
Concerned
enterprises

Concerned
enterprises

Training
institutes

Training
institutes

Number of the unemployed
Ten thousands

Data from Ministryof Health, Laborand WelfareRatio of Unemployment
Percent

Data from Ministryof Health, Laborand WelfareNumber of protected families
Ten thousands

Ratio ofprotection

Number ofprotected families

Data from
Honkawa Data
TribuneThousand yen

Immigrant workers
Ten thousands
Estimation of the Ministryof Health, Labors andWelfareIncluding illegal
workers

Legal workers

Data from
Honkawa Data
TribuneA
Ｂ
ＣD
Ａ：To maintain the present policy
Ｂ：To maintain the present fee and enhance scholarship programs
Ｃ：To maintain the present scholarship programs, but decrease the tuition
fee
Ｄ：To start zero and plan a new higher education system based on nonformal learning for professional development
Ｅ：Another plan
Education At a GlanceConventional Educational System
Non-formal learning

Formal learning

Schools & Colleges

Informal learning

Learning activities out of schools

Ubiquitous learning in daily life
How can we design, evaluate and manage ubiquitous learning?

Ubiquitous
ICTFirstphase

Autonomous
learning and Support

Process of Learning
Dependence andInstruction

Norms
克 of
Team learning
Respect

Responsibilirty

Autonomy

Right
to learn

心
Contribution

Collaboration 己

Firstphase

Leaning Activities, Contents and Outcomes
Learning Outcomes
Learning Contents

Learning Activities

Cam
pus

First
phase

Collaborative and Autonomous Learning

Competence
Learning outcomes and competence
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Ｕｎｉｔ

Ｕｎｉｔ

Ｕｎｉｔ

Ｕｎｉｔ

Ｕｎｉｔ

Ｕｎｉｔ

Ｕｎｉｔ ９Ｕｎｉｔ ８

Ｕｎｉｔ ７

Ｕｎｉｔ ６

Ｕｎｉｔ ５

Ｕｎｉｔ ４

Ｕｎｉｔ ３

Ｕｎｉｔ ２

Ｕｎｉｔ １

Collaborative andAutonomous Learning

Learning of Authentic Themes

10

11

12

13

14

15

Prepared learning resources
Various reference materials, local by available resources
and Web-based knowledge

Theme: To design
a virtual school Survey Informa t io nbyand develop a students
lesson plan forStudents’
this school

awarenessof problems

Secondphase
Teamdiscussion

Information

Gatheringof
information

Team
presentation
ReportInterimPresentation

Final
Presentation

i on
s
s
i
m
b
Su

Credits

Theme: To design
a virtual school Survey Informa t io nbyand develop a students
lesson plan forStudents’
this school

awarenessof problems

Secondphase
Teamdiscussion

Information

Gatheringof
information

Team
presentation
ReportIndividual learning
Presenin a teamtation

i on
s
s
i
m
b
Su

Credits

Submission
Final
Learning Outcomes presentation

Mutual assessment
and self-evaluation

Interimpresentation
Vectoradjustment
Ice breaking

Autonomous learning
Collaborative learning

Secondphase

Image of Learning Activities

Introductory course of
Instructional Method
Spring semester in 2004
Spring semester in 2005
Autumn semester in 2005

Number of students
228
276
181

y Instructor: Haruo NISHINOSONOyBukkyo University
y Teaching assistant: Shiho Mochizuki

他の学生は図書館や学習室で作業Growth after
one cycle

Third
phase
Personalpedagogicalknowledge
Analysis and intersubjective
interpretation

Metaphor

Pedagogicalactions

Images

Propositional
attitudeModels
Propositions/Empirical laws

Thirdphase

Growth after
one cycle
Personalpedagogicalknowledge

Sharingvisions

Analysis andinterpretation

Metaphor

Planning

Interpretationand learning

Image

Pedagogicalactions

Model
Meeting fordesignEmpirical
laws

Propositional
attitudeAutonomous
preparation

ProposalRole assignmentand briefing

Collaborative
learning
Agreement

Autonomous
learningMACETO Model for Learning Design
Internal
conditions
Meaning

Actions

Learning

Outcomes

Content

Environment

Tools
External
conditions

LearningTechnology

Metaphor: Medical Treatment
and Pharmacy
CS

LD

CS

Subject Matter Specialist

LD Learning Developer
LO Learning Objects
Mt Mentor, Learning GuideLO

TA Technical Assistant
L

L

L
L

L

Learner

Instruction
Mt

TAManagement of
Collaborativeand Autonomous Learning

Two types of higher
education
KSPL
Metaphor: Cafeteria
Institutions for ubiquitous
learning

National Universities/
famous Private Universities
Metaphor: Luxurious restaurant
Institutions for affordable people

JWS between Germany & Japan, 2009 Berlin

The Organizational Knowledge Circulated
Management System on e-Learning Practices& Human Development
Toshio Okamoto, PhD Professor
University of Electro-Communications,Tokyo-Japan
President: Japanese Society of Information
System on Education

Knowledge Society and Next Society
 By network technology, we need the total

management system for knowledge
producers, providers and consumers
 From structured knowledge to ill-structured
knowledge
 Methodology change ... classroom lecturing
to modern apprenticeship Change of employment systems

Technological Issues
haring/Re-using the distributed
learning resources
istributing computational load
eamless accesstock of learning experiences

Entity of CL

Collaborative tools

AP/Tool

AP/Tool

CW profile (design description)
Data-log of
Learning process

Share window &Ope ration from
Multi sites

AP/Tool
AP/Tool
Descriptive modelSocial computingWhy we need e-pedagogy?
 Changing teachers/instructors’ roles?
 Changing teaching/learning styles?
 Changing teaching/learning resources?
 Changing methodologies ofteaching/learning?
 Changing peoples’ thinking ways, mentality?
 Changing social/industry/business
infrastructure?

What is e-Pedagogy
for Knowledge Building ?
 Independent Self-development
 Collaboration/Align Self-responsibility Learner centric Evaluation (digital portfolio & e-Carte) Practices based on situated context in realworldThe principles of e-Pedagogy
from Social computing
emand Driven
elf-Identity through social activity
ne Top Access to Real World and Data
onstructional Conjunction for Semantics
and Concept by Interactive activity

Dimensions(parameters) of Learning Design
Highlystructured
highStructure
Teacher control

No structurelowexternal

Moderation of learninginternal

external

Learner motivationinternal

Curriculum
based

Learning content

Learner based

Assessment

Unilateralby learner

Unilateral
by teacher

As design & operational factors
Changing Pedagogics

Learning Organization &Knowledge Management
 Instructional / Learning design
 Monitoring / Mentoring / Coaching Evaluating / Revising Collaborative environment
 Knowledge sharing, reusing and delivering Seamless linkage among faculties,

administrative offices and computer center

Faculty Development
Instructional Design

Knowledge
for human
relationships

Learning Design
Skill of Contents Developing
Mentoring Skill

Learning Log Data

Standard of
Academic
Abilitye-Learning
ＣＳＣＬ

Educational
Quality
Assurance

Knowledge Mining
Scientific
Knowledge

Practical
Knowledge

Skill of Educational Evaluation

Mission of CDEL

The Structured Database of Learning Resourcesin Webclass-RAPSODYOrganizational Knowledge
Circulating Management System
Daily e-Learning practices
Creator / Teacher

Teacher

LMS

Reusing

Frame-Construction
Instructional
Knowledge

Extracting

Practice

Frame-Sequence

SavingRelational DB

Matching

SavingExtracting

ATI
Knowledge

Analysis-system
SavingContents DB

Log-Data DB

WebClass-RAPSODYThe Specified System Configuration for
Authoring and Learning Supports

E-Karte
Immediate feedback for learning progress Mentoring & monitoring Revise e-contents
 Management improvement
Rule ofmessagecondition

Mentoring System
Extracting target
moduleProduction ruleof leaner classification

Instructor

Constructing
Rule ofmessage module
messageconstruction
Sending message
Check messages
moduleMessages

Learner

Learning
activities

Production rule ofmessage construction

Learning log data

WebClassRAPSODY(LMS)Architecture of mentoring system

Learning
Log DB

Center for International
Program and Exchange・Support for international students

Information Processing Center
・Network maintenance for e-Learning
・Account management

Center for Research and Developing e-Learning
・Running integrated LMS・Support for planning and developing contents
・Faculty development
・Copy right management
・Support for mentoring and coaching

Center for Higher Education
Development and Research・Planning educational program
・Evaluating educational program

Faculty of Electro-Communications
Graduate School of Electro-Communications
Graduate School of Information Systems
・e-Learning practice in special/ basic course
・e-Learning practice in English
・Mentoring and coaching

Organizational collaboration in UEC

Open Learning Environment and Executing
Strategies for Human Development
 Curriculum and subjects( basic/up-to-date) Quality of courses
 Competency assurance -> national

certification and qualification-> authorization
 Cost burden Sustainable supports (pedagogical andphysical) Linkage with real workshops

A Psychological View on Cognition from
Human Development

Conclusions
 Sustainable organizational managing

scheme for human development
 Sustainable growing services for people Technological & pedagogical environments
for collaboration and autonomous individual
learning
 Commitments, contributions and selfresponsibility including money bearing

The Role of Knowledge Transfer in the
Future Internet

Klaus Tochtermann
http://www.know-center.at© Know-Center - gefördert durch das Kompetenzzentrenprogramm COMET

Where am I from?
Austria is not Australia2
http://www.know-center.at

JDZB 2009© Know-Center

Graz is...

3
http://www.know-center.at

JDZB 2009© Know-Center

Austria

46% of Austria iscovered by forest4
http://www.know-center.at

JDZB 2009© Know-Center

High-Tech Truck in the Forest and theInternet

5
http://www.know-center.at

JDZB 2009© Know-CenterFuture Internet Initiatives

6
http://www.know-center.at

JDZB 2009© Know-CenterPeople…

2008 → 1 Billion Internet User

200 Millionen users
Doubling within 8 months

7
http://www.know-center.at

JDZB 2009© Know-Center

More and More Content & Knowledge[Future Internet Ongoing Activities; Presentation byP. Fatelnig EC]

2002 - 2007 – 2 Billions new photos
2007 - 2008 – 1 Billion new photos

1998 – 26 * 106 indexed webpages
2008 – 1018 indexed webpages

8
http://www.know-center.at

JDZB 2009© Know-CenterFuture Internet
Internet by and for people

Internet of content& knowledge9
http://www.know-center.at

JDZB 2009© Know-CenterLearning at the Professional Workplace

Only 30% of what was learned in a formal learning
courses is applied at the workplace[Robinson, 2003 ]But 80 – 90% of the workplace knowledge isacquired through informal learning[Raybould, 2000]

Bring the learning material to the knowledge worker
and not the knowledge worker to the learning material10

http://www.know-center.at

JDZB 2009© Know-Center

Workplace Learning…

Work Tasks!?
11(Collaborative) Learning Steps
http://www.know-center.at
JDZB 2009© Know-Center

Knowledge Transfer Based on Content ...

12
http://www.know-center.at

JDZB 2009© Know-Center

... and People13
http://www.know-center.at

JDZB 2009© Know-Center

How Many Trees in Austria?

3.475.000.000
4.294.967.296
14
http://www.know-center.at

JDZB 2009© Know-Center

Adressability…

IPv4: 1032 IP-Addresses (4.294.967.296)
IPv6: 10128 IP-Addresses

40.282.366.920.938.463.463.374.607.431.768.211.456
15
http://www.know-center.at

JDZB 2009© Know-Center„Things“ Online

I have arrived ...
16
http://www.know-center.at

JDZB 2009© Know-Center

Internet of Things
Misuse of Knowledge Transfer

17
http://www.know-center.at

JDZB 2009© Know-CenterChallenges ...

Regulation evolves at much slower rate than technology

Who is the owner of the data in networked systems

18

http://www.know-center.at

JDZB 2009© Know-CenterFuture Internet
Internet by and for people

Internet of content& knowledge

Internet of things19
http://www.know-center.at

JDZB 2009© Know-CenterFuture Internet(FI movie – not included in slides)(FI movie – not included in slides)

20
http://www.know-center.at

JDZB 2009© Know-Center

Knowledge Transfer Based on Services

Austrian-Hungarian
Wolfgang von Kempelen
1734–1804
JDZB 200921
http://www.know-center.at© Know-CenterFuture Internet
Internet of services

Internet of content& knowledge

Internet by and for people

Internet of things22
http://www.know-center.at

JDZB 2009© Know-Center

Conclusion
Austria
250 Mio litres wine/year
Future Internet
Old wine in new bottles?

Future Internet
Knowledge transfer will become more informal, self- 23
directed, self-organised and democratic
http://www.know-center.at

JDZB 2009© Know-CenterThank You!
Prof. Dr. Klaus Tochtermann
Graz University of Technology & Know-Center
Inffeldgasse 21a
A-8010 Graz
Tel.: +43 316 – 873 9250
Fax: +43 316 – 873 9254
Email: ktochter@know-center.at

http://www.know-center.at© Know-Center - gefördert durch das Kompetenzzentrenprogramm COMET

Introductory Speeches on 11 Sept 2009

Comprehensive Learning Interactive andGroup Activities as New Ways of Learning
Toshio Okamoto
Graduate School of Information Systems
UEC&
Japanese Society of Information and Systems in Education

Responsible Assignment Study asGroup Project for Learning Finding and setting a problem
 Awareness, consciousness and meanings
 Contrive appropriate strategies/tactics to solve

the problem
 Formalization
 Corresponding the problem with an actual
event Processing and handling Analysis, testing and verification
 Judgment
 Summarizing and report/presentation

Core-Competency
 The skill to analyze the problem and build any

artifact to achieve the goal The skill to build/implement any artifact
appropriate to a given specification
 The skill and attitude to evaluate one’s own
artifact or others’ objectively
 The skill to describe what should be reportedwith correctness
 The attitude to probe the problem and to
manage to solve itSocial Constructivism Approach Group modeling and collaborative role-

activities based on situated context
 Exploration-minded experimental
learning
 Learning by asking, explaining, teaching
and building to acquire a new insightwisdom
 Interactive diagnosis and open learning
modelComprehensive Approach Topic oriented structure Scenario oriented structure Minimum essentials
 Integration by synthesis

The Practice of E-Learning Based on ROPSODY
LM for Simultaneous
Learning

The Visualization of the
Topic Transition LM

Dialogue history
Structured LM
他グループの問題解決過程•グループ学習（協調学習）
自グループ
の過去の問
題解決過程

自グループの現在の問題解決過程LM for DistanceSeminars

•個別学習
•一斉学習

グループＢ

グループＡ

Internet
Collaborative
Learning LM

Web教材

学習活動
ログ
RAPSODY
サーバ

学習用
資源

学習用
資源

LM for Lecture
Searching
協調学習向けＬＭ（症例診断シミュレータ）Lecture
VOD

学習用
資源

①

③

②

④

⑤

Image

of

Model of the Thinking Logic
Type of dmn.

Well-structured

Style ofThinking
1. Rational(Conservative)

Inside atextbook

2. Pragmatic
3. Critical
4. Radical

Ill-tructuredNoassumption

Changing
assumption

Traditional
competency
New competecy
for legacy+ to think out scientific ways
+ to explore the unknown+ to do nonmonotonous one

Web Based Learning Ecology (WBLE): Suggestion to e-Pedagogy
Toshiaki Honda
College of Education, Ibaraki University
2-1-1 Bunkyo, Mito, Ibaraki 310-8512 JAPAN
Abstract•

Background
Difference between Apollo No.13 and Space Shuttle Columbia
People’s wisdom (folksonomy) and adaptability•

What is Learning Ecology?
“A metaphor to describe an environment for learning.”•

Why Learning Ecology Now?
Learning about environment to support learner’s decision for target achievement
Collaborative learning and folksonomy
Ubiquitous net society, “anytime and anywhere”
To consider other’s existence according to learner’s situation•

Concept of Learning Ecology
Learner customizes the tools individually and freely•

Web Based Learning Ecology (WBLE)“Learning ecology focuses on factors and conditions facilitating the process oflearning and searches for ways to increase its efficiency, in the sense of opening new
possibilities for realization of the self-organizing impetus of the living entities, at any
level of the web interactions.”•

Our Project Based on WBLE
Uniting of iGoogle and Mozilla Firefox•

Summary
LESEL (Learning Ecology Supported E-Learning)Web Based Learning Ecology (WBLE):
Suggestion to e-Pedagogy

Toshiaki Honda
Ibaraki University
honda@mx.ibaraki.ac.jp

Outline








Background
What is Learning Ecology?
Why Learning Ecology now?
Concept of Learning Ecology
Web Based Learning Ecology (WBLE)
Our Project Based on WBLE
Summary

Background (1) Difference between Apollo No.13 andSpace Shuttle Columbia
 People’s wisdom (folksonomy) andadaptability

Space Shuttle Columbia
 “Doing nothing is just not an option if
they had known the extent of thedamage,”（Tyrone Woodyard, spokesman for
the Columbia Accident Investigation Board）

Background (2)＊From A to B → B in(to) A＊under A, using B, consequent C↓
under A, purpose C, using B(Reigeluth,1998)

What is Learning Ecology?
 “a metaphor to describe anenvironment for learning”
John Seely Brown (2000): Growing Up Digital: How the Web
Changes Work, Education, and the Ways People Learn.

Why Do We Need a New Concept of
Learning Environment?
 Difference between old concept of “Learning
Environment” and “Learning Ecology”
 Sustainability
 Development
 Informality
 Community Harmony Creativity
 Globals

Why Learning Ecology Now? （1） Learning environment to support
learner’s decision for target achievement
 Collaborative learning and folksonomy
 Ubiquitous net society, “anytime andanywhere”
 To consider other’s existence according
to learner’s situation

Why Learning Ecology Now? (2) Knowledge sharing according to a daily
situation
 Each learner’s synchronized andasynchronized conversation
 Support of formation and maintenanceof study community

Why Learning Ecology Now? (3)
From

To

Learning separated from
community

Cooperative learning

Teacher is a communicator of
Existence of Abundantthe first information (knowledge) knowledge information
Learning isolated from
community

Occurrence of learning
community on the world scale

Concept of Learning Ecology（１）*Richardson, A. (2002): An Ecology of Learning and The
Role of eLearning in The Learning Environment.
Learner Self-Navigation

Content Delivery

Experience andFocus

Practice Focus

Guided Navigation

Concept of Learning Ecology（2）*Richardson, A. (2002): An Ecology of Learning and The
Role of eLearning in The Learning Environment.
Learner Self-Navigation

Studying

Projects

Content Delivery

Experience andFocus

Practice Focus

Teaching

Exercises

Guided Navigation

Concept of Learning Ecology （3）*Richardson, A.(2002): An Ecology of Learning and The
Role of eLearning in The Learning Environment.
Learner Self-Navigation

Content Delivery

Experience andFocus

Practice Focus① facts② concepts
Guided Navigation

① ② ③

④

⑥

Gagne： “Taxonomy of intellectual skills”⑤③ principles④ procedures⑤ problem solving⑥ motor skills

Concept of Learning Ecology （4）*Jay Cross (2007): Designing a Web-Based Learning
Ecology.

 Learner customizes the tools
individually and freely
 Information
 Amazon, blog etc.

 Collaboration
 Skype, chat etc.

 “Unworkshop” resources
 “Informal Learning Research Center” etc.

Web Based Learning Ecology (WBLE)(1) “Cloud computing” as the following
paradigm shift
 IBM: Hardware (~80’)
 MS: Software (90’)
 Google: Web Sharing (00’~present)
 Amazon: Cloud Computing (near future)

Web Based Learning Ecology (WBLE)(2)*Dimitrov, V.(2000): Learning Ecology for Human andMachine Intelligence.

 “Learning ecology focuses on factors
and conditions facilitating the process oflearning and searchers for ways toincrease its efficiency, in the sense of
opening new possibilities for realizationof the self-organizing impetus of theliving entities, at any level of the webinteractions.”

Web Based Learning Ecology (WBLE)(3) Web Based Learning Ecology (WBLE) Portability, connectivity, feasibility,
adaptability etc.
 Learning with blogs, Wikis, and Web 2.0

 Cost performance vs. Learning
OutcomeWeb Based Learning Ecology (WBLE)(4) Cost problem of using portableterminal PDA or game machine inelementary and junior high school(“Nintendo DS” costs $170 in Japan)
 It is possible to use web on PC inelementary and junior high school There are “computer rooms” in almost all
public schools in Japan.

Our Project Based on WBLE (1) Our project (practice in elementaryand junior high schools)
 Uniting of iGoogle and Mozilla Firefox
 Firefox as platform for learner iGoogle as search engine that can becustomized as learner like

Our Project Based on WBLE (2) Plan Subject: Social studies
 Unit: virtual “Stocks buying and selling”
 Suitable to 2nd or 3rd grade junior highschool studentOur Project Based on WBLE (3) Method Install Mobile Firefox to mobile USB memory
stick (about 10 Euro? by 1GB), and it makes
iGoogle to customize top page.
 It leaves no personal information behind on themachine learner runs it on, so learner can takelearner’s favorite bookmarks and extensions
wherever learner goes.
 Advantage at the computer classroom incommon school.

Our Project Based on WBLE (4) Following tools can be used by learner free
while studying












Google Web retrieval
Dictionary
Search YouTube
The world clock
Wikipedia
Book retrieval
News retrieval
Translation
Chat
Bulletin board
Blog etc.

Our Project Based on WBLE (5) Expecting learner’s activity
 Tokyo Stock Exchange ... various
information ...
 Economy and social environment havebeen checked as an information source Sources like newspaper, the quarterly
report, and the magazine, etc.

Our Project Based on WBLE (6) Solution of the problem can beattempted by using alreadymentioned iGoogle and Mozilla
Firefox.
 Learner freely creates the learning
environment for the accomplishment
to goal of study.

Lesson based on WBLE (1)Type of “Project”
Developed by Under Graduate
Student (about Swine Flue）

The gadget is shared in the group, and each one's idea is reflected. (common gadget and individual gadget)Lesson based on WBLE (2)Type of “Study”
Means teacher gives student necessary
material

Is eco-backing
necessary?

Dissenting opinion

Agreement opinion

Lesson based on WBLE (3)Use of Ｗiki （Based on FFP and iGoogle）

Link fromiGoogle to Wiki

Lesson based on WBLE (4)Use of Ｗiki （Based on FFP and iGoogle）

Link to group in class page

Individual summary page

Lesson based on WBLE (5)Effect of Learning (1)Verification of 14 pupils in public elementary school in social studies"Our Ibaraki Prefecture"

調べ安さ

Effectivenessof cooperati
ve
study

Effectivenessofasynchronization

compa Webでのrison

Average

4.3

4.6

4.3

4.5

Decentraliza
tion

.68

.24

.68

.43

Frequency
8
7
6
5
4
3
2
1
0
1

Histogram
Frequency

2

3

4

5

Children’s evaluation

evaluation by teacher
Degree of interest of children by questionnaire survey

Lesson based on WBLE (6)Effect of Learning (2)Correlation in use of children’s evaluation and exchange gadget and use of Wiki

C’s E

ToG

GOS

ToW

C’s E

１

ToG

.61

１

GOS

.54

.98

１

ToW

.40

.40

.37

１

WOS

.55

.91

.85

.45

WOS

１

C’s E・・・ children’s evaluation
ToG ・・・ Writing total of gadget
GOS・・・ Number of writing of gadgets from outside the school
ToW ・・・ Writing total of Wiki
WOS・・・ Number of writing of Wiki from outside the school

Lesson based on WBLE (7)Effect of Learning (3)Relations between children’s evaluation and number of writing

35
30
25
20
15
10
5
0

Concern
ToG
GOS
ToW
WOS

E５

E４

E３

E３

E２

E１

Summary Harmony with age (zeitgemäß) Harmony with culture (kulturgemäß)(by Diesterweg)
 Social Constructivism↓
From 3R’s （reading, writing, arithmetic）
to 4R’s (+information)

Why don’t you join us?
 LESEL Learning Ecology Supported E-Learning Ibaraki University Web Based Learning
Ecology System

Thank you!
Contact:
Toshiaki Honda(honda@mx.ibaraki.ac.jp)
This work is supported in part by the JSPS

Adopting Web 2.0 Technology in Online Learning: Challenges and Experiences
Univ.-Doz. Dr. Denis Helic
Graz University of Technology
Knowledge Management Institute

Abstract
The emergence of Web 2.0 technology changed the ways in how technologysupported learning is carried out in organizations. The online learning systems
ceased to be tools where learning content is organized, structured, and delivered to
the learners. Rather, these systems became the tools where learning content is on
one hand created in collaboration and on-the-fly, and on the other hand integrated
from disparate and heterogeneous online data sources.
Moreover, the online learning processes in organizations changed for all people
involved. Educators began to use tools like wikis, blogs, or RSS feeds for content
integration. Learners instead of consuming the content, or discussing a number of
pre-assigned topics, started to produce highly interlinked content and to actively
participate in designing the steps of the learning process itself. System developers
realized that monolithic systems strictly following a closed set of e-learning
standards cannot support the new learning processes and adopted service-oriented
architectures based on open standards.
However, such ground-breaking changes do not always run smoothly and without
obstacles. They require openness, flexibility, willingness to learn, adopt, and to
explore new grounds not only from educators and students, but also from systemdevelopers. Also, they require a new set of tools that make use of the underlying
technology transparent for educators and learners, but are still technologically
flexible enough to capture modern online learning processes.
In this talk, the experience of educators, learners, system developers, andadministrative service staff in adopting Web 2.0 technology for online education atGraz University of Technology will be presented. Additionally, a short presentationof similar experience from a foreign language learning project funded by EU will begiven.

Freeform eLearning- Approach and Building Blocks

Workshop: ePedagogy and Digital Media
Berlin, September 11, 2009
Joachim Niemeier

Freeform eLearning•

A view to the unconference learning scene•

New tools for new times•

Potential uses of social software for learning•

Beyond the hype: challenges of integrating

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 2

http://www.flickr.com/photos/stephendann/3390437001
Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 3

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 4

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 5

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 6

http://wwweblern.pbworks.com/

http://unionsquareventures.com/2009/05/hacking_education.html

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 7

http://anonymenichtlernende.org

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 8http://bildungsexpedition.de/

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 9

New Tools for New Times
Communication

Social Networks
VideosPhotosWeb OS Programs

Information

Shopping

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 10Life

Opportunities ans Risks

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 11

Will Enterprise 2.0 and Learning 2.0 Have a
Future?

http://www.flickr.com/photos/jam343/1703693/

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 12

Adoption of Technologies
Automating Transactions

Enabling collaboration and participation

Adoption of ERP, CRM, SCM:
• Users assigned by management• Users must comply with rules• Often complex technology
investment

Productivity
Adoption of Web 2.0 tools:• User groups can form unexpectedly• Users engage in high degree ofparticipation• Techology investments often alightway overlay to existing
infrastructure

1990

2009
Source: Chui, M.; Miller, A.; Roberts P.P. (2009), Six Ways to Make Web 2.0 Work,in: The McKinsey Quarterly
Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 13

Zeit

LMS Market Update

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 14

Expertise by Learning ModeHigh
Informal Learning
Methods

Formal Learning
Methods

Low
NovicePracticioner

ExpertSource: Quinn, Clark (2009), Social Networking: Bridging Formal and Informal Learning,
In: Learning Solutions, February 23, 2009

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 15Five Moments of Learning Need•

Learning something new or for the first time•

Learning more of something•

Trying to remember something•

Adjusting performance/behavior because something
has changed•

Figure out what to do when something goes wrong or
fails
Source: Gottfredson, Conrad (2007), http://www.performancesupport.blogspot.com/2007/11/beginning-discussion.html

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 16

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 17

Uses of Social Software for LearningGroup

Network

Collectiv

Metaphor„Virtual classroom“„Virtual community ofpractice“„Wisdom of crowds“

Relationship between
learners

Strong

Weak

Potential

Goals

Accreditation, formal
learning, task completion

Knowledge generation,
expanding social capital

Knowledge extraction

Potantial Web 2.0-Tools

Wiki, Google Docs

Blogs, feedreader, social
networking software, Twitter

Blogosphere, tagging,collective filtering

Operational sizes

Can be effective at low
number 3 - 5

Needs 30 - 50 members tosustain network operation

Only provides value whenvery large numbers of users
participate

Typical value proposition

Productivity, ability torespondKnowledge generation,
bridge to other networks

Innovation, serendipity

Adapted from: Dron, J.; Anderson, T. (2009), How the Crowed Can Teach Quinn

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 18

Trends in Online Networks

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 19

Integration Web 2.0 into Learning

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 20

Getting Learning Done Phases•

Step 1: Initiation and start-up•

Step 2: Looking around and orientation•

Step 3: Sprint or project phase•

Step 4: Result and presentation phase

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 21

Getting Learning Done Phases•

Step 1: Initiation and start-up
Help to find and connect people•

Step 2: Looking around and orientation•

Step 3: Sprint or project phase•

Step 4: Result and presentation phase

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 22Social Software Quadrant

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 23

Initation and start-up
Example: Twitter•

Following a subject
matter expert•

Follow a subject•

Build a community•

Use it to send FAQs

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 24

Initation and start-up
Help to find and connect people•

Follower principal•

Dynamic activities, lifestreams, activity streams•

Signals and structures•

Aggregated skill profiles•

Reputation and community value systems

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 25

Getting Learning Done Phases•

Step 1: Initiation and start-up•

Step 2: Looking around and orientation
Help to start a conversation and inform people•

Step 3: Sprint or project phase•

Step 4: Result and presentation phase

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 26

Social Software Quadrant

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 27

Looking around and orientation
Help to start conversation and inform people•

Low entry barriers and low hurdles to capture andshare short chunks of information•

More informal communication and easy to use
collobaration tools•

When ideas evolve into something concrete then theyusually require a different environment

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 28

Getting Learning Done Phases•

Step 1: Initiation and start-up•

Step 2: Looking around and orientation•

Step 3: Sprint or project phase
Help to start collaboration and cooperation•

Step 4: Result and presentation phase

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 29

Social Software Quadrant

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 30

Even More Collaboration Tools•

Workgrouping•

Web Conferencing•

Project Management•

Collaborative Writing•

Collaborative Reviewing
For details see Robin Good‘s list under
http://www.mindmeister.com/de/maps/show_public/12213323
Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 31

Sprint or project phase
Help to start collaboration and cooperation•

From chaos to coordinated activities•

From colloboration to cooperation•

Task and result oriented•

Knowledge creation

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 32

Getting Learning Done Phases•

Step 1: Initiation and start-up•

Step 2: Looking around and orientation•

Step 3: Sprint or project phase•

Step 4: Result and presentation phase
Help to discuss and share results

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 33

Social Software Quadrant

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 34

Result and presentation phase
Help people to discuss and share the results•

Write what you learn and get feedback•

Quick publishing and sharing of content•

Publish in a format that explicitly allows copying andmodifying of its information (open content)•

Usage in a more formal eLearning environment

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 35

Social Software Quadrant

Identity andNetwerk Management

Information
Management

Communication
Management

Cooperation and
Collaboration
Management

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 36

Understanding the Importance and Power of Web 2.0
for Learning•

Emergence is the way complex systems and patterns
arise out of a multiplicity of relatively simple
interactions•

Emergent structures, rather than imposed ones•

Replacing central control with a more dynamic andflexible set of rules•

Making learning agile and flexible but without
introducing chaos

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 37

Tale of the Two Tunnels

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 38

Social Software Fills the Gap Between the Formal andthe Chaotic
Engineered:
Inflexible Structure
Participation • Mandantory
participationand progress• User tracking

Adaptability• Rigid schemas,

Structuring
andorganization• Rigid metadata• Isolated repositories• Often out of date

workflows, accessrights, templates

Freeform and Open:
Adaptive Structure

Personal:
Chaotic Structure• Open to participation• Visible learning in• Invisible learning inprogress

progress• Invisible history• Open to modification• Reuse in context• Incremental refinement• Too much noise• Organization reflects• Each user reinventscurrent use and needs• Natural group formation
based on activities andinterests

their own structure• Large body of
information notorganized

Adapted from Gartner

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 39

(duplication, version,changes)

The business case and the adoption process
are still maturing

http://www.flickr.com/photos/jam343/1703693/

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 40

http://www.flickr.com/photos/mkuhn/2815676352/

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 41

http://www.flickr.com/photos/virgomerry/19751300/

Joachim Niemeier
Freeform eLearning, September11, 2009
Seite 42The Quality Assurance Related to e-Learning Contents andLearning Design
Naomi Nagata

Abstract
e-Learning is a relative newcomer to the education area, yet it holds already a
noticeable share of the learning market. In general, e-Learning contents arecomposed of some representative media such as sentences, figures and tables,
video, sound-narrations, animations, and simulations. While any multimedia isbeing used, the instructor is doing various devices to improve sustainability.
The aim of this study is to develop a method of qualitative analysis for
extracting features/characteristics from e-Learning contents, in considerationof the semantic relationship between figures and sentences. In order to extract
the features/characteristics, we propose a method of contents analysis for“characteristics on frames” and “sequences of frames.” On the basis of thisanalysis, we propose a method for contents construction. In comparison withprevious research on the subject, our research is aimed to the synergy-effect inthe meaningful relationship among figures, sentences and sound-narrations; wetake a qualitative analysis approach from the point of view of cognitive andlinguistic semantics. As a result, we extracted three patterns:“progressive-pattern,” “regressive-pattern,” and “spiral-pattern” from thecharacteristics on analyzed frames. Moreover, we try to test the “synergy-effect”
for the compounded contents among figures, sentences, and sound-narrations.
Also, we propose the concept of “rhythm of understanding” from the point of
the semantic relationship among those media. For that we define “rhythm ofunderstanding” is internal behavior to create harmony in brain forunderstanding a series of learning and instructional materials, accompaniedwith several represented media. We assume the degree of this harmony“synergy-effect.”Japanisch-Deutsches Zentrum Berlin

The Quality Assurance
Related to e-Learning
Contents and Learning Design

Naomi Nagata
Toshio Okamoto
The University of Electro-Communications
Tokyo JAPANResearch motivation
 Sentences Figures & tables
 Sound-narrations
 Video Animations
 Simulations

How is quality assurance related to
e-Learning Contents & Learning Design?

The framework of the course
structure
Relational & logical information of course structure

CourseUnit

Unit
Instruction Q & A

Instruction Q & A

Instruction Q & A

Instruction Q & A

Frame Frame Frame Frame Frame Frame Frame Frame
SubFrame

SubFrame・・・・・・・・・・・・・

SubFrame

SubFrame・・・・・・・

The qualitative-analysis forcontents construction- method
Extraction of characteristics on contents
Extraction of characteristics on frames

Extraction of characteristics on contents
Figures (A table is regarded as a kind of figures )Semantic relationship between figures & sentences

Chart for contents-analysis* 1.“F” is short for “Frame”. * 2. Evaluator checks (☑) in this chart.

Area & exemplification

Coordinates & copy

Link & supplement

Array & condensation

Ordinability for intuitive-understanding… without deep understanding
Semantic relationship between
figures & sentences

Y-axis?
?
?
?
X-axis?

?

?

Figure?

Ordinability for intuitive-understanding about
figures & sentences

Ordinability for “intuitive-understanding” about
figures & sentences
1) Ordinability for figures:

22.92) Ordinability of the semantic
relationship between figures& sentences:
23.0

20.2

18.7
10.4

10.7
6.1

7.2

Set up 2-dimentions

X-axis: Link
: Array: Area: Coordinates
Y-axis: Exemplification: Copy: Supplement: Condensation

Extraction of characteristics on frames
The procedure for extracting frame-characteristics

The analysis for frame-characteristics
1) Pattern1: Progressive-pattern：１１2) Pattern2: Regressive-pattern：８3) Pattern3: Spiral-pattern：７

“Synergy-effect” by soundnarrations in frames
ExperimentⅠ:
The effective description of explanatory
sentences for understanding
Experiment Ⅱ:
The more effective method of adding soundnarrations

ExperimentⅠ:

The effective description of explanatory
sentences for understanding

Procedures
A) Key-sentences only B) Key-phrases only C) Explanation

ExperimentⅠ:

The effective description of explanatory
sentences for understanding

Procedures
A) Key-sentences only B) Key-phrases only C) Explanation

Repeatingsound-narrations

Repeatingsound-narrations

Repeatingsound-narrations

Test-results
100
90
80

80

73

71

70
60

66
60

57
52

50
40

Multiple-choice questions

46
38

Free recall questions

30
Description questions

20
10
0
Key-sentences

Key-Phrases

Explanation

Experiment Ⅱ:
The more effective method of adding
sound narrations
ProceduresB) Key-phrases only C) Explanation

Repeatingsound-narrations

Repeatingsound-narrations

Experiment Ⅱ:
The more effective method of adding
sound narrations
ProceduresB) Key-phrases only C) Explanation

Repeatingsound-narrations

Repeatingsound-narrations

Complementarysound-narrations

Complementarysound-narrations

Conclusions
From point of view ...
 Contents-analysis
 Synergy-effectContents-analysis
Qualitative method for contents analysis
 Extracting three patterns
 Progressive-pattern Regressive-pattern Spiral-patternSynergy-effectKey-phrases sentences

Complementarysound-narrations

Rhythm of understanding
FigureSoundnarrations
SentencesThank you for your attention

Hyperblog for Sharing and Inheriting Knowledge from Research
Activities

Akihiro KASHIHARA1, Keisuke NAGATOME1, and Shinobu HASEGAWA2

Abstract

Research activities in a laboratory include research meeting, survey of related work,
system development, etc. These activities produce formal knowledge of researchcontents and informal knowledge tacitly obtained from them. The formal knowledge
is represented as papers, program source codes, presentation documents, etc. The
informal knowledge also includes slogan, heuristics, experiences, how-to knowledge,
etc. It is quite important for the research members to share and inherit suchknowledge to promote their research activities.
The main issue addressed in this paper is how to share and reuse knowledge
from research activities within a laboratory and how to facilitate legitimate peripheral
participation of newcomers to the laboratory. We particularly focus on sharing theinformal knowledge. In general, it would be embedded in the research logs that
research members keep in their daily work. Each member could reflect on and orient
his/her own research activities with his/her research logs. Sharing the research logs
kept by other members, he/she could also gain some awareness of knowledge, which
could not be obtained from his/her logs, from their logs. In addition, he/she could
be motivated to research. It is also important for the newcomers to inherit the
informal knowledge. They would usually make a gradual transition from a guest to
research member in the laboratory. In other words, they first play a peripheral roleand gradually fill a central role in the research activities. Such transition could bepromoted by learning research logs accumulated by other members to inherit the
informal knowledge.
The key issue towards sharing and reusing the research logs to be obtained

from the members is how to accumulate the logs that are dispersed in each member.
Our approach to this issue is to propose Hyperblog that enables each researchmember not only to submit and accumulate his/her research logs as blog entries, butalso to share and reuse the logs gathered from other members. Hyperblog connects
each blog generated by each member to organize and reorganize the blog entries withthree types of metadata, Research Activity, Tags, and Research Topic. It also provides
three functions that are blog entry submission, blog entry sharing, and knowledge
inheritance.
This paper also demonstrates a Hyperblog system, which has a SNS-basedarchitecture. It allows the research members to share and reuse blog entries
accumulated by themselves and by others, and also to communicate with each othervia the blog entries. In this paper, we also report the case study with the system. The
results indicate the possibility that Hyperblog facilitates submitting, sharing andreusing the research logs in an effective way.

----------------------------------1

Dept. of Information and Communication Engineering, The University of Electro-Communications;kasihara@ice.uec.ac.jp
2

Japan Advanced Institute for Science and Technology

•
•
•
•
•

•
•
•

Knowledge from Research Activities

Publishing
Meeting

System evaluation

Survey of related work

Research theme setting

System development
Idea refinement

•
•

•
•

Publishing

Knowledge Sharing/Reuse

Meeting

System evaluation

Survey of related work

Research theme setting

System development
Idea refinement

•
•

•
•
•
•

Publishing

Knowledge Inheritance

Meeting
System evaluation
Survey of related work
System development
Research theme setting
Idea refinement

•

•
•
•
•

•
•

Approach

•

•

•
•

•
•

Framework of Hyperblog

•

•
•

•

•

•

•

Blog entry

Metadata•Key research activities (System-defined):

Research theme setting, idea refinement, meeting,survey of related work, system development, evaluation,and publishing

Submission Phase•Tags (User-defined)•Research topics (Community-defined):
Tags that have been used by more members

1. Research topic generation:

Automatically detecting research topics as meta-data that havebeen used by more members

2. Tag candidate presentation:- Presenting tags as candidates for meta-data of submission entry,
which are classified according to the key research activities, and- Preventing the tags as meta-data from dispersing

Sharing Phase

Inside links

Links between
members

1. Blog entry search:

Using meta-data to search blog entries according to inside links
and links between members

2. Tag identification:- Automatically identifying tags that have the same meaning and different
expressions to create well-organized structure of blog entries- Identification mechanism:
Calculating the degree of similarity between the vectors of keywords
included in the blog entries
If the similarity degree is high, the tags attached to them are identified.

Inheritance Phase

Difficulties for newcomers to learn
with a huge number of blog entries

1. Recommendation:- Recommending them instructive blog entries to be filtered- Recommending them other members who can guide them in
research activities

Under construction...

Hyperblog System

•

•
•
•

User Interface of Hyperblog

Navigation bar

Newly-arrived blog entries from members

Newly-arrived comments from members

Recent blog entries submitted by the user

User Interface of Hyperblog

List of key research activities as
meta-data

List of research topics detected

List of tags attached

List of blog entries submitted by the user

User Interface of Hyperblog
List of blog entries linked between members
whose key research activity as meta-data is“Meeting”
Search results with “Meeting” as keyword

Case StudyResults

Results: Questionnaire

15Strongly no

Strongly yes

Conclusion• Hyperblog• Accumulating and organizing research log in a researchcommunity• Sharing and inheriting informal knowledge from researchsystem• SNS-based
Using OpenPNE•• Support for submission, sharing, and inheritance• Trial Use

work• Future
Large-scale and long-term evaluation•• Support for sustainable blogging for sharing and inheriting
research knowledgehttp://wlgate.ice.uec.ac.jp

Social Situation and Demandfor Further Education
Requirements for e-learning
systems

… a remark on the title
 To make it quite clear– Demand is most probable the wrong term Much more precise would be– NeedOn the scope of my contribution
 Working with e-learning professionals since quite
a few years, I have felt a bias in the e-learning
discussion:
 Most of my colleaques tend to cater for highly
motivated, interested and socially mobile people.
 But we forget to look at the needs of those, who
need education and training most:the under-privileged, younger people,
lacking any professional education

Sources for my statements
 Advisory council for further education at thestate government of Baden Württemberg
 Statistisches Landesamt Baden
Württemberg
 Deutsche Bank Research Experience at a vocational training instituteThe situation
 Education and unemployment

Situation

Education and further education

…even worseJapan and Germany???

Some observations
 The group which needs training andeducation most, has the lowest
participation rate Companies train well educated and trained
employees 10 times more than untrained
employees
So – as a result – the most affected group
receives the smallest part in training

A first conclusionSociety can not afford this any longer– Demographic development requires theactivation of the full potential of the citizens
As– the increasing international competition
and– the increasing complexity of technologies
are doingRequirements for e-learning
systems 1
 An e-learning system includes– Continuing education (not course or
examination based)– Service to provide competencies (not only
knowledge!)– Service as consultants to individuals andcompanies– Provision of LLL– Using international standards and certificatesRequirements for e-learning
systems 2
 We have to adress– People outside the educational mainstream– Provide adequate forms and methods
 Edutrainment
 Game based education– Cultural differences– Language diversity– Changed patterns of learning Edupunk, educamp etc.

Virtual Campfire –Digital Media Discourses
between Cultures, Continents
and Generations
Japanisch-Deutsches Zentrum Berlin,
September 11, 2009
Ralf KlammaInformatik 5
RWTH Aachen© www.role-project.eu

Conclusions andOutlook

Virtual Campfire

Non-linear storytelling

Knowledge
Management

International
Communities in Cultural
Heritage Management

Media Discourses

Agenda© www.role-project.eu

Virtual Campfire – A Teaser© www.role-project.eu

Media Discourses –New Challenges• Media is witness for cultural • Knowledge may get lost,
heritage preservation
if no community/individualis telling stories any more
• How to preserve
knowledge?
• How to bridge
intergenerational,
intercultural gaps?
Reconstruction?
How?
• How to use information
technologies to preserve– Heterogeneous communities
knowledge?
– Media as research discourses
and archive© www.role-project.eu

International Communities
Communication /Cooperation ?

UNESCO

Administration

SketchdrawingGPS
positioning

Content input / request
SPACH

Content retrieval
ICOMOS
Database

Standards
defining

Surveying/recording

RWTH
AachenResearch

Experiences
imparting

Cultural heritage in
Afghanistan
Surveying/safeguarding

Photographing
Asia
Teaching/
presentationwww.bamiyan-development.org© www.role-project.eu

Knowledge Sharing• The SECI Model (Nonaka and Takeuchi, 95)• Interpretation with the Transcription-media Theory(Jäger, 02)• Knowledge management for cultural heritage
management communities
Implicit
Knowledge

Implicit
Knowledge

Explicit
Knowledge

Explicit
Knowledge© www.role-project.eu

Cross-Media
Theory of Transcription
Cross-Media Transcription

Pre-“texts“ Strategies of transcriptivity

Transcript
Understandand Critisize Collection of learning materials are re-structured by new media
 Design is specific for media and communities by default

 Strategies of addressing
 Social Software promotes the globalization of address spaces Personalization and adaptive strategies are mission critical forcommunities

 Strategies of localisation
 Re-organization of local practices is stimulated by new media
 Need to model practice explicitly

Jäger, Stanitzek: Transkribieren - Medien/Lektüre 2002

© www.role-project.eu

Learning & Knowledge Management
Individual / Community Perspective

Declarative Knowledge

Procedural Knowledge

sensomotoric skills, procedural scripts
non-documented routines and operations

Semantic Knowledge

Episodic Knowledge

semiotic concepts
documentation

memory of experiencing past episodes
web blogs, narratives[Nonaka & Takeuchi, 1995]

VerbalNon-verbal

words
linguistic data

image, icon, index
video blogs, diagrams,
images, photographies[Ullman, 2004]© www.role-project.eu

Non-linear multimedia
story-telling“Digital Storytelling uses digital media to create
media-rich stories to tell, share and to preserve.
Digital stories derive their power through weaving
images, music, narrative and voice together, thereby
giving deep dimension and vivid color to characters,
situations, and insights.”
Digital Storytelling Association(http://dsaweb.org)• Tell: Experiencing & Navigating MM stories• Share: Web-based collaboration• Preserve: DB driven storage of discourses

e-learning© www.role-project.eu

Applications for Non-linear
Multimedia Storytelling

Localization

Addressing
Problem panelMOD
story creation panel:organic view, (cycle, …)

Transcription
Media panel© www.role-project.eu

Story-tellling Expert Finding Knowledge value of community# Recommendations

sorted by keywords

AmateurExpertvaluesExpertKeywords© www.role-project.eu

Virtual Campfire Applications
Context-Aware Services(Mobile)Interfaces

Storytelling
Storytelling
Service
ServiceMedia
Creation

GPSaugmented
multimedia
creation

Media
Media
SearchSearchSemantic
Semantic
Browsing
Browsing
Mashups
Automatic
Discovery &Configuration

Multimedia GIS

Connectors: HTTP, SOAP

Media
Media
Tagging
Tagging

MPEG-7MPEG-7
Services
Services

Map
Services

Context
Services

Multimedia Processor
Multimedia
Multimedia
Storytelling
Annotation
Adaptationon the ipod
Multimedia
PlayerSNA
Tools

Databases

Non-linear digital storytelling
Metadata
Multimedia
Extractor
Multimedia
Multimedia
Multimedia
Repository
Repository
Repository

Multimedia
Input

Context aware
Context aware
multimedia search
multimedia GIS
SessionUser
ObjectManagerManagerManager
Community Engine

Data Sources

Data
AccessWWW

MPEG-7 multimedia
tagging andcommsonomy

MPEG-7 enabled context
aware multimedia search© www.role-project.eu

Conclusions & Outlook
Virtual Campfire• Media discourses for large distributed professional
communities• Discourse support between generations, cultures, andcontintents• Cultural heritage preservation as an example• Integrated story-telling and knowledge management approach• Complete implementation as a community information system
Future Work• Mobile Storytelling and new media (3D scans, realtime video)• Integration of serious gaming• Sustaining communities beyond funded projects© www.role-project.eu

Language Learning and Digital Media
Ikumi WARAGAI (ikumi@sfc.keio.ac.jp)
Tatsuya OHTA (FZE00305@nifty.ne.jp)
Contents
1. Theoretical Background2. Learning Tools
3. Construction of a Database
4. Research Perspective

1. Theoretical Background
Language learning and life-long learning/autonomous learning
Competence of foreign language=
communicative competence +language awareness + learning awareness• Role of digital media• Construction of a rich language learning environment

2. Learning Tools
2.1. Project Neue Medien und DaF
New Media and German as a Foreign Language(Keio University, Shonan-Fujisawa-Campus)= Language learners develop digital learning environments for themselves
and other learners
2.2. Learning Platform
Learning Material 1
Learning Material 2

Learning Material 3
2.3. Advantages of mobile media• Accessible everywhere, at any time
• Effective use of spare time
• Integration of learning and leisure activities
2.4. Application of GPS-Function• Identification of location and situation by GPS supported net book,
iPhone, etc.
• Long term recording of learner behavior

3. Construction of a Database• Database for/of learning after school• Construction of a database of pre- and post-graduation language learning
biographies
Issues• A short term evaluation of education is not possible.
→ An output study from a long term perspective is needed.
• How can we evaluate an “outcome”?
→ the ability to use the skills in professional life? / in communicative
situations?

4. Research perspective• Analysis of data from the experiment with GPS-based language tools• Experiment in campus network with GPS-based language tools• Integration into the university’s database…
etc.

Interaction-Oriented CSCL Environment Based on Focusing
Intentions of Learners
Yuki HAYASHI, Tomoko KOJIRI and Toyohide WATANABE
Graduate School of Information Science, Nagoya University

With the development of network technologies, learners can easily study with others
through network independent of time and location. However, as the communication
band of the network is restricted, learners cannot acquire much information aboutsituations or behaviors of other learners in the virtual learning environment. In orderto support successfully communication among learners, we construct theinteraction-oriented behavior learning space, in which learners can be aware of theeffective information according to their focusing intentions for other learners(focusing target) or utterance (focusing utterance). Focusing targets of learners are
estimated by calculating focusing degrees for each learner based on the actions suchas making utterances, observing the memo-sheet of other learners, so as to increase
the degrees for their target learners. The learner’s direction of view is changed
according to the focusing target with the largest focusing degree, and also his area ofview is turned by the degree of the learner’s focusing target. In addition, utterance
texts move from utterer to the utterance targets in the virtual learning environment
so that the learner can grasp the conversation flow intuitively. The focusing
utterances which are detected based on the target utterance, utterer and utterance
target information, are represented in the learner view with different colors anddisplay-time to distinguish it from other utterances. The experimental result showsthat the display method of utterances makes it clear that participants grasped the flowof utterances intuitively by observing the moving utterance texts.

Interaction-Oriented CSCL
Environment Based on
Focusing Intentions of Learners
Yuki HAYASHI,
Tomoko KOJIRI,
Toyohide WATANABE
Graduate School of Information Science,
Nagoya University
2009/09/11

1

Outline
1. Research Background and Objective• Target Learning Environment

2. Approach• Focusing Intention for Other Learners• Focusing Intention for Utterances

3. System Operation
4. Experiment and Summary
2009/09/11

2

BackgroundDevelopment of computer technologies• Many people can easily study with others throughnetwork independent of time and location.

Real-time communication tools commonlyused in collaborative learning• Communication means are restricted.
• Display image of information are same for all cases.
ÆIt is hard for learners to study with other learners
smoothly and effectively.
2009/09/11

3

Research Objective
To construct interface for collaborative learningwhere learners can feel interaction with others
Learners progress learning collaboratively byfocusing on particular learners/utterances.
Focusing target• Other learner whom learner is interested in

Focusing utterance• Utterance which relates to learner himself/herself
2009/09/11

4

Target Learning Environment
Using text-chat, other learners’ camera
images and learner’s memo-sheet
Chat window

Round-table window
Camera images of other learners

Memo window

2009/09/11

5

ApproachFocusing intentions for other learners
1. Learner view is changed based on his/her
focusing degrees to other learners.

Focusing intentions for utterances
2. Utterances texts are moved in learnerview to display flow of conversation.
--------------------

2009/09/11

6

Detection of Focusing Target (1/2)
Actions from learner X
A

B

2

3

Learner X
1

Actions from other learner
6A

7
5
Learner X

2009/09/11

Target learnerbased on action

B

4

1

Learner X

2

Undefined

3

Learner B

4

Learner B

5

Learner B

6

Learner B

7

Learner A
7

Detection of Focusing Target (2/2)
To calculate focusing degree of learners
Learner n’s focusing
degree at time t

Constant number which represents change
of focusing degree on certain action type i

F (n,t) + α i⎧⎪
F (n ', t) + α i⎪ ∀∑F ( n , t + 1 ) = ⎨ n '∈ N
F (n,t)⎪⎪ ∑ F (n ', t) + α i⎩ ∀ n '∈ N

Target learnerfor action type i
OtherwiseFocusing Target• Learner who has the largest focusing degree
2009/09/11

8

Learner View Change
Focusing target• Direction of learner view

Focusing degree of focusing target• Distance between learner and focusing target
View field
View direction

2009/09/11

9

Learner View Change
Focusing target• Direction of learner view

Focusing degree of focusing target• Distance between learner and focusing target

2009/09/11

10

ApproachFocusing intentions for other learners
1. Learner view is changed based on his/her
focusing degrees to other learners.

Focusing intentions for utterances
2. Utterances texts are moved in learnerview to display flow of conversation.
--------------------

2009/09/11

11

Focusing Utterance Patterns
Utterance whose target utterance is:• X’s utterance
A

B

A

1

2

2

Learner X

B
1

A

B
1

2

Learner X

Learner X• Other learner’s utterance whose target is X
A

B

2

1
Learner X

2009/09/11

A

B
1

2
Learner X

12

Moving Utterance in Learner View
Utterance to particular learner• Utterers Æ Utterance target

Utterance to all learners• Utterers Æ Midpoint between X and X’s focusing target
Focusing target

C

B

Focusing utterance• Text color: highlighted• Font size: bigger• Fade-out time: longer
2009/09/11-----------------------------------------------------------------

D------------------------------------------------------------------A---------------------------------

X

13

Demonstration
Learner viewRound-table window
Focusing target

Learner C

Learner B

Chat window

Learner A
Memo window

Utterance text
2009/09/11

14

Experimental Setting
To evaluate effectiveness ofdisplay method of utterances
Participants• 2 groups of 4 college students

Task• To discuss current topic of Japanese society

Evaluation method• To answer questionnaire about display method ofutterances [1(worst) to 5(best)]
2009/09/11

15

Experimental ResultAverage score of questions
QuestionsAverage

Could you recognize transitions of(a)utterances?

4.00(b) Could you read utterance texts?

3.63

Did moving texts prevent smoothcommunication?
Could you grasp display differences of(d)focusing utterances?
(c)

2009/09/11

4.75
3.25
16

Experimental ResultAverage score of questions
QuestionsAverage

Could you recognize transitions of(a)utterances?

4.00(b) Could you read utterance texts?

3.63

Majorityof texts
participants
could recognize
Did moving
prevent smooth(c)
4.75
utterers and utterance targets.
communication?
Could you grasp display differences of(d)focusing utterances?
2009/09/11

3.25
17

Experimental ResultAverage score of questions
QuestionsAverage

Some participants could not read all
Could
you recognize
transitionsofutterance
texts
when
they
were
long.
(a)
4.00
utterances?

(b) Could you read utterance texts?

3.63

Did moving texts prevent smooth
4.75
communication?
Could you grasp display differences of(d)3.25
Participants could communicate with others
focusing utterances?
(c)naturally through round-table window. 18

2009/09/11

Experimental ResultAverage score of questions
QuestionsAverage

Could you recognize transitions of(a)utterances?

4.00(b) Could you read utterance texts?

3.63

(c)

4.75

Participants were able to grasp detectedfocusing
utterances
some extent.
Didmoving texts
prevent tosmoothcommunication?
Could you grasp display differences of(d)focusing utterances?
2009/09/11

3.25
19

SummaryWe construct intuitive collaborative learninginterface based on focusing intentions of learners.
• Changing learner view according to focusing target• Moving utterance by target information

Future work
• Modification of display method for utterance• To distinguish learner’s own utterance from other learner• To divide utterance into several texts according to text length• Introducing voice chat2009/09/11

20

From Learning in the Net to Learning Networks
Aljoscha BURCHARDT
Darmstadt University of Technology
Abstract
The increasing use of social software – often referred to under the heading “Web2.0” – in combination with the rapid expansion of ubiquitous, embedded, andnetworked computing technology has already started to change the way peopleinteract, socialize, and live. Our working environment as part of a globalized
knowledge society is subject to change as well. These changes also affect the way
people learn, i. e. the way they acquire, update, and propagate knowledge.
Technologies emerging from Ubiquitous Computing, Natural Language
Processing, and the study of Social networks/Web 2.0 enable what we call ambient
learning by connecting humans, devices/services, and content into learning networks(Downes 2007).
In the presentation, we will give an overview of research activities at TU
Darmstadt related to e-learning and the topics mentioned above. This includes
short introductions of the Telecooperation Group, the Ubiquitous Knowledge
Procesing Lab, and the Center of Research Excellence “E-Learning 2.0.”

From Learning in the Net toLearning Networks
Dr. Aljoscha Burchardt
Center of Research Excellence „E-Learning 2.0“Technische Universität Darmstadt„In my opinion you must definitely go to Darmstadt.
They havea good Polytechnic School.“
Albert Einstein 1919

09/2009 | Center of Research Excellence "eLearning 2.0" | 2

Some Facts about TU Darmstadt
 16 Departments 13 Centers of Research
Excellence 7 Graduate Colleges
 Focus on Technology
 ICT/Computer Science Engineering Topics: Energy, Mobility, …

 Multidisciplinarity
 eLearning Urban Development
 Adaptronics
09/2009 | Center of Research Excellence "eLearning 2.0" | 3

The center of Research Excellence„eLearning 2.0“ – Structure & Funding

Graduate
SchoolUbiquitous
Knowledge
Processing

Telecooperation

CRE„eLearning

2.0“
Semanticsbased
Knowledge
Acquisition

Ambient
Semantic
Learning

eDidactics

09/2009 | Center of Research Excellence "eLearning 2.0" | 4

The center of Research Excellence„eLearning 2.0“- Management
 Prof Dr. Iryna Gurevych Head of Ubiquitous Knowledge Processing Lab (UKP) Semantic Natural Language Processing Prof Dr. Max Mühlhäuser
Prof. Dr. Max
Mühlhäuser

 Head of Telecooperation Group (TK) Head of Graduate School „eLearning“
 Ubiquitous Computing (aka. Ambient Intelligence) Dr. Aljoscha Burchardt
 Research Manager
 Ambient Semantic Computing Project
09/2009 | Center of Research Excellence "eLearning 2.0" | 5

The Philosophy of Learning Networks(inspired by Stephen Downes)

HumansDevicesContent

09/2009 | Center of Research Excellence "eLearning 2.0" | 6

Vision 1: Learning in the Net
Example Scenario: Ambient Learning
Which business model did we favor in
the forum discussion?
How is it defined?

WWW(eContent,
Blogs, WiKis, Video,
Forums, .ppt‘s)

09/2009 | Center of Research Excellence "eLearning 2.0" | 7

Vision 2: Learning Networks
Example Scenario: Product Development Teams of developers are globally distributed and networked
 Masses of data to be considered (usage data, scientic achievements)

ResearchCommunity

Forums/ImagesNorms/
Patents

Wireless
Mobile(s)Sensors

Communikation

Learning Networks
Innovation

Productdevelopment

MarketingUsage

Recycling Central challenges
 Modeling the semantics of the networks (Teams, Communities, Events)
 Global (Team-)communication
 Synchronization (workflows, online time, trend detection)
09/2009 | Center of Research Excellence "eLearning 2.0" | 8

In the Remainder a Short Overview of…

 UKP Lab TK Group Graduate School / Ambient Semantic Computing project

09/2009 | Center of Research Excellence "eLearning 2.0" | 9

Subject Areas of UKP Lab

User-generated Discourse

eLearning 2.0

Web 2.0 \ Services

1. Multilingual Semantic Information Management (SIM)
2. Educational Natural Language Processing (e-NLP)
3. Natural Language Processing and Wikis (NLP4Wikis)
4. Ambient Semantic Computing (ASC)Prof. Dr. Iryna
GurevychDarmstadt
Knowledge
Processing
Repository

WikiMining

NLP / Lexical Semantics
Semantic Information Management
Text / Opinion Mining

09/2009 | Center of Research Excellence "eLearning 2.0" | 10

UKP Projects (Excerpt)
Self-structuring Wikis
AQUA

Semantic Information
Retrieval (SIR), DFG

Wiki-Mining

Sentiment Analysis inUser Generated
Discourse (SentAL), DFG

Semantic Question Answering for eLearning 2.0 (QA-EL)

Internet der Dienste(THESEUS), BMWI

Wiki

Darmstadt Knowledge
Processing Repository
Data import

Linguistic preprocessing

Morphological analysis?

Syntactic analysis

Semantic analysis

Project specific analysis

Data export

09/2009 | Center of Research Excellence "eLearning 2.0" | 11

NLP

What is this Text About?
CHICAGO, Oct 29 - Kraft Foods Inc and Kellogg Co posted better-than-expected third-quarter
profits on Wednesday as price increases and new products helped lift sales in a weakeconomy. Kraft also stood by its forecasts for 2008 earnings before one-time items as well
as for 2009 net income, while Kellogg said its profit this year should hit the high end of its
previous targeted range. Both Kraft, the largest North American food maker, and Kellogg,
the world's largest cereal company, have taken steps to cut costs and put more money intoadvertising. Both have also bolstered new product development to attract consumers evenas rising commodity costs pushed them to raise prices. Commodities like wheat and energy
have become less expensive in recent months, but food companies may not see a big
benefit until next year, in part because they lock in their costs months ahead. Kraft, whichmakes Oreo cookies, Tang breakfast drink and Oscar Mayer hot dogs, reported a profit of
45 cents a share before one-time items, a penny above what analysts polled by Reuters
Estimates had expected. The company hiked prices on products, leading to a 0.9 percent
drop in volume. However, that key result was still better than the company had expected.
Analysts are watching to see how much consumers cut back on buying branded products inthe face of rising food prices and a slumping economy. Kraft sales rose 19.4 percent to$10.46 billion. Organic sales, which exclude the impact of currency, acquisitions anddivestitures, rose 7.1 percent due to higher pricing. Over the past several years, Kraft has
closed factories, cut jobs and divested brands to focus on areas like cookies and crackers,
pizza and healthier foods. Shares of Kraft rose 1.8 percent to $29.39 in premarket tradingfrom Tuesday's closing price of $28.88 on the New York Stock Exchange, while Kellogg
stock was not active. Kellogg, the maker of Rice Krispies and Eggo waffles, said net income
rose to 89 cents a share from 76 cents a year earlier. The results were far better than the 80
cents analysts had forecast.
09/2009 | Center of Research Excellence "eLearning 2.0" | 12

For Example: Automatic Insertion of Key
Phrases
CHICAGO, Oct 29 - Kraft Foods Inc and Kellogg Co posted better-than-expected third-quarter
profits on Wednesday as price increases and new products helped lift sales in a weakeconomy. Kraft also stood by its forecasts for 2008 earnings before one-time items as well
as for 2009 net income, while Kellogg said its profit this year should hit the high end of its
previous targeted range. Both Kraft, the largest North American food maker, and Kellogg,
the world's largest cereal company, have taken steps to cut costs and put more money intoadvertising. Both have also bolstered new product development to attract consumers evenas rising commodity costs pushed them to raise prices. Commodities like wheat and energy
have become less expensive in recent months, but food companies may not see a big
benefit until next year, in part because they lock in their costs months ahead. Kraft, whichmakes Oreo cookies, Tang breakfast drink and Oscar Mayer hot dogs, reported a profit of
45 cents a share before one-time items, a penny above what analysts polled by Reuters
Estimates had expected. The company hiked prices on products, leading to a 0.9 percent
drop in volume. However, that key result was still better than the company had expected.
Analysts are watching to see how much consumers cut back on buying branded products inthe face of rising food prices and a slumping economy. Kraft sales rose 19.4 percent to$10.46 billion. Organic sales, which exclude the impact of currency, acquisitions anddivestitures, rose 7.1 percent due to higher pricing. Over the past several years, Kraft has
closed factories, cut jobs and divested brands to focus on areas like cookies and crackers,
pizza and healthier foods. Shares of Kraft rose 1.8 percent to $29.39 in premarket tradingfrom Tuesday's closing price of $28.88 on the New York Stock Exchange, while Kellogg
stock was not active. Kellogg, the maker of Rice Krispies and Eggo waffles, said net income
rose to 89 cents a share from 76 cents a year earlier. The results were far better than the 80
cents analysts had forecast.
09/2009 | Center of Research Excellence "eLearning 2.0" | 13

For Example: Assessing the Quality of Usergenerated Content

High Quality
Content

09/2009 | Center of Research Excellence "eLearning 2.0" | 14

WikiAnswers

1st fastest growing domainof the top 1,500 in the U.S.
in 2007 (comScore)
09/2009 | Center of Research Excellence "eLearning 2.0" | 15

Questions?

09/2009 | Center of Research Excellence "eLearning 2.0" | 16

For Example: Opinion Mining Can Improve theLearning Experience

09/2009 | Center of Research Excellence "eLearning 2.0" | 17

Telecooperation @ 30,000 ft.
Telecooperation :==targeted (= tele-) cooperation
between & among networked
people, computers & things
Research Area: Ubiquitous Computing
Research Fields:
1. Cooperation:

Prof. Dr. Max
Mühlhäuser

how to integrate (& provide synergy among) people, computers, things?

2. Interaction:
how to provide ease-of-use (users not at desktop, can hardly use keyboards& mice)?

3. Protection:
how to protect users despite UbiComp – how to protect them by means of
UbiComp?
09/2009 | Center of Research Excellence "eLearning 2.0" | 18

TK Projects (Excerpt) Public Security: SoKNOS German Ministry of Education and Research Knowl.Work/eLearning: GKel (TK: lead) & Peer2Peer Networks: Research Cluster
 German Research Foundation

 Internet of Services: Theseus - Texo German Ministry of Economics & Technology

 Ubiquitous Computing: Smart Products
 TK: lead Sc. Coordinator; European Union FP7, IP

 IT Security: CASED (TK: lead area 3)
 State of Hesse Public Security: ProTect (new; TK: lead)

ProTect
09/2009 | Center of Research Excellence "eLearning 2.0" | 19

 Industry

For Example: Paper-Centric Computing
 Paper remains central for knowledge work (Sellen/Harper 2003)
 Reasons: haptics, mobility, efficiency, navigation, structuring/indexingÆ Goal: ‚best of both worlds‘
 Here: Anoto Digital Pen & Paper: astounding resolution
 So far at TK group: collaborative annotation (Knowledge work)

09/2009 | Center of Research Excellence "eLearning 2.0" | 20

Uniform Interaction

PapierTabletop-Display

09/2009 | Center of Research Excellence "eLearning 2.0" | 21

Papier + Display

Cross-media Hyperlinks+
09/2009 | Center of Research Excellence "eLearning 2.0" | 22

Digital Paper Bookmarks

09/2009 | Center of Research Excellence "eLearning 2.0" | 23

Paper Centric Computing:
New Forms of Collaborative Annotation
1. Attach

2. Associate

3. Label(Steimle et al.: 2x best paper)

Computer GUI:

09/2009 | Center of Research Excellence "eLearning 2.0" | 24

For example: Digital Lecture Hall (DLH)
Virtual Blackboard
multiperspektiv-Video
Presentations-SW
Æ Recording

Smartboard,
PlasmaBoard…: ”eBoard”
LCD-Tablet as
e-overhead-projector &Control Unit

Learners-in-the-loop:- 4 types of devices- diverse interaction levels

09/2009 | Center of Research Excellence "eLearning 2.0" | 25

Internet

Recording:Download /Stream-For Example: Smart Products (Saeco)

09/2009 | Center of Research Excellence "eLearning 2.0" | 26

Graduate School „Quality Improvement ineLearing via Feedback-based Processes“ 16 scholarships by German Science Foundation (DFG) USP: Interdisciplinary „tandem-supervision“ Research focus for next phase: ROD Lernsettings (German
acronym) Feedback–loops on different granularity levels for quality management
 Openness (group size, age, location, previous knowledge, …)
 Dynamicity (learner‘s come and go, tools and technologies change, …)
 Furthermore: learning at university, on the job, in spare time grow tighter
together

09/2009 | Center of Research Excellence "eLearning 2.0" | 27

Most Recent ASC-Project on Ambient Learning
Multi-modal, multi-device access to lecture recordings
 Slides, audio & video stream
 E.g. time slider on handheld & ambient display
 Automatic topic identification and summarization

09/2009 | Center of Research Excellence "eLearning 2.0" | 28

ASC-Project Detail: Navigation in Large
Information Spaces („peephole metaphor“)

09/2009 | Center of Research Excellence "eLearning 2.0" | 29

Interested? Want to know more?

Don‘t hesitate and contact me:

www.cre-elearning.tu-darmstadt.de/burchardt

07.09.2009 | Center of Research Excellence "eLearning 2.0" | 30

What capabilities are emerging among the next generation?
Based on a comparative survey of Japan and South Korea
Keizo NAGAOKA
Waseda University
Abstract
The object of this study is to investigate new capabilities that are emerging
among the younger generation. I report the results of a comparative survey
conducted in Japan and South Korea. Although the two countries, on a global
scale, are geographically and culturally close to one another, we found that there
exist certain differences.
I would like to propose some capabilities; which will be emerging among
the next generation, and discuss generally in the worldwide vision.
We prepared 71 questionnaire items for the participants from Japan andSouth Korea. Seventy items were related to “abilities that have recently increased
among college students” and one question was “whether scholastic abilities havedecreased.” T-test and factor analysis were conducted on the results of allquestionnaire items.
The result the of t-test indicates that the Japanese participants felt thatscholastic abilities have declined compared to ten years ago. In contrast, theKorean students did not have this perception.
Analyzed were following factors:
For Japan: Factor 1: Self responsibility and social adaptability, Factor 2: Self
interest, Factor 3: Efficiency in action, Factor 4: Communication skills.
For Korea: Factor 1: Self responsibility and social adaptability, Factor 2:
Language and computer skills, Factor 3: Critical thinking, Factor 4: Self awarenessof one’s health and appearance.
Comparing the results of Japan and South Korea, we believe that it will bedifficult to counter the decline in scholastic abilities by dealing only with theinstitutional issue of relaxed (yutori) education, and that measures are needed toaddress the broader socio-economic reality associated with Japan’s lower birthrates.
Furthermore, while the Internet is viewed in Japan as improperly utilized and thus
associated with a negative image, this study suggests that the Internet can beperceived in a more positive light if properly utilized, as the case of South Korea
shows.

1.
2.

3.
4.
5.
6.

Introduction
Scholastic decline in Japan: Japan’s
relaxed (yutori) education
Questionnaire items for survey
Results (1) – factor analysis of 70 items
Results (2) – t-test of Item No. 71
Conclusions

1. Introduction

I report the results of a comparative
survey conducted in Japan and South
Korea.
How is the situation in other countries,
especially in Germany?

JAPAN
SOUTH KOREA
DEUTSCHLAND
USA

127,770,000(127,780,000)
48,456,000
82,314,900
295,896,000

2008(2007)
2007
2006
2005

Percentage of students going and existing
Higher Education (2&4 years), *incl. parttimer
JAPAN
SOUTH KOREA
DEUTSCHLAND
USA

56.2
101.6
35.4
53.2

67.1
*130.7
51.5
*90.5

2008
2007
2006
2005

GDP All Schools H.E.(=Public+Private)JAPAN 4.99
SOUTH KOREA 1.33
DEUTSCHLAND 3.26
USA 15.79

4.9

1.4(=0.5+0.9)

7.2

2.4(=0.6+1.8)

5.1

1.1(=0.9+0.2)

7.1

2.9(=1.0+1.9)

Tuition for H.E. (Japanese Yen)JAPAN
SOUTH KOREA
DEUTSCHLAND
USA

PublicPrivate(Num.%)

535,800

1,033,200(74.6)(max)827.600(max)1,058,200(81.8)(BonnU.)106.400/( 3.1)

689,000

2,904,000(25.5)

Around the world and since ancient
times the current generation of adults
often is concerned about the declining
abilities of the younger generation.
I am
Aristlepoorer scholastic
abilities!

worsemanners!

lesscreativeIt may be true that certain abilities haveindeed declined．
But, this must have been
compensated for by the developmentof other capabilities.
Ability decline may be qualitativechange to cope with changing times.
Human progress from ancient times
until today cannot be explained
otherwise.
It is more worthwhile to make efforts
to develop capabilities that are suited
to the coming age, not to criticize.

In Japan, the decline of scholastic abilities
among the younger generation has beena subject of debate for some years.
PISA has been conducted every three years
since 2000 by OECD, and each time its
results are announced.
They are received with great concern
depending on whether one’s country roseor fell in the international rankings.

The fall in Japanese standing is often
attributed to the adoption of the morerelaxed (yutori) education policy.

Yutori Education:
Education that aims at development of
individual talent rather than learning byrote.
Compared to 1992, the class hours ofjunior high school were reduced from3150 units to 2940 units in 2000. For
the elementary school, from 5785 units
to 5376 units. And so on.

South Korea is geographically close to
Japan. In common, developed ICT,
competitive school entrance
examinations.

These consisted of 70 items that related to“abilities that have recently increased
among college students”
and one question No.71 on“whether scholastic abilities have fallen.”The questionnaire took the following
format.
“Comparing yourself today and your imageof college students ten years ago, readeach of the following questions andindicate your answer by encircling one
item (1-5).”

Items 1-70

The participants and their numbers are as follows:
Japan: Undergraduate students at Waseda
University 123
female: 29, male: 88, unknown: 6==========================================
 South Korea: Undergraduate and graduate
students 163
1. Ewha Womans University - female: 81
2. Inha University - male: 51, female: 11
3. Korea University - male: 0; female: 20
male: 51, female: 112
Factor 1: Self responsibility and social
adaptability“item 64: I am more able to persevere andcarry things through to the end (factor
loading 0.781)”“item 8: My sense of solidarity withfriends/colleagues has strengthened (factor
loading 0.690).”
Factor 2: Self interest
Factor 3: Efficiency in action
Factor 4: Communication skills

Factor 1: Self responsibility and social
adaptability
Factor 2: Language and computer skills
Factor 3: Critical thinking
Factor 4: Self awareness of one’s healthand appearance========
Factor 1: “Self responsibility and social
adaptability” was common to both Japanand South Korea.

T-test was conducted on the results of allquestionnaire items 1-71. Here, we
discuss the results of item No. 71 only.

Item No.71 “whether scholastic ability
has declined?”

JAPAN

KOREA
1 Strongly Disagree, 3 Neither,
5 Strongly AgreeJapanese students :When we analyzed the written comments by
those Japanese students who answered
either “agree (4)” or “strongly agree (5),” wewere able to classify them into three groups.
i) Effect of relaxed (yutori) educationii) Effect of the Internet and other mediaiii) Effect of lower birthrates (decrease incollege-aged population) and consequentrelaxation of entrance exam standards.

i) Effect of relaxed (yutori) education.
No such policy has ever been adopted in South
Korea. This policy is a uniquely Japanese
phenomenon.
ii) Effect of the Internet and other media.
While the Internet is perceived in Japan as
contributing to the decline in scholastic abilities,
the Korean students felt that their computer
skills had expanded, as indicated by factor 2.
iii) Effect of lower birthrates.
In Japan, a widespread notion is that after enteringcollege, there is no longer any need for serious
studying. But in Korea maybe not.

In Japan, many of the participants feltthat the decline in scholastic abilities
was caused by: Introduction of the relaxed (yutori)
education policy,
 Spread of the Internet and other media,
 The easy entrance exam caused by thelower birth rates.
Meanwhile, in Korea:
 Capabilities resulting from the shift toan information society led to better
academic performance.

I thank Dr.Young Soo Kim (Ewha Womens University)
for her cooperation, and also, Shoichi Sugiyama,
student of Waseda university, In Woo Hwang, Sung
He Choi, Young Hwa Kim, graduate students ofEwha Womens University.

Lifelong and Lifewide eLearning
Fire Fighters and Forest Rangers in Rhinland-Palatinate
Ingo DAHN
Abstract
Learning at the workplace presents particular challenges for elderly employees. Also
lifewide learning, involving learning at spare time, is changing due to increased useof the potential of IT.
The presentation discusses ways how industry and public services canbenefit from the e-learning competence of universities to develop livelong andlifewide e-learning. This is exemplified with experience from two projects in theland of Rhinland-Palatinate for the training of forest rangers and voluntary firefighters.

Lifelong and Lifewide eLearning Firefighters and Forest Rangers inRhineland-Palatinate
Ingo Dahn
University Koblenz-Landau
Knowledge Media Institute Koblenz

Lifelong and Lifewide Learning• Lifelong Learning – learning in all phases of life
– Case: Forest rangers 50+• Lifewide Learning – learning in parallel– Case: Voluntary firefighters

How can public services profit from eLearning competency ofthe public universities – and conversely?

University Context• University Koblenz-Landau, Campus Koblenz– 6.500 students, mostly computer science and pedagogy– IWM Koblenz since 2001 – central eLearning institute• Research – Piloting – Support/Evaluation• Staff: 1.5/5.5/20/1 – pedagogs and computer scientists• Blackboard LMS, Online Assessements, Course records, Online
Community, ePortfolios, Video use• Pedagogic support, technical support, software development,

Lifelong Learning – ZEBIT Context• ZEBIT – Central IT management unit for wood andenvironment management in RLP• Central IT infrastructure FORSTNET• Regular training courses• Trainer background: Forest and IT• Learner background: Forest rangers (lower management),
average age: 50

ZEBIT Objectives
•
•
•
•
•

Introduce PCs in all forest offices
With special software
In parallel with ongoing changes in the work process
Make sure software is efficiently used in daily work
Design course in collaboration with IWM

The Project• IWM: Summative evaluation of learner needs by structured
interviews– Highly diverse attitudes and experiences– Desire to be involved in planning• Recommendation: Personalize training– Joint PC setup with hidden test
– Individual course plan, group work

• Advice during course design• Evaluation in FFH Diploma thesis

Lifewide Learning – LFKS Context• Training Group Leaders for voluntary firefighters• 14 days on place out of job payed by local community• Experienced trainers using Powerpoint, real devices - andVirtual Reality - „Generation Märklin“• Trainer background: Professional firefighters• Learner background: All professions

LFKS Objectives• Reduce required presence at LFKS– Reduce resistance of employers to free their staff for firefighter
qualification– Reduce costs for communities to pay wages during qualification– Simplify combination of learning with family and social life

• Attract younger and better qualified firefighters for
qualification as group leader

The Project• Didactic analysis of course, guided by IWM• IWM sets up infrastructure for authoring and LMS• Training the trainers: Use of media, online assessments,
online communication• Providing graphics and animations• Providing pre-test• Evaluation

Lessons Learned• Key to Success: Synergy of pedagogic (and technical)
competeny from university and partner• Qualifying the trainers is essential• IWM as Guide and Enabler, not as service provider• Benefits for partners:– Pedagogic advice, technical support– Qualification of staff• Benefits for University– New staff – new synergies– Realistic jobs for students

Lessons Learned• eLearning has huge potential for personalized learning– more efficient for inhomogeneous groups of learners– Lifelong and lifewide learning happens mostly in inhomogeneousgroups• Elderly learners have more – and different! – knowledge
which must be taken into account for ALL learning• The assumption that eLearning is less appropriate for
elderly is WRONG

A Basic Study on a Drawing-Skill Learning Support System
Mizue KAYAMA
Abstract
The purpose of this study is to develop a support system in drawing-learning withina networked environment. In this paper, we describe the results of potential
assessment for our system. Two assessment approaches are shown.
One is the possibility of a digital pen as a drawing-tool. The other approach is theeffectiveness of the drawing-learning support in the networked environment, basedon the reuse of the learner’s and/or expert’s drawing process. The drawing processmodel for supporting individual drawing-learning is also discussed.

A Basic Study ona Drawing-Skill Learning
Support System
Mizue Kayama, Takashi Nagai, Kazunori Itoh
Graduate School of Science and Technology, Shinshu University

Types of Drawing Learning

RecordReplayRefer

Recording a Drawing-Process with the DigitalPen• Function– Automatically recording sets oftime and pressure per stroke.

• Advantages– Concentrate in drawing– Direct relation with drawing
process and drawing work
– Mobility

Some Specifications of the Digital Pen

Proposed Learning Environment

AdvicesDrawing
Process
Data
Learner

Tutor
Drawing
Process Model

Drawing Process Model

Seven
Steps

Three
PhasesSix
Parameters

Drawing Process Model

Key Points of Drawing LearningThree Phases

Shape

Tone

TextureThree Phases

Phase A
Shape

Phase B
Tone

Phase C
TextureSeven Steps of Drawing ProcessSix Parameters of Drawing Phases

Individual Learning Support
Functions• Record/Replay/Refer drawing process• Analyzing learner’s drawing process– 6 parameters• Showing examples of experts’ and otherstudents’– Drawing process– Final works• Giving some advises about drawing techniques

Conclusions and Future Works• Proposed a support system for beginners indrawing– Using digital pen– Recording and reusing drawing process• Drawing process model– Three phases / Seven steps / Six parameters• Collecting drawing data
– Experts’ / Beginners’– Various kind of motifs• Refining the drawing process modelFakultätsname XYZ Fachrichtung XYZ Institutsname XYZ, Professur XYZSupporting Self-Regulated Learning of ScientificConcepts through Interactive Learning Tasks –Product and Process Findings
Felix Kapp, Hermann Körndle, Susanne Narciss & Antje Proske
Psychology of Learning & Instruction, TU Dresden, Germany

Berlin, 11.09.2009

Agenda Self-regulated learning Supporting SRL through interactive learning tasks
 Method Results
 Conclusion

Self-Regulated Learning
Self-Regulated Learning (Zimmerman, 2000):sustainmotivation

implement
techniques andstrategies

set goals

evaluatelearning
progresschoosetechniques andstrategies
In case of low achievement:
correct strategies

Interactive Learning Tasks
Components of interactive learning tasks (Körndle, Narciss & Proske, 2004):

Content

Content

Task analysis

learning
goals

Knowledge
Space

FormatCognitive operations

distractors

Interactivity- Feedback- hints

Learning tasks

Interactive Learning Tasks and SRL

Interactive Learning tasks in CBLEs can facilitate : the learner‘s retention and understanding of learning material
 the learner‘s knowledge organization and application
 the learner‘s assessment of his progress of knowledge and skill acquisition
Interactive Learning tasks and SRL (Körndle, Narciss & Proske, 2004). :Forethought
Phase• show demands• activate previous knowledge• guide attention

Learning Tasks• evaluate achievement• evaluate used strategies
EvaluationPhase• learn and practice• use hints
Performance
PhasePurpose of the StudyInvestigate the effects of interactive learning tasks onlearners‘ achievement in acquiring scientific concepts

Gain information about how interactive learning tasks
support the process of self-regulated learning.

MethodSample: 20 university students (University of Applied Science
Neubrandenburg, Germany)

Instructional context: Early education, scientific concepts(e.g. Piaget‘s stages of cognitive development)

Instructional scenario: Blended learning class, students
were supposed to study relevant texts at home to prepare forthe following presence classProcedure: 4 months, 6 presence classes and self-regulated
learning phases

Material
Learning Management System (University of Applied Science Neubrandenburg):

Material
Interactive Learning Tasks:
Progress Bar

Item StemDistractors(MC Format)

Hint Button

Procedure

Learning process
Achievement- semi-structured interviews- Log-File Analysis

Textbook +no tasks
10 tasks

10 tasks

15 tasks

5 tasks

8 tasks

Online learning
environmentCG

12 tasks

EG
Knowledgetest
Presence class

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6- 15 Items- MC andshort answer

Results
Learning achievement:

14 students worked on the knowledge test in the evaluation session

The experimentalgroup (n = 8, M =9.9, SD = 2.1)
showed a significant
higher achievement(t(14) = -3.27,
p<.01, d = 1.54)
than the control
group (n = 6, M =5.7, SD = 2.7).

Results
Learning process:Log files:
Evaluation session:Mean working time for set of 12 tasks: 12.1 minInteractive learning tasks solved correctly: 6.7 out of 12

All sessions:

Average working time on learning tasks: 53 minutes

Three students did not use the learning tasks

Several students worked twice on single sections

Hints were hardly used (only 5%).

Results
Learning process:Interviews:
 Several students of the EG had read the text twice - once
before working on the tasks and once after getting the
feedback from the interactive learning tasks.
 Students stated that working on the 12 tasks was done in
relative short time.
 Benefited from the offer
 Some students of the control group reported that they only
glanced over the text.
 The teacher realized that students this semester were better
prepared (concerning all six presence sessions).

Conclusion



A higher achievement of students uses learning tasks while
studying texts.



Results suggest that achievements are based on feedback on thelearning process provided by the learning tasks as well as active
processing of the information while working on the tasks.

Further research on interactive learning tasks should address inmore detail the cognitive and motivational functions in selfregulated learning, which can be supported by providing suchtasks.

Thank You for Your attention!

References

Artelt, C., Demmrich, A. & Baumert, J. (2001). Selbstreguliertes Lernen. In J. Baumert, E. Klieme, M. Neubrand, M.
Prenzel, U. Schiefele, W. Schneider, P. Stanat, K.-J. Tillmann & M. Weiß (Hrsg.), PISA 2000. Basiskompetenzen vonSchülerinnen und Schülern im internationalen Vergleich (S. 271-298). Opladen: Leske + Budrich.
Hamaker, C. (1986). The effects of adjunct questions on prose learning. Review of Educational Research, 56, 212-242.
Klauer, K. (1987). Kriteriumsorientierte Tests. Göttingen.: Hogrefe.
Körndle, H., Narciss, S. & Proske, A. (2004). Konstruktion interaktiver Lernaufgaben für die universitäre Lehre. In D.
Carstensen & B. Barrios (Hrsg.), Campus 2004. Kommen die digitalen Medien an den Hochschulen in die Jahre? (S. 5767). Münster: Waxmann.
Narciss, S. (2007). Feedback strategies for interactive learning tasks. In J.M. Spector, M.D. Merrill, J.J.G. van Merrienboer,& M.P. Driscoll (Eds.), Handbook of Research on Educational Communications and Technology (3rd ed., pp. 125-144).
Mahaw, NJ: Lawrence Erlbaum Associates.
Narciss, S. (2006). Informatives tutorielles Feedback. Entwicklungs- und Evaluationsprinzipien auf der Basis
instruktionspsychologischer Erkenntnisse. Reihe Pädagogische Psychologie und Entwicklungspsychologie (Band 56).
Münster: Waxmann.
Narciss, S., Proske, A., & Körndle, H. (2007). Promoting self-regulated learning in web-based learning environments.
Computers in Human Behavior, 23(3), 1126-1144.
Zimmerman, B.J.& Campillo, M. (2003): Motivating self-regulated problem solvers. In: Davidson, J.E.& Sternberg, R.J.
(Eds.): The nature of problem solving. New York: Cambridge University Press

Promoting Self-Regulated eLearning through Prompts
Maria BANNERT
Chemnitz University of Technology
Educational Media (Germany)
Abstract
Research in the field of self-regulated learning reveals that many learners havedifficulties in performing strategic and metacognitive activities, such as analyzing,planning, monitoring, and evaluating, in effect resulting in lower learning outcomes.
Hence, the key purpose of this research is to find appropriate scaffolding formetacognitive reflection when learning with modern computer-based learning
environments. It is assumed that prompting students for metacognitive reflection
will affect the learning process by engaging students in more metacognitive
behavior leading to better learning performance. Design and major results fromthree experiments where students of the experimental groups were supported bydifferent metacognitive prompting measure are described. The results of learning
processes and outcomes confirm the positive effects of all three support measures.
However, their specific influence varies significantly in size. Implications for thedesign of metacognitive support to improve self-regulated e-learning are discussed.

Promoting Self-Regulated eLearning
through Prompts
Maria Bannert
Educational Media
Chemnitz University of Technology, Germany

Overview{Self-Regulated Learning{

Metacognitive Prompting{

Experiments: Procedure and Main Results{

Summary and Conclusions

11.09.2009 – JDZBMaria Bannert

2Self-Regulated Learning

Behavior
Cognition
Motivation
e.g. Albert et al. 2009,
Azevedo, 2009
Benz & Schmitz, 2008
Boekarts et al, 2000
Pintrich, 2000
Narciss & Körndle, 2007
Winne, 1996
Zimmerman, 2002
11.09.2009 –IATEL
19.06.2009:JDZBMaria Bannert

3

Metacognitive Activities
What to do?
Which resources
do I have?

What do I
want to learn
actually?

How to proceed?
How long will ittake?

Behavior
Cognition

Do I remember
and understandthe topics
learned?
Did I reach thelearning goals?

Where to findinformation?
Information really
relevant?

Motivation

Reading, memorizing,elaboration of extracted
information
11.09.2009 –IATEL
19.06.2009:JDZBMaria Bannert

4

Metacognitive Prompting (Bannert, 2009){

Prompts stimulate and support students’ metacognitivereflection, e.g. by prompting studentsz

to give reasons for their actions(e.g. Lin & Lehman, 1999; Bodvarsson, 2005)z

to generate hypotheses(e.g. Veenman, 1993; Thillmann et al, in press)z

to practise with certain learning questions / techniques(e.g. Ge et al, 2005; Kaufmann et al, 2008)

11.09.2009 – JDZBMaria Bannert

5Experimental Studies

Exp. 1

EG = Reflection Prompts (n=24)
CG = without (n=22)

Exp. 2

EG = Metacognitive Prompts (n=20)
CG = without (n=20)

Exp. 3

EG = Training + Metacognitive Prompts (n=20)
CG = without (n=20)

11.09.2009 – JDZBMaria Bannert

6

Screenshot

11.09.2009 – JDZBMaria Bannert

7

Reflection Prompts

In Experiment 1:{ Students (EG) were prompted
at each navigation step in a hypermedia system
to give reasons why they choose this specific node{

Why do you choose this node?
Please say out loud all reasons for this node selection.

11.09.2009 – JDZBMaria Bannert

8

Reasons for Node Selection - Examples„because I don‘t know where to go“
adequate strategic reasons„I don‘t know“„to go back“

inadequate strategic reasons“to get an overview”“to get an example”“to deepen my understanding”“to repeat”“to check my understanding”„because I am interested
in this topic“and other

11.09.2009 – JDZBMaria Bannert

9Screenshot 2

11.09.2009 – JDZBMaria Bannert

10Design of Metacognitive Prompts
For example- glancing at task and material- writing down sub-/goals- planning ongoing procedure(time and sequence)n At the beginning of learning :z Orientationz Goal Specificationz Planning

For example- use menu and index- judge relevance- test comprehension- check plano During learning :z Search and Judgementof Informationz Elaborationz Monitoring/Regulation

For example- make a summary- check learning goals

p At the end of learning :z Evaluation
11.09.2009 – JDZBMaria Bannert

11Research Questions
Does metacognitive prompting{ … influence the learning process ?
(by engaging students in more metacognitive behaviour?){… increase learning performance ?

{Are there individual differences ?
(prior knowledge, cognitive ability, metacognition, motivation,
self efficay)

11.09.2009 – JDZBMaria Bannert

12Design and Procedure

Lerner‘s
Prerequisites

EG:

Prior Knowledge

Introduction
Hypermedia+ Metacognitive
Prompts

Learning with
Metacognitive Prompts

Introduction
Hypermedia

Learning without
Metacognitive Prompts

Videotaped

Learning Outcome
RecallKnowledge
Transfer

Verbal Intelligence
Metacognition
Motivation
Self Efficacy
1 week before

CG:

Videotaped

Learning Outcome
RecallKnowledge
Transfer

Individual sessions lasting 1.5 – 2 hours

Exp. 1 = 46 University students (Psychology, Education); age = 24.3 (5.2); female = 84.8 %Exp. 2 = 40
age = 22.1 (3.3); female = 67.5 %Exp. 3 = 40
age = 23.0 (3.6); female = 72.5 %11.09.2009 – JDZBMaria Bannert

13

Learning Performance
EG = with prompts
CG = without

Exp 1:
reflection prompts

Exp 2:
metacognitive prompts

Exp 3:
training +metacognitive prompts
11.09.2009 – JDZB

RecallKnowledge

Transfer

RecallKnowledge

Transfer

p=.07, d=.43

Knowledge

Transfer

p=.03, d=.58

RecallMaria Bannert

p=.03, d=.54

14Summary{{

Learning Process: more metacognitive activities
Learning Performance:z Significant effect on transfer performance- Exp.1: reflection prompts, d = 0.54
- Exp.2: metacognitive prompts, d = 0.43
- Exp.3: training + metacognitive prompts, d = 0.58{

Compliance with Support:
even greater effects: 1.09 < d < 1.93 !

11.09.2009 – JDZBMaria Bannert

15

Conclusions{{

Greater effect sizes
z more complex learning environmentz long-term interventions / follow up
z adaptive prompts, e.g. metacognitive avatars

Need for scaffolding student's metacognitive activities
and self-regulated elearning

11.09.2009 – JDZBMaria Bannert

16Thank you for your Attention

maria.bannert@phil.tu-chemnitz.de
www.tu-chemnitz.de/phil/elearning/

11.09.2009 –IATEL
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17

A Study for Exploration of Relationships between Behaviors andMental States of Learners For an Automatic Estimation System
Tatsunori MATSUI, Yuki HORIGUCHI, Kazuaki KOJIMA
Faculty of Human Sciences, Waseda University
Abstract: It is an important task to implement an e-learning system that can
automatically detect changes of learners’ mental states by observing their behaviorsin learning activities. In this study, we conducted an experiment to explore
relationships between mental states and behaviors of a learner on our experimental
tools designed along with an assumption of a learning environment with an elearning system. We focused on mouse and face movement as the behaviors. The
results of the experiment revealed some features about the behaviors and themental states.
Keywords: e-leaning system, automatic estimation, mental states, mouse tracking,face movements
Introduction
Current e-learning systems are classified into two types: synchronous andasynchronous systems. In the former systems, learners can learn anytime andanywhere without being under any time and spatial constraints. However, teachers
cannot observe the learners’ behaviors on the system to estimate theirunderstanding. The latter systems allow teachers to observe learners, but such
systems impose time constraint on the teachers and learners because they have towork simultaneously. Therefore, it is an important task to implement anasynchronous system that can automatically detect changes of the learners’ mental
states by observing their behaviors. Here, we call such a system an estimation
system.
Several studies have addressed the implementation of an asynchronous elearning system that estimates the learners’ mental states, such as reaching animpasse in problem solving or impressions of problem difficulties perceived bylearners. Ueno’s estimation system has succeeded in detecting unusual states oflearners by measuring response time required to solve each problem (Ueno, 2007).
However, it cannot specify sources that cause unusual responses in problem
solving processes because it is based on response time. An estimation system by
Nakamura and his colleagues can detect sources of unusual behaviors based onlearners’ responses (Nakamura, Akamatsu, Kuwabara, & Tamaki, 2002). To detect
the sources, it needs learning contents that embed particular materials, such as
buttons to present hints. A system by Nakamura, Kakusyo and Mino (2007) judges

whether or not learners find problems difficult based on behavioral data: eye andface movements acquired through a stereo-camera, and interval time among input
operations on the system. Because the specific device stereo-camera is required, it
may be difficult to actually adapt the system to practical e-learning environments.
In order to adapt an estimation system into ordinary e-learning
environments, it should require no specific devices. In our previous study(Horiguchi, Kojima, & Matsui, 2008), we have proposed an estimation system that
detects unusual behaviors during problem solving based on velocity of mouse
movements. Although the system can specify sources of unusual behaviors inproblems to some extent, we consider it needs further study to refine its model ofthe behavioral detection. According to the concept “no specific devices” describedabove, we conducted an experiment that examined relationships between behaviors
and mental states of a learner in order to expand the detection model for
implementation of a system that possesses a more accurate estimation.

A Study for Exploration of Relationships between Behaviors
and Mental States of Learners for an Automatic Estimation
SystemTatsunori Matsui, Yuki Horiguchi and Kazuaki Kojima
Faculty of Human Sciences,
Waseda University, Japan

Agenda• １．Introduction• ２．Experiment 1• ３．Experiment 1• Results & Discussions• ４．Experiment 2• ５．Experiment 2• Results & Discussions• ６．Conclusions

１． Introduction

１． Introduction

Current e-learning systems

Synchronous

Asynchronous１． Introduction

Current e-learning systems

Synchronous

Asynchronous

Estimation System
Can’t estimate
Time constraintarners
learners’ understanding
Automatically detects changes of learners' mental states by observing their
behaviors.

１． Introduction

Estimation systems to detect unusual behaviors
Using response time
Cannot specify sources that cause unusual responses
in problem solving processes

Based on a interval time between operations
Needs learning contents that embed particular materials,
such as buttons to present hints

Based on behavioral data and interval time among input operations
Needs a specific device

Based on velocities of mouse movements
Needs models for behavioral detection

１． Introduction

Concept

Real Time Estimation!?

No Specific Operations
No Specific Devices

１． Introduction

Purpose of the current study

Examine relationships between behaviors
Real Time Estimate
and mental
NostatesSpecific Actionsof a learner in order
to expandthe
No Specific
Devices
detection model.

!?

２． Experiment 1

２． Experiment 1

PurposeTo examine relationships between
behaviors and mental states of a learner

Collected with experimental
tools

Obtained fromthe learner's protocol data

２． Experiment 1

Learning Contents
Answering a question
with multiple choices
Mouse pointers tracks depend on
representation of learning contents,
such as textual sentences or figures [Horiguchi
et al. 2008]

Reading English sentences (only textual sentences)
No scroll operation
No keybord operation
Only mouse operation

２． Experiment 1

Behavioral Data of Learner
Estimation of learners’ impressions of problem difficulties based onterminal features and facial features[Nakamura et al. 2007]

Mouse Data
Face Data

Laptop computer with a embedded
web camera

２． Experiment 1

Behavioral Data of Learner
Mouse Data

Positions {x, y}States of a mouse button (on, off)
Sampling-rate：60Hz

Face Data
Used OpenCV
for the web camera image analysis

Positions {x, y}
Inclination of face within {θ}Distance between face and monitor {w}Sampling-rate：5〜7Hz

２． Experiment 1

Mental State Data of LearnerStep. 1

Problem solving with learning interface
Think aloudStep. 2

Answering interview
Retrospective report

Step. 3Making a sheet of mental change

A?
A?...
...D?
D?...
...
I Idon't
don'tknow
knowthisthisword...
word...
I Ihavehavenonoidea...
idea...

３．Experiment 1 Results & Discussions

３． Experiment 1 Results & Discussions

Experiment Information

1 Lerner 4 Trials*（4 training trials）* 1 of 4 was abandoned because the learner was exhausted

３． Experiment 1 Results & Discussions

Classifications of the Mental States

A?
A?...
...D?
D?...
...
I Idon't
don'tknow
knowthisthisword...
word...
I Ihavehavenonoidea...
idea...

...14 periods in 3 trials

Periods of impasses (get stacked)

３． Experiment 1 Results & Discussions

A Relationship between
Speeds of Mouse Movements and Impasses
1．Speeds of mouse movements wereslower in periods of impasses.

Whole processes

Periods of impasses

３． Experiment 1 Results & Discussions

Features of Mouse Tracking

２．Words or sentences the mouse pointed consistent with those thelearner reported as sources of the impasses“a“acenterfold
centerfoldfor
forPopular
PopularMechanics”
Mechanics”“Eleanor“EleanorLambert”
Lambert”“concurrence“concurrenceofofopinion
opinionofofthe
thefashionfashionindustry
industryofofthe
theworld”
world”In all 14 periods of impasses

３． Experiment 1 Results & Discussions

A Relationship between
Hesitations and Face Movements

３．The learner’s face kept away from the monitor in periods ofimpasses

３． Experiment 1 Results & Discussions

Conclusions

1. Speeds of mouse movements were slow in periods of impasses.
2. Words or sentences the mouse pointed consistent with those thelearner reported as sources of the impasses
3. The learner’s face kept away from the monitor in the periods ofimpassesa centerfold for Populara centerfold for Popular
Mechanics
Mechanics

EleanorEleanorLambert
Lambertconcurrence of opinion of the fashion industry
concurrence of opinion of the fashion industryof the worldof the world

３． Experiment 1 Results & Discussions

Sampling Time for Computing Mouse Speeds

5.0 sec.

Sampling time

3.0 sec.

1.0 sec.
0.1 sec.
Speeds of Mouse

SD

Most appropriate: 1.0 sec.

３． Experiment 1 Results & Discussions

Sampling Time for Computing of Speeds of Face Movements(away from the monitor)

5.0 sec.

Sampling time

3.0 sec.

1.0 sec.
0.1 sec.
Speeds of Face Movements

Most appropriate: 0.5〜1.0 sec.

３． Experiment 1 Results & Discussions

Features of Mouse Tracking & Face Movements

I Idon't
don'tknow
knowthisthisword...
word...

IsIsthisthiscorrect?
correct?

Face

Mouse

5 sec.

Time

Periods of impasses

about 5〜10 sec.

３． Experiment 1 Results & Discussions

Automatic Estimation Model
Detecting Changes of Speeds of Mouse Movements⇒When the speeds are kept less than a thresholdover five consecutive seconds&
Detecting Changes of Speeds of Face Movements⇒When the speed is less than a threshold

Succeeded in detecting Periods of Impasses: 62%（ 9/14 ）４． Experiment 2

４． Experiment 2

Difference Between Experiment 1 and 2

Experiment 1
Learner was asked :All mental states

SimplifiedExperiment 2
Learner was asked :When finding impasse(Level of an impasse)

４． Experiment 2

Definition of Level of an Impasse
Positive behaviors

Negative behaviors- In problem solving -- Not in problem solving -Usualness
Level of an Impasse

Think

Impasse (Stall)Omission
Tiredness
Lapse in concentration
Break etc...

５． Experiment 2 Results & Discussions

５． Experiment 2 Results & Discussions

Experiment Information

1 Learner* 3 Trials（2 Practices）*Another learner５． Experiment 2 Results & Discussions

Levels of an Impasse Distribution

Usualness

Think

5 periods in 3 trials（Ave. 25 sec.）

Impasse (Stall)

3 periods in 2 trials（Ave. 93 sec.）

５． Experiment 2 Results & Discussions

Features of Speeds of Mouse Movements
Usualness
Speedsof
Mouse

Impasse (Stall)
Speedsof
Mouse
Period of impasse :145 sec.

５． Experiment 2 Results & Discussions

Compare Experiment 1 with 2"I"Idon't
don'tknow
knowthisthisword”
word”

Experiment 1

Speedsof
Mouse

Experiment 2

Speedsof
Mouse“I“Ihave
havenonoideaidea
which
whichisisthe
thecorrect
correctanswer”
answer”

５． Experiment 2 Results & Discussions

Compare Experiment 1 with 2

Behavior
Behaviorofofcomparison
comparisonamong
among
choices
choices“A?...B?.....C?...”“A?...B?.....C?...”
Experiment 1

SpeedsofMouse５． Experiment 2 Results & Discussions

Features of Speeds of Mouse Movements
Experiment 1
Speedsof
Mouse

Experiment 2

Speedsof
Mouse

Behavior characteristic of comparison among choices
Can we find out periods of impasses from these patterns?

５． Experiment 2 Results & Discussions

Supplementation (Pattern of Negative action)
Concentrated in problem solving
Diversified
Diversified

Lapse in concentration
Stationary
Stationary

６．Conclusions

６．Conclusions

Conclusions

PurposeExamined relationships between behaviors and mental states ofa learner in order to expand the detection model.

Results➡Change speeds of mouse and face movements
Detect Periods of Impasses: 62%➡Behavior characteristic of comparison among choices

Future➡Can we estimate period of impasse with these patterns?

６．Conclusions

Future Work
Further experimentswith a number of learners

Establish estimation models
Method of detect behavior characteristic⇒Using Bayes prediction

Implement Build an Estimation System
Immediately gives learners feedback
during problem solving

The Concepts of Competences and Self-Regulation in Teacher
Training and Life Long Learning
Dietrich ALBERT
University of Graz & Graz University of Technology

For teaching as well as for (life long) learning the concept of competences is ofinherent importance. (Action-)competences are the basis for adaptive, flexible, andsituation-related behavior and problem solving, and they are necessary for handling
unknown, new situations. Competences are not directly observable entities, which
can be assessed by observing behavior and evaluating performance. A framework
for modelling both competences and performances is the Competence-based
Knowledge Space Theory (CbKST). A special type of competences and skills is
required in self-regulated (life long) learning, which gives control of the individual
learning process to the learner him- or herself. Self-regulated learning processes canbe supported by appropriate software tools, which have been developed on thebasis of CbKST within the iClass-project (EU-FP6-IP) by the Cognitive Science
Section of the University of Graz.

Scaffolding Self-Regulated Learning on the World Wide Web
Bastian F. BENZ
Educational Psychology
University of Technology Darmstadt

Even though nowadays the World Wide Web is used for learning, originally it has
not been created for this purpose. Hence, users are confronted with a very highdegree of freedom when learning on the www. In order to foster the quality of thelearning process, as well as the learning outcome, we created an extension of theFirefox web browser. Based on current models of self-regulated learning, eightprocesses, which have been defined as being crucial for learning on the www aresupported in an indirect or direct way. The evaluation of the extension showed that
fostering those eight crucial processes enhanced learners’ involvement in goal
setting activities and the definition of relevant learning goals before actually starting
the search. Towards the end of the search reflection processes were enhanced. A
positive effect on performance could be found for the easy questions of anachievement test. Direct support, which provides higher levels of support, wassuperior to indirect support. The next step of our research will be to optimize thesupport, which is provided during the action of searching in order to help learners
to pursue previously set goals and thereby to reach higher gains in achievement
measures.

Scaffolding Self-Regulated Learningon the World Wide Web

Dipl.-Psych. Bastian F. Benz
Prof. Dr. Bernhard Schmitz
Educational Psychology
University of Technology Darmstadt

M. Sc. Doreen Mann
Dipl.-Inf. Philipp Scholl
Dr. Christoph Rensing
Prof. Dr. Ralf Steinmetz
Multimedia Communications Lab
University of Technology Darmstadt

Learning on the World Wide Web
 The World Wide Web Nonlinear & unstructured environment
 Not designed for learning Learning on the World Wide Web Learners are confronted with high degrees of freedom, e.g.
 Navigate in the environment
 Judge the trustworthiness of sources (epistemology)
 Decide when to stop searching Organize and learn findings

 Related research: Fostering learning within hypermedia environments
 Azevedo and colleagues
 Adaptive human scaffolding Bannert and colleagues• Metacognitive prompts
 Winne and colleagues• gStudy software
17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 2

Which processes should be fostered?
Self-Regulated Learning – Metacognitive Processes
Preaction-Goal setting-Planning

Postaction

Action-Reflection-Self-Monitoring-Process-Regulation(Boekaerts, 1999; Pintrich, 2000; Schmitz & Wiese, 2006; Winne & Hadwin, 2008; Zimmerman, 2000)
17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 3

Which processes should be fostered?
Specifying crucial processes for the www!
Preaction-Goal setting-Planning

Action-Self-Monitoring-Process-Regulation

1. Identification of knowledge gaps
2. Goal oriented approach
3. Definition of relevant goals

4. Goal orientation during action
5. Finding relevant pages
6. Importing relevant information
7. Assigning relevant information to relevant goal

Postaction-Reflection

8. Learning relevant information(9. Recall of relevant information)
17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 4

How to foster processes?
Direct vs. Indirect Support
 Direct support
 Instructing Prompting Low degree of freedom
 Indirect Support
 Design of the learning environment Providing functions
 High degree of freedom(Friedrich & Mandl, 1992)

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 5

Three Versions of ELWMS III
Supported processes

CG

Identification ofknowledge gaps

EG2 - Direct

Feedback on pretest

Goal oriented approach

Folder - Function

Definition of relevant
goals

-

Goal orientation during
action-Finding relevant pages-

Importing relevant
information-

Assigning relevant
information to relevant
goal-

Learning relevant
information

EG1 - Indirect

5 minute warning
Overview,
knowledge net

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 6

ELWMS-Sidebar – Version CG

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 7

Three Versions of ELWMS II
Supported processesCG

EG1 - Indirect

Identification ofknowledge gaps

Feedback on pretest

Goal oriented approach

Folder - Function

Goal-Function

Definition of relevant
goals

-

-

Goal orientation during
action-Goal-Activation - Function

Finding relevant pages--

Importing relevant
information--

Assigning relevant
information to relevant
goal

-

-

Overview,
knowledge net

5 minute warning
Overview,
knowledge net

Learning relevant
information

EG2 - Direct

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 8

ELWMS-Sidebar – Version EG1

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 9

Three Versions of ELWMS III
Supported processesCG

EG1 - Indirect

Identification ofknowledge gaps

EG2 - Direct

Feedback on pretest

Goal oriented approach

Folder - Function

Goal-Function

Prompt to set goals

Definition of relevant
goals

-

-

Prompt to set relevant goals

Goal orientation during
action-Goal-Activation - Function

Prompt to activate goal

Finding relevant pages

-

-

-

Importing relevant
information--

Prompt to check relevance of
information

Assigning relevant
information to relevant
goal

-

-

Prompt to check fit

Overview,
knowledge net

5 minute warning
Overview,
Prompt to prepare forknowledge net
posttest,
overview, knowlege net

Learning relevant
information

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 10

ELWMS-Sidebar – Version EG2

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 11

Model of Adaptive Learner Support for the
Enhancement of Learning Quality
Precondition•Learner characteristics•Traits•States•Situation

Scaffold•Crucial processes•Indirect vs. Direct

Learning process•SRL/Metacognition•States

Performance•Knowledge Gain
•Structure Research Questions
1. Does the scaffolding of our eight crucial processes enhance the quality of thelearning process?
a)

2.
a)

Direct vs. Indirect support

Does the scaffolding of our eight crucial processes enhance the quality of thelearning outcome?
Direct vs. Indirect support

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 12

Design of the Study
Day 1
90 minDay 2
120 minScaffolds

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 13

Post-Test - Psychometrics

Pre-Test – Classical Antiquity

38

Introduction of Tool

36

Pre-Test - Psychometrics

34

Post-Test – Classical Antiquity

Search and Learning Phase
45 min Wikipedia

Results Based on Log Files –Crucial Processes
Preaction-Goal setting -Planning •Viewing goals/folders
2. Goal oriented approach:F(2, overview/knowledge102) = 6.12, p < .01, net
η = .33 •Viewing
 No scaffolding vs. scaffolding: t(102)=-1.85, p < .05 (1-tailed), r = .18
 Indirect vs. direct support:t(102)=-3.18,< .01 (1-tailed), r = .30
 During
minutep5-40

3. Definition of relevant goals : F(2, 102) = 3.94, p < .05, η = .27 •Re/entering
relevant
pages r = .20
 No scaffolding vs. scaffolding:t(102)=-2.10,•Creatingp < web.05goals/folders(1-tailed),
 Indirect vs. direct support: t(102)=-1.85, p < .05 (1-tailed), r = .18

 During minute
5-40
 In
first 5 minutes

Action-Self-Monitoring -Process-Regulation 

4. Goal orientation during action: F(2, 102) = .80, p > .05, η=.12 •Viewing relevant goals/folders
5. Finding relevant pages: F(2, 102) = 1.06, p > .05, η = .14 •Viewing relevant
ressources•Creatingrelevant goals/folders
6. Importing relevant•Opening
information:
F(2,= .413, p > .05, η = .09 
relevant102)
ressources
7. Assigning relevant informationtoInrelevantgoal: F(2, 102) = 3.13,
first 5 minutes
p < .05, η=.24  In last 5 minutes
 Indirect vs. direct •Importing
support: t(102)=2.10,< .05 (1-tailed), r = .20
relevantp ressources

Postaction-Reflection  During minute 5-40
8. Learning relevant information: F(2, 102) = 1.092, p > .05, η = .14  Reflection: F(2, 102)•Restructuring= 8.05, p < .01, ηressources= .40– ressourcep <fit.01 (1-tailed), r = .27
 No scaffolding vs.•Goal/folder
scaffolding: t(102)=-2.83,
 Indirect vs. direct support: t(102)=-2.82, p < .01 (1-tailed), r = .27

 During minute 5-40

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 14

Performance: Analysis of Goal/Folder –Ressource Structures
 Calculating a value for the quality of the created goal/folder – ressource structure No significant group differences F(2, 102) = 1,344, p > .05, η = .16

 Distinguishing between easy and difficult questions
 No significant group differences for difficult questions
 F(2, 102) = .163, p > .05, η = .06

 Significant group differences for easy questions
 F(2, 102) = 3.83, p < .05, η = .26
 No scaffolding vs. scaffolding: t(102)=-1.907, p < .05 (1-tailed), r = .19
 Indirect vs. direct support: t(102)=-1.990, p < .05 (1-tailed), r = .19

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 15

Summary•Extension to the Firefox that enhances the quality of searching andlearning on the www•Log files to evaluate the employment of SRL processes (objective)•Results:

Preaction

Support of 8
crucial processes

Indirect vs. direct support•Goal oriented approach•Goal oriented approach•Definition of relevant goals•Definition of relevant goals

ActionPostaction

Performance•Assigning relevant information
to relevant goal
•Reflection•Reflection•Created structure
for easy questions•Created structure
for easy questions

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 16

Future Perspectives

 Support during the action of searching and learning has to be optimized
 Performance!
 How can we improve indirect support? Relevance for praxis!
 Adaptivity: When direct, when indirect support?

17. September 2009 | JDZE 2009 | Scaffolding Self-Regulated Learning on the World Wide Web | Bastian Benz | 17

Thank You Very Much!
Questions?

Dipl.-Psych. Bastian F. Benz
Prof. Dr. Bernhard Schmitz
Educational Psychology
University of Technology Darmstadt

Benz@psychologie.tu-darmstadt.dewww.paedpsy.psych.tu-darmstadt.de

Multi-Modal Competence Assessment Based on Users’
Performance on Complex Tasks
Cord HOCKEMEYER
University of Graz & Graz University of Technology, Austria

Knowledge Space Theory (KST) and its competence-based extension (CbKST) are
well-established frameworks for the adaptive teaching and testing of knowledge
and competences. Recent technological developments allow an increasing use ofsimulations, virtual realities, etc. for technology enhanced learning. These learningtechnologies require adequate instruments for assessing the learners’ individual
learning progress.
Multi-modal assessment gaining information from different types ofsources can be realized with CbKST, thus covering the various sides of current
computer-based learning.

Multi-Modal Competence
Assessment Based on Users’
Performance on Complex Tasks
Cord Hockemeyer
Cognitive Science Section
Department of Psychology, University of Graz
Knowledge Management Institute, Graz University of Technology

Acknowledgements
This presentation reports results from several
projects funded by the European Commission

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Overview• Adaptive competence assessment in
CbKST• Microadaptivity and non-invasive
assessment• Multi-modal assessment

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Adaptive Competence Assessment in
CbKST• Knowledge Space Theory (KST)
structures items of knowledge by
prerequisite relations• Competence based KST clearly
distinguishes between abstractcompetences and concrete objects (testproblems, lessons, …)• Prerequisite structures serve as a basis foradaptivity
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Adaptive Competence Assessment in
CbKST• Mimicking a private teacher:– Starting with a question of medium difficulty– Subsequent questions are more or lessdifficult, depending on the previous answers• Non-numerical testing, i.e. testing what aperson knows (vs. how much)• A learner’s competence state is given by
the subset of competences s/he masters.
The set of all possible states is called
competence space.
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Competence Assessment in CbKST
1. False c
2. Corr. b
3. Corr. dMulti-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Adaptive Competence Assessment in
CbKST• Lerners’ responses do not always perfectlyreflect their competence state• Therefore, probabilistic assessment isapplied• Three main components:
1. Question rule
2. Update rule
3. Stopping criterion
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Microadaptivity and Non-Invasive
Assessment• Originating from game-based learning• Distinguishing two types of adaptivity– Macro level: adapting by selecting learning
objects– Micro level: adapting by changing a learning
object during its consumption• Non-invasive assessment in order to not
disturb the flow of the gameMulti-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Microadaptivity and Non-Invasive
Assessment• Connecting CbKST and problem spaces• Interpreting users’ actions by underlying(required or missing) competences• Updating probabilities according to such
evidences• Non-invasive assessment means also no
optimal selection of questions• Immediate related feedback
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Multi-Modal Assessment• Not everything can be tested by questions
and test problems• Assessment information should begathered from different types of sources• Need arose in medical competenceassessment based on simulations and on
work with patients

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Multi-Modal Assessment

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Multi-Modal Assessment
Numerous possible types of sources:• Questions and test problems• Simulators, virtual reality, game situation• Self, peer, and expert assessment• Analysis of tasks and results in daily work
Not all sources are suited for all contexts.

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Multi-Modal Assessment• Adaptivity on a macro level, e.g.,– Which case scenario is used in a simulation– When to ask a user for a self assessment• Adaptivity on a micro level, e.g.,– Introduce a difficulty in a simulation if a testee
seems secure– Dynamic questionnaires for self/peer/expert
assessment
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Multi-Modal Assessment
Components of assessment procedure• Update: Real-time requirement• Questioning: Decreased importance,
redundant assessment information occur• Stopping criterion: Only needed in training
context

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Conclusions• (Cb)KST was developed for the adaptive
assessment of knowledge andcompetences• The original aim was to uncover a testee’scompetence state asking a minimal
number of questions• Multi-modal assessment allows transfer of
non-numerical testing to much broader
applications
Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Thank You for Your Attention!
Cord.Hockemeyer@uni-graz.at
http://css.uni-graz.at/staff/hockemeyer

Multi-modal Competence Assessment Based on Users' Performance on
Complex Tasks

Practices of Technology Supported
Learning in Japanese Industry— From the Activities of e-Learning Consortium Japan —Kiyoshi NAKABAYASHIThe Open University of Japan /e-Learning Consortium Japannaka@code.u-air.ac.jp

2009/91

Outlinee-Learning in Japanese industry
Activities of e-Learning ConsortiumJapan
Organizations
 Promotion of technology standards e-Learning professional program

Conclusion
2009/92

HRD System in Japanese Industry
Training for executive
Executive
ManagerJobspecific
training
2009/6

Employee
Manifac Develop
Salesturingment

Training for manager

Training for employee

3HRD System in Japanese Industry
Established in 1960~70’s
Training specific to job category


Sales, manufacturing, development, …

Training corresponding to the position in theorganization hierarchy


Executive, middle management, employee

OffJT and OJT
Off the Job Training: Traditional formal training
 On the Job Training: Informal training in the daily job2009/94

Introduction of e-Learning inJapanese Industry
Major targets


Replacement/complement of OffJT Time/Cost efficiency
 Enhance course variation
 Quick training course without leaving workplace Increase training opportunity

Major issues
Content delivery
 Content/Training design2009/95

Activities of
e-Learning Consortium Japan (eLC)
Organization
Promotion of technology standards
e-Learning professional program

2009/96

Organization of eLC
Launched as Technology-based Training (TBT)
Consortium in 1996
Changed name to e-Learning Consortium Japan andauthorized as nonprofit organization in 2001
About 60 member organizations from industry andscademia
Investigation and research in e-learning and related fields
Development and practice of learning program about eLearning for e-learning users and providers
Promotion of technology standards on e-learning systemand content

2009/97

Organization of eLC
Plenary meeting
Board of directors
Executive committee

6 Standing committees
 e-Learning Professional, Technology Standards, New Technology,

Publicity, etc.



6 Ad hoc groups Open Technology, Human Performance, Knowledge Management,

Content Authoring, etc.

EventsMonthly members meeting e-Learning conference in summer and winter Two to three days seminar
2009/98

e-Learning Conference

2009/99

Promotion of Technology Standards
Since year 2000
Supported by government

Emphasis on SCORM
LMS/Content interoperability was the firstpriority at that time System module development
 Seminars & publications
 Conformance programs

2009/910

System Module Developments
To minimize interoperability trouble andimplementation barrier
Supported by the government
Distributed as open source
SCORM 1.2 module in 2001
SCRORM 2004 engine since 2002
Mobile extension since 20052009/911

SCORM 2004 Engine

Course Structureas XML stream

Sequencing
EngineModuleBrowser
SCO Launch

RTE
RTE
ModuleTrace Log
as XML stream

API
ModuleResumedata
2009/912

SCORM 2004 Engine
Implemented as Java classes
Distributed as an open source
http://www.elc.or.jp/cgi-bin/scorm_engin/lms/
index-scorm.html
 http://www.oss.ecl.ntt.co.jp/lms/More than 1500 downloads since 2004
Used in several commercial LMS

2009/913

Sample Screen

2009/914

Mobile Extension
Manifest
FileProtocolTransformation
ServerSCORM 2004
LMS

Learning
ResultLearning
Resource
For
PC
For
Mobile2009/915

Mobile Extension
Based on SCORM 2004
Content and learning result shared by
PC-based and mobile-phone-basedlearning
Offline learning with mobile phone

2009/916

Sample Screena) Lecture pages

2009/9b) Test pagec) Feedback page17

Seminars and Publications
Seminars in e-Learning conference
Translations and tutorial documents
SCORM 1.2 and 2004
 SCORM assessor program texts Includes a document about interoperability troubles
and solutions encountered in actual implementation
practices

SCORM 2004 tutorial For system developers and content developers
 Document with sample content

2009/918

Conformance Programs
To share experience and knowledge about
interoperability issues in the community
For LMS and content
Periodical events to check if they work with each
other

SCORM assessor

2009/9Certify skilled SCORM content engineer
19

LMS Conformance
20 LMSs as ofMarch 2007
Several LMSs
developed BEFORESCORM with
proprietary
specification has
been modified toconform SCORM
2009/920

SCORM Assessor
Background
Third party content conformance test is expensive
 Content vendors needs engineers with skills about
interoperability issues
⇓Authorized assessor in each content vendor
Assessor training course Content self test and report Assessor community for information sharing

2009/921

SCORM Assessor Skill Set
Knowledge about theassessor program







Purpose of the program
Responsibility and authority ofassessor
Content conformance
procedureContent registration procedure
Interoperability trouble
management
Purpose of assessor
community

Knowledge about SCORM
specifications


2009/9GeneralContent aggregation
Run-time environment
Conformance requirement

Knowledge about SCORM
applicationContent development
Content test
Typical interoperability issues
and solution

Knowledge about related
fieldsStandardization of industrial
product
Standardization of e-learning
product
Communication protocol
Client side programming
Server side programming
Basic knowledge of computers

22

Increase of SCORM Assessor
120

106

Number of Assesors100

2009/9

87
70

80

60

60

39

40
20

14

47

22

0

23

Survey for SCORM Assessors
Findings
SCORM specification was intended to promote
ready-made content dissemination, but SCORM
assessors are involved in custom content creation
rather than ready-made content creation
 SCORM is utilized as a non-proprietary content
technology independent from each LMS
 Customers recognize that SCORM assessor
certification is as an evidence of excellent content
vendor

2009/924

e-Learning Professional Program
Defines seven job
skills related to elearningUser-side Manager
 Expert
 Tutor

Vendor-side Consultant
 Learning designer
 Content creator SCORM engineer

2009/925

Job Coverage ofe-Learning Professional
Strategy

Planning

SystemDesignContent
Creation

Learning

Evaluation

ManagerUser
sideExpertTutor
Consultant
Learning
Designer

Vendorside

Content
CreatorSCORMEngineer

2009/926

e-Learning Professional Curriculum

2009/927

e-Learning Professional Program
Collaboration with universities
Graduate school of instructional systems,
Kumamoto University
 Research Center for e-Learning Professional
Competency, Aoyama University“e-Learning Basic” course launched in 2008Prerequisite course for seven certifications

e-Learning consultant launches in 2009
SCORM assessor will be merged to SCORM
engineer
2009/928

Future Issues
Early introduction stage to popularization
stage
Strategic approach to exploit
e-learning is needed
From formal to informal
 From content to context
 Migration of daily job and learning activities Learner-centric and community-based2009/929

Nissan way by Carlos Ghosn“The power comes from inside”
学習者は内に能力を持つ
心構え（mindset）
Cross-functional / Cross-cultural
多様性が価値を生む
 Transparent
共有・協調 Learner
学び続ける Frugal
成果の最大化 Competitive
自己満足しない

2007/330

Nissan Way
行動（actions）
Motivate
 Commit & Target Perform Measure Challenge

2007/3

自他の動機付け
自ら目標設定結果に向かって成果の測定
変化への挑戦31

Fujitsu Learning Media

2009/932

Conclusion
e-Learning in Japanese Industry
Activities of e-Learning Consortium Japan
Organizations
 Promotion of technology standards
 e-learning professional program

Mutual benefits are essential forsustainable activities


Customers/companies/individuals

Future issues
2009/933

Personalized Learning Environments – Today and in the Future(Responsive Personalized Learning Environments)
Martin WOLPERS
Fraunhofer Institute FIT
Support for the learning process is constantly maturing. Specifically in the area oftechnology enhanced learning (TEL), software emerges that supports the learning
activity on a much more individual level than before. Still, today’s TEL systems do
not offer an individual learning experience for each learner. Instead of addressing
individual needs, mass-customization is used, forcing learners into stereotypes.
Consequently, learners lacking their own learning environment need to invest
significant energy to handle existing learning systems.
In this context, I will talk about the next step in personalized learning
environments. We develop new responsive open learning environments, in whichlearning services are suggested/recommended that suite the learners preferences,knowledge, competencies, etc. but also his organizational needs. Our approachpermits individualization of the components, tools, and functionalities of a learning
environment, and their adjustment or replacement by existing web-based softwaretools. Learning environment elements can be combined to generate (to mashup)
new components and functionalities, which can be adapted by lone learners or
collaborating learners to meet their own needs and to enhance the effectiveness of
their learning. This empowers each user to generate new tools and functions
according to their needs, and can help them to establish a livelier and personallymore meaningful learning context and learning experience.

Personalized Learning Environments– Today and in the Future –(Responsive Personalized Learning Environments)

Dr. Martin Wolpers
FIT.ICONFraunhofer-Gesellschaft

 57 Institutes
 15 000 employees Non-profit organization for
applied research 57 research institutes
 15.000 employees Annual budget ca. 1,400
Mio. €

7 Groups:
 Information and Communication Technology
 Life Sciences Microelectronics
 Light & Surfaces
 Production
 Materials and Components - MATERIALS Defense and Security

Fraunhofer Institute FIT
Applied Information Technology
Prof. Dr. Matthias Jarke• User-centeredcentered information and cooperation systems• Goal: Optimizing usability and usefulness of IT in theInterplay with organizational work practice, structures,and processes.
Business Areas:• Cooperation systems / collaborative computing• Mobile knowledge• User-centered software engineering• Decision and process support• Life science informatics• Collaborative virtual and augmented reality

ca. 115 scientists: computerscience, social science, busine
and economics, psychologists
engineersCAPLE
Context and Attention in Personalized Learning Environments
Research Areas:
Information and knowledge processing• Knowledge inference, knowledge management, Knowledge Representation• Semantic knowledge and information modeling• Information and Metadata
Personalization and adaptation• Attention metadata• User profiling• Information retrieval• Recommender Systems
Technology enhanced learning
Communication Analysis
Artificial intelligence and Machine Learning
Social Network Analysis
Software engineeringTechnology Enhanced Learning“Technology enhanced learning (TEL) has the goal to provide socio-technicalsocioinnovations(also improving efficiency and cost effectiveness) for learning practices, regarding
individuals and organizations, independent of time, place and pace. The field of TEL
therefore describes the support of any learning activity through technology.”
TEL in Wikipedia• Personalized Learning Environments• Responsive Learning Environments• Open Learning Environments• Self-Regulated Learning• Life-Long Learning• Constructivist Learning

Monitoring Usage and Attention: CAM

SchemasModels (Domain, Navigation,…)Usage Data
Application Profiles

Data about
the User

Usage Data
User Profiles
UserUser-driven Processes

Data about
the Content

Contextualized
Attention Metadata

Sources of Contextualized Attention Metadata (CAM)

Searched andlooked?
Reused?

When? Where?
How?

Search terms?
Topics?

When, withwhom, about
what?

Capture, exchange, associate,combine and analyze

CAM Infrastructure

Com.
Apps.

Wrapper
Log2CAM

File
Apps.

Wrapper
Log2CAM

ServerApps.

Wrapper
Log2CAMDB Wrapper
CAM2RDF
P2P,
Client,ServerWWW

P2P,
Client,Server

CAM Analysis

P2P,
Client,ServerDB Wrapper
CAM2SQL
DB Wrapper
CAM2XML

RDF
Store
Rel.
DB
XML
DB

CAMera: Reporting on Computer Usage

Communication Analysis: Social Networks

CAMera/ MACE: Remote Services, Zeitgeist

MACE(http://www.mace-project.eu)
project.eu)

Metadata for Architectural Contents in Europe
Making architectural learning contents available to learners using new access methods
and bridging repositories

MACE: Faceted Search

MACE: Search Results

MACE: Mobile Services, Augmented Reality

Responsive Open Learning Environments

ROLE Vision• Empower the learner to build theirown responsive learning environment

Responsiveness• Awareness and reflection of own
learning process

User-Centered• Individually adapted composition of
personal learning environment

http://www.rolehttp://www.role-project.eu

ROLE: Mash-up
up services, rules and principles
Intelligent Mediation and Recommendation
within ROLE Interoperability Framework(GUI mash-up + mash-up
up on learning design level)

Activity-driven

Preferencedriven

Skilldriven

Testdriven

Resourcedriven

Managementdriven

Actionoutcometool
bindings

Personal
learning stylerules

Competency
profile driven
rulesPlannedLearning
outcomes

Content rules

Learning
progressmilestones

Tool andlearnerinteraction
patterns

Time and cost
constraints/preferences

Learning
progress driven
rules

Rules to fulfill
Compliance
Tests

Service rules

Peer educator
given rules

API to Test
Systems

API to Content Repositories, LMS,LCMS, Soc. Networks

API to User and Skill Profiles in OpenID, LMS etc.

LogiAssist
Mobile training for truck drivers
 Learning in breaks, at stops, during driving.
 Using mobile low-profile technology Distributed learner communities- Motivation for self-regulated learning- Context-sensitive
sensitive adaption of learning contents and presentation modes- Security aspects

Thank you.
Dr. Martin Wolpers
martin.wolpers@fit.fraunhofer.de
http://www.fit.fraunhofer.de/~wolpers+49 2241 14 -2128

http://www.fit.fraunhofer.de/services/mobile/caple_en.html

JAPANESE-GERMAN CENTER BERLIN [JDZB]
in cooperation with

JAPAN SOCIETY FOR INFORMATION AND SYSTEMS IN EDUCATION [JSISE]
THE UNIVERSITY OF ELECTRO-COMMUNICATION, TOKYOGRAZ UNIVERSITY
Tentative Program
For the symposium and workshop on

The Challenge of Demographic Change –Sustainable Life-Long Learning and Digital Media
September 10 and 11, 2009at the JDZB, Saargemuender Str. 2, 14195 Berlin
Wednesday, September 919.30 hGet-together for speakers and organizers, Hotel Savoy

Thursday, September 10, public symposium
Languages: Japanese/German, simultaneous interpretation
09.30 hWelcome Remarks
Dr. Friederike BOSSE (JDZB)

09.40 hIntroduction
Prof. Dr. OKAMOTO Toshio (Japan Society for Information and Systems in Education[JSISE]; The University of Electro-communication, Tokyo)
Prof. Dr. Dietrich ALBERT (Graz University, Austria)

Session 1

Policy Perspective
Chair: Prof. Dr. Dietrich ALBERT (Graz University, Austria)

10.00 h

SAITO Haruka (Director, Educational Media and Information Policy Bureau, Life-long
Learning Policy Bureau, Ministry of Education, Culture, Sports, Science andTechnology, MEXT)

10.20 hInvestitionen in Bildung und Forschung - Der Schlüssel für Innovations- undWettbewerbsfähigkeit vor dem Hintergrund der demographischen Entwicklung
Dr. Stefan LUTHER (German Federal Ministry for Education and Research, Deputy
Director General, Life-long Learning)

10.40 hQ&A

11.00 hCoffee break

11.30 hTechnology-enhanced learning - changing the research perspective in Europe
Christian WILK (European Commission, DG Information Society and Media)

11.50 hQ&A

12.15 hLunch

Session 2

The Use of Digital Media at Universities and Perspectives for Life-long Learning
Chair: Prof. Dr. OKAMOTO Toshio (Japan Society for Information and Systems in
Education [JSISE]; The University of Electro-communication, Tokyo)

13.30 hProf. Dr. Nicolas APOSTOLOPOULOS (Director, Center for Digital Systems, Freie
Universitaet Berlin)

14.00 hKyoto School of Professional Learning aiming at sustainable life-long learning
Prof. Em. NISHINOSONO Haruo (Institute of Learning Technology)

14.30 hQ&A

Session 3

Knowledge Transfer, especially between Old and New Workforce, and Digital Media
Chair: NN

15.00 hThe Organizational Knowlegde Circulated e-Learning Management System andHuman Development
Prof. Dr. OKAMOTO Toshio (The University of Electro-communication, Tokyo JSISE)

15.30 hOn the Role of Knowledge Transfer in the Future Internet
Prof. Dr. Klaus TOCHTERMANN (Know-Center / Graz University of Technology)

16.00 hQ&A

16.30 hCoffee break

Session 4

Panel Discussion: Technology Supported Learning in a Changing Working
Environment
Chair: Nikola WOHLLAIB (Berlin) tbc

17.00 hIntroductory Remark
NN (Stifterverband für die deutsche Wissenschaft), asked
Participants:
Dr. Lutz P. MICHEL (D-ELAN)
Prof. NAKABAYASHI Kiyoshi (National Institute of Multimedia Education)
Prof. Dr. Christoph MEINEL (Director, Hasso Plattner Institute at the University of
Potsdam)
Jan KUPER (DIHK)
Dr. Winfried HEIDEMANN (Hans Böckler Stiftung)18.30 hEnd of symposium
DinnerFriday, September 11, workshop
Language: English only
09.30 hIntroductory speeches
Prof. Dr. OKAMOTO Toshio (JSISE)
Prof. Dr. Dietrich ALBERT (University of Graz, Austria)

10.00 h3 Parallel Sessions (A-C)
A) Digital media in international academic learning and researchB) Knowledge transfer to the next generation
C) Social network services

12.00 h

Lunch

13.30 h3 Parallel Sessions (A-C) continued

15.30 hCoffee break

16.00 h3 Parallel Sessions (D-F)
D) Life-work balance and digital media
E) ePedagogy
F) Learning Grid

18.00 hDinnersupported by
THE JAPAN FOUNDATIONTHE SOCIETY OF FRIENDS OF THE JDZBAuthors
ALBERT, Prof. Dr. Dietrich; University of Graz & Graz University of Technology
APOSTOLOPOULOS, Prof. Dr. Nicolas; Freie Universität Berlin, Center for Digital
Systems
BANNERT, Prof. Dr. Maria; Chemnitz University of Technology, Educational
Media
BENZ, Dipl. Psych. Bastian; Darmstadt University of Technology, Educational
Psychology
BURCHARDT, Dr. Aljoscha; Darmstadt University of Technology, Center ofResearch Excellence “E-Learning 2.0,”
DAHN, Prof. Dr. Ingo; University Koblenz Landau, Knowledge Media Institute
Koblenz
HASEGAWA Shinobu; Japan Advanced Institute for Science and Technology
HAYASHI Yuki; Nagoya University, Graduate School of Information Science
HELIC, Dr. Denis; Graz University of Technology, Knowledge Management
Institute
HOCKEMEYER, Cord; Cognitive Science Section, Department of Psychology,
University of Graz; Knowledge Management Institute, Graz University ofTechnology, Austria
HONDA, Prof. Toshiaki; Ibaraki University, College of Education
HORIGUCHI Yuki; Waseda University, Faculty of Human Sciences
ITOH, Prof. Kazunori; Shinshu University, Graduate School of Science andTechnology
KAPP Felix; Dresden University of Technology, Psychology of Learning &Instruction
KASHIHARA, Prof. Dr. Akihiro; Dept. of Information and Communication
Engineering, The University of Electro-Communications
KAYAMA, Prof. Dr. Mizue; Shinshu University, Graduate School of Science andTechnology
KLAMMA, Dr. Ralf; RWTH Aachen, Informatik 5
KÖRNDLE, Prof. Dr. Hermann; Dresden University of Technology, Psychology of
Learning & Instruction
KOJIMA, Prof. Kazuaki; Waseda University, Faculty of Human Sciences
KOJIRI Tomoko; Nagoya University, Graduate School of Information Science
MANN, Doreen; Darmstadt University of Technology, Educational Psychology
MATSUI, Prof. Dr. Tatsunori; Waseda University, Faculty of Human SciencesMÜLLER PHILIPPS SOHN, Dr. Herbert; FBD Bildungspark, Stuttgart
NAGAI, Prof. Takashi; Shinshu University, Graduate School of Science andTechnology
NAGAOKA, Prof. Dr. Keizo; Waseda University
NAGATA Naomi; The University of Electro-Communications, Tokyo
NAGATOME Keisuke; The University of Electro-Communications, Dept. ofInformation and Communication Engineering

NAKABAYASHI, Prof. Dr. Kiyoshi; The Open University of Japan; e-Learning
Consortium JapanNARCISS, Susanne; Dresden University of Technology, Psychology of Learning &Instruction
NIEMEIER, Joachim; Entrestage GmbH; Stuttgart University
NISHINOSONO, Prof. em. Haruo; Kyoto University of Education, Institute of
Learning Development
OHTA, Prof. Tatsuya; Nanzan University
OKAMOTO, Prof. Dr. Toshio; University of Electro-Communications; JapaneseSociety of Information and Systems in Education, TokyoPROSKE, Antje; Dresden University of Technology, Psychology of Learning &Instruction
RENSING, Dr. Christoph; Darmstadt University of Technology, Educational
Psychology
SAITO Haruka; Educational Media and Information Policy Division, Life-long
Learning Policy Bureau, Ministry of Education, Culture, Sports, Science andTechnology (MEXT), JapanSCHMITZ, Prof. Dr. Bernhard; Darmstadt University of Technology, Educational
Psychology
SCHOLL, Dipl.-Ing. Philipp; Darmstadt University of Technology, Educational
Psychology
STEINMETZ, Prof. Dr. Ralf; Darmstadt University of Technology, Educational
Psychology
TOCHTERMANN, Prof. Dr. Klaus; Graz University of Technology & Know-Center
WARAGAI, Prof. Dr. Ikumi; Keio University
WATANABE Toyohide; Nagoya University, Graduate School of Information Science
WILK, Christian; European Commission, Generaldirektion Informationsgesellschaft und Medien
WOLPERS, Dr. Ing. Martin; Fraunhofer Institute FIT