The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter

	
  

iafor
The IAFOR Journal of Education
Volume 2 – Issue 1 – Winter 2014

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  IAFOR Publications
Executive Editor:
Joseph Haldane
The International Academic ForumThe IAFOR Journal of Education
Editor:Bernard Montoneri, Providence University, Taiwan

Associate Editors:
Cassandra Atherton, Alfred Deakin Research Institute, Australia
Beena Giridharan, Curtin University, Sarawak Malaysia
Askhat F. Safiullin, Chonbuk National University, South Korea

Published by The International Academic Forum (IAFOR), Japan
IAFOR Publications. Sakae 1-16-26-201, Naka-ward, Aichi, Japan 460-0008

Executive Editor, IAFOR Publications: Joseph Haldane
Design: Bernard Montoneri

The IAFOR Journal of Education
Volume 2 – Issue 1 – Winter 2014

IAFOR Publications © Copyright 2014
ISSN: 2187-0594 (Online) http://iafor.org/educationjournal.html
Cover image by Ajari/Flickr
http://www.flickr.com/photos/ajari/3898575530/in/photostream/
http://creativecommons.org/licenses/by/2.0/
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  Notes on Contributors

Henning Breuer is founder of “uxberlin – innovation consulting" (www.uxberlin.com) andprofessor of business and media psychology at the university of applied sciences for media,
communication and management in Berlin, Germany. His focal point of interest is the creation ofsustainable value. His research and consulting work currently focuses on innovation strategy andorganizational learning, corporate venturing and business modeling and human-centered design.
As an adjunct researcher at Waseda University Tokyo he is also creating concepts and prototypes
for learner-centered design. For Deutsche Telekom set up a project field for User Driven
Innovation as research and innovation director. Before, he used to work at consulting companies,
at the University of Chile, and at the University for Applied Sciences Potsdam.
Heinrich Schwarz is owner of Schwarz Innovation, a people centric strategy consultancy basedin Hamburg, Germany, and lecturer on business anthropology. In the past he worked as
management consultant in Denmark and as academic faculty and ethnographic research
consultant in the US. He holds a PhD in science and technology studies from M.I.T and other
degrees in social and cultural studies and psychology.
Kristina Feller works as a scientific associate at User Driven Innovation, a user-centered unit of
Telekom Innovation Laboratories in Berlin. The User Driven Innovation supports user-centric
product development by developing and applying innovative user research tools along the entire
innovation process. Kristina Fellers research and work focuses on the early phase of theinnovation process - ethnographic exploration and idea creation based on the ethnographic
insights. She holds a Master degree in Intercultural Communication and a BA in Social andCultural Studies obtained at the European University Viadrina. Previous to her role as a research
assistant Kristina Feller worked as a student assistant at Telekom Innovation Laboratories as well
as at European University Viadrina.
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  Mitsuji Matsumoto joined NTT Labs in 1970 and worked on terminal architecture, design andinternational standardization for facsimile, telematics, and multimedia systems. In 1994 hereceived the Doctor's Degree of Engineering from Waseda University, Tokyo Japan. In 1996, hejoined Waseda University as a Professor. From 2000-2004 he was Vice Chairman of ITU-T
SG16 Multimedia. Recently he leads standardization in accessibility for persons with disabilities,
and education about standards. He is a member of ITU-T Academia, IEEE Senior member, IET
and a member of IEICE and IIEEJ (former President).
Esther Smidt is an Assistant Professor of TESOL in the Department of Languages and Culturesat West Chester University. Her research interests include distance education, computer-assisted
language learning, immigrant identities, immigrant education, and second language teacher
education.
Jennifer Bunk is an Associate Professor of Psychology at West Chester University. She teaches
online and hybrid courses in industrial/organizational psychology and research methods. She isinterested in understanding distance education through a psychological lens and also researches
workplace stress, workplace incivility, and work-family conflict.
Bridget McGrory is currently a second year graduate student at West Chester University
pursuing a Masters of Arts in the Industrial/Organizational Psychology program. She received a
B.S. in Psychology from the University of Pittsburgh. Her research interests include distanceeducation, workplace incivility and transformational leadership.
Rui Li is the Executive Director of Distance Education and Instructional Design at West Chester
University. She has taught online/blended courses both nationally and internationally and her
research focuses on distance education and technology as cognitive tools.

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  Tanya Gatenby is an Associate Professor and Masters of Public Health and Health CareManagement Track Coordinator at West Chester University. Her research focuses on distanceeducation, health and wellness, underserved populations and health care access.
Kiran Hashmi has been a Master trainer, a teacher educator and researcher for a decade. She isworking as a Senior Lecturer at Notre Dame Institute of Education, Karachi, Pakistan. She is wellknown for her teaching skills and research contribution. She has a bright academic andprofessional career. Currently she is pursuing her doctoral study in Psychodynamics ofLeadership, the first of its kind in Pakistan. Her research papers have been published at national
and international levels.
Kent Fredholm lives in Sweden and has a background as a teacher of Swedish, Italian, French,
Spanish, Latin and Mandarin Chinese, teaching pupils between ages 12 and 75 for the last decade.
He is currently performing PhD. studies in Spanish at the Department of Language Education of
Stockholm University. His current studies concentrate on the use of information andcommunication technology among pupils learning Spanish as a foreign language, with particularfocus on digitalised writing strategies, grammar learning and online translation. Earlier studies
and interests have concerned symbolism in Italian and French 20th century literature and pupils’
motivation for foreign language studies.
Russell Butson is a senior lecturer in higher education/educational technology. His research is
focused on institutional learning that is the learning that takes place within professional contexts,
particularly within the university setting. How and why do students and faculty acquire the skills
and knowledge needed to advance their professional goals? Information Communication
Technologies (ICT) is a core part of this learning context and therefore the development of
discipline-based ICT literacy offers a new perspective into the learning process.

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  KwongNui Sim is a Ph.D. candidate in higher education. Her research is focused on ICT(Information Communication Technologies) beliefs and practices held by students as they
undertake their tertiary education. What is the role of ICT among undergraduate students in their
daily study practice? How does ICT play a role in postgraduate students’ day-to-day research
practice? ICT literacy could be a significant aspect in today’s tertiary learning context. Therefore,studies on students’ ICT literacy offer a new perspective in the emerging area of research on ICT
utilisation and integration in tertiary education.
Dr. Marilyn L. Balmeo is currently the Department Head for Professional Education in the
School of Teacher Education, Saint Louis University, Philippines. She had been teaching for 18
years in the tertiary level and had been a research adviser both in the undergraduate and graduatelevels in the University. She had been able to present several of her research works in varied
national and international forum and conventions. She is also a trainer and speaker in educationrelated topics and activities.
Allan B. Castro is currently a fourth year student majoring in Mathematics Education under the
School of Teacher Education of Saint Louis University, Baguio City, Philippines. He has been
assisting various student researchers in his college in matters of interpreting research results andorganizing research data. Outside the academic field, he is the president of the student council ofSaint Louis University and is a debater for SLU Debate Society.
Kristine Joy T. Caplis is a Special Education graduate under the School of Teacher Education ofSaint Louis University, Baguio City, Philippines. She is currently working as an educator at
Northridge Academy, Inc., Baguio City.

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  Kizzylenn N. Camba is a Special Education graduate under the School of Teacher Education ofSaint Louis University, Baguio City, Philippines. She is currently working as an educator at
Northridge Academy, Inc., Baguio City.
Jahziel Gillan M. Cruz has been a Special Education student of the School of Teacher
Education of Saint Louis University, Baguio City, Philippines.
Marion G. Orap is a fourth year special education student of the School of Teacher Education ofSaint Louis University, Baguio City, Philippines. Currently, he is in his practicum phase for his
chosen program.
Joroma Sol T. Cabutotan is a Special Education graduate under the School of Teacher
Education of Saint Louis University, Baguio City, Philippines.
Mariyana Ivanova Ilieva is from Bulgaria, Sofia city. She obtained her PhD in 2012 at Sofia
University St.Kliment Ohridski, Faculty of Education, code of professional field - Pedagogy,
Doctoral programme - History of The pedagogy and the Bulgarian education. She graduated fromthe Sofia University St. Kliment Ohridski, Faculty of History in 2005 with Bachelor's Degree in
History, specialization: History of Byzantium and the Balkans. She also completed a Master’s
Degree in Education, specialization: Management of education from the Sofia University St.
Kliment Ohridski, Faculty of Education in 2002. Her career at Sofia University St. Kliment
Ohridski started in 2008. She is currently an assistant professor at the University St. Kliment
Ohridski, Faculty of Education. She teaches History of Pedagogy, History of Bulgarian Education,
History of social work, Alternative Education - history and contemporary. Ilieva has publishedthe research papers and articles about Historical pedagogy. Her research interest include
European and Bulgarian history, Historical pedagogy, The Philosophy of education, Pedagogic
innovations, Research and development methodologies, E-learning. She participated in several
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  national, an international scientific forums and conferences about Education. She also
participated in several national projects. Ilieva is currently participant in the project Developmentof the research potential of University of Sofia in the field of e-learning is funded by the
Operational Programme for Human Resource Development of the European Social Fund.

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Volume 2 - Issue 1 - Winter	
  Journal of Education Editors
Editor: Dr Bernard Montoneri
Providence University, Taiwan
Bernard Montoneri earned his Ph.D. (African, Arab, and Asian Words; History, Languages,
Literature) and his BA in Chinese from the University of Provence, Aix-Marseille I, France. He
is currently an Associate Professor at Providence University, Taichung, Taiwan. He teaches
Literature (European, Children, American, and British) and languages (French, English, andItalian). Bernard has published more than 32 journal and conference papers, 5 books and has
obtained 16 teaching or research projects. His research interests include European literature,children literature, English writing, automated scoring systems, teaching and learning evaluation,
data envelopment analysis, networking, and teaching methods. He is a reviewer for top academic
journals such as Review of Educational Research (impact factor: 3.169; rank: 3 out of 203 in
Education & Educational Research), American Educational Research Journal (2.393), Teaching
and Teacher Education (1.322), and European journal of Operational Research (1.815). He is
linked to around 22 million professionals on LinkedIn.
Associate Editor: Dr Cassandra Atherton
Alfred Deakin Research Institute, Australia
Cassandra Atherton is a senior lecturer at Deakin University. She has written several articles onacademic public intellectuals for international journals and is currently writing a book, Wise
Guys, on the changing role of the public intellectual in academe, based on her interviews with
Noam Chomsky, Harold Bloom, Camille Paglia, Stephen Greenblatt and others. A bookinterviews with these American public intellectuals, entitled In So Many Words, is forthcomingfrom Australian Scholarly Press. She has written a critical monograph, a novel and a book of
poetry.

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  Associate Editor: Dr Beena Giridharan
Curtin University, Sarawak Malaysia
Beena Giridharan is the Dean, Teaching and Learning at Curtin University, Sarawak. She is
responsible for strategic and academic leadership and continuous improvement in teaching andlearning across all programs offered by Curtin Sarawak. She attained a doctoral degree inApplied Linguistics and Education from Curtin University, Western Australia. Her Master’s
degree (first class) is in English Language and Literature, and her Bachelor’s degree in Science(first class). She has been a fellow of the Higher Education Research and Development Society ofAustralasia (HERDSA) since 2006. She won the 2006 Carrick Australian Award for University
Teaching and the Curtin Excellence in Teaching and Innovation award in 2006. As a member ofan OLT (Office of Learning and Teaching, Australia) funded project entitled ‘Learning Without
Borders’, she has investigated leadership roles in Transnational Education (TNE) andinternationalization of curriculum. She is a reviewer for the Pertanika-Journal of Social Sciences
and for the Higher Education Teaching and Learning Journal. She has been an invited speaker atseveral national conferences. Her research interests include vocabulary acquisition in English as asecond language, higher education practices, transnational education, work-integrated learning,and ethno-linguistic studies in indigenous communities. She was a visiting professor at theVirginia Commonwealth University, Richmond, Virginia, USA, between 2007 and 2008.
Associate Editor: Dr Askhat F. Safiullin
Chonbuk National University, South Korea
Askhat F. Safiullin earned his Ph.D. (International Studies) and his BA in International Relationfrom the Yonsei University, Seoul, South Korea. He is currently an Adjunct Professor at
Chonbuk National University, Jeonju, South Korea and Adjunct Professor at the Graduate Schoolof International Studies at Yonsei University, Seoul. South Korea.

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Volume 2 - Issue 1 - Winter	  He is also a Visiting Professor at Sonkyunkwan University, Seoul, South Korea. He teaches awide spectrum of subjects in International Relations ranging from Diplomacy and Global
Governance to the Korean Research Design.
Askhat has published a number of journal and conference papers and a chapter in a book. His
research interests include International Relations and related spheres, and effective teaching andlearning methods.

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Volume 2 - Issue 1 - Winter	
  Table of Contents
Notes on Contributors

p. 1

Journal of Education Editors

p. 7

Table of Contents

p. 10

Editors Introduction

p. 11

Value Innovation in Learner-Centered Design. How to Develop Valuable Learning Tools.

p. 16

Henning Breuer, Heinrich Schwarz, Kristina Feller, Mitsuji Matsumoto
Student Attitudes about Distance Education: Focusing on Context and Effective Practices.

p. 40

Esther Smidt, Jennifer Bunk, Bridget McGrory, Rui Li, Tanya Gatenby
Human Resource Management Strategies and Teacher’s Efficiency within Schools:
A Co-relational Study.

p. 65

Kiran Hashmi“I prefer to think for myself”: Upper Secondary School Pupils’ Attitudes towards Computerbased Spanish Grammar Exercises.

p. 90

Kent Fredholm
Teaching Improvement Model Designed with DEA Method and Management Matrix.

p. 125

Bernard Montoneri
To What Degree are Undergraduate Students Using their Personal Computers to Support
their Daily Study Practices?

p. 158

KwongNui Sim, Russell Butson
Exploring Major Predictors of Student Satisfaction: An Input towards a LearningFriendly School Environment.

p. 173

Marilyn L. Balmeo, Allan B. Castro, Kristine Joy T. Caplis, Kizzylenn N. Camba,
Jahziel Gillian M. Cruz, Marion G. Orap, and Joroma Sol T. Cabutotan
Mikhail Geraskov (1874-1957) Methodological Concepts of Learning Physics.

p. 199Mariyana Ilieva
Guide for Authors

p. 220

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Volume 2 - Issue 1 - Winter	
  Introduction
It is my great pleasure and honour to introduce Volume 2 of IAFOR Journal of Education. This
first issue is mostly a selection of papers submitted during:
1. The fourth annual Asian Conference on Education (ACE 2012), 'Learning and TeachingThrough Transformative Spaces', held in Osaka in October 2012. ACE attracted 450
registrants and invited speakers from more than 40 countries; it was IAFOR’s biggest
conference to date. 130 papers were submitted online in December 2012.
2. The inaugural European Conference on Education (ECE 2013). The First European
Conference on Education was held alongside the Inaugural European Conference on
Technology in the Classroom (ECTC 2013). The two conferences were held in Brighton,
UK, in July 2013. The event attracted 350 delegates from over forty countries.
The first paper is co-authored by Henning Breuer, Heinrich Schwarz, Kristina Feller, and Mitsuji
Matsumoto. Breuer et al. identify a potential value innovation by using a recent innovation
project in higher education in Germany. The project had the goal to identify potential newlearner-centered tools and services for university students with high business potential. Threedifferent research methods (Ethnography, desk research, and blue ocean market analysis) wereapplied and combined to achieve a broader and deeper understanding of the topic. Breuer et al.
show that only in combination can the derived ideas create a new market and meet customers’
needs at the same time.
The second paper by Esther Smidt, Jennifer Bunk, Bridget McGrory, Rui Li, and Tanya Gatenby
propose to understand the experience of online courses from students’ perspectives. They apply aqualitative method in a specific context, namely that of a Mid-Atlantic mid-sized state university,and translate their findings into practical recommendations for instructors. Smidt et al. notably
demonstrate that online courses have heavy workloads requiring student autonomy; students tend

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Volume 2 - Issue 1 - Winter	  to complain about the lack of instructor support and about the lack of interaction, whether
instructor-student or student-student.
Kiran Hashmi studies Human Resource Management and Development (HRMD) strategies andtheir effect on teachers’ efficiency within the Catholic Board of Education (CBE) schools of
Pakistan whose teachers are graduates in educational leadership courses from a private teacher
education institutes in Karachi. The paper endeavored to build a simple theoretical andconceptual framework where the effectiveness of HRMD strategies in educational leadershipwere studied to explore their impact on enhancing teachers’ efficiency.
The next paper, written by Kent Fredholm, conducts a qualitative survey mapping upper
secondary school pupils’ attitudes towards the Information and Communications Technology(ICT) use for learning Spanish language. His study looks at ICT use for grammar practice. A
group of pupils completed lesson diaries, reflecting upon web-based grammar exercises,
comparing them to paper-based exercises, and a questionnaire survey on general attitudes
towards ICT in language learning. Results show that the majority of participating pupils ask for agreater variety of tasks and see a need also for traditional forms of grammar practice, especiallywritten exercises which give time to reflect upon grammar, syntax and vocabulary. They want
ICT use to be an option, not a constraint.
The paper by Bernard Montoneri uses student evaluation of teachers to design a teaching
improvement matrix based on teaching efficiency and performance by combining management
matrix and data envelopment analysis (DEA). This matrix is designed to formulate suggestions toimprove teaching. The research sample consists of 42 classes of freshmen following a course ofEnglish in Taiwan. The empirical findings show that proposed model can distribute all theevaluated classes into 4 quadrants depending on their performance and efficiency, identify theimportance of each performance indicator, and suggest the improvement direction in different

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  quadrants for all the evaluated classes. A study case of one inefficient class is presented in orderto demonstrate the proposed model utility and feasibility.
The next paper is co-authored by KwongNui Sim and Russell Butson. They examine the degree
to which twenty two undergraduate students used their personal computers to support theiracademic study. The students were selected based on their responses to a questionnaire aimed at
gauging their degree of computer skill. Computer activity data was harvested from the personal
computers of eighteen students and video footage of the students personal study sessions wasgathered from a further four students. They conclude that for this group of students computers
played an important role in their day to day lives, but the degree to which they were used in theiracademic study was lower than we had expected.
The study co-authored by Marilyn L. Balmeo, Allan B. Castro, Kristine Joy T. Caplis, Kizzylenn
N. Camba, Jahziel Gillian M. Cruz, Marion G. Orap, and Joroma Sol T. Cabutotan applies
Stimulus-Organism-Response theory to determine the perceived level of importance andperceived level of satisfaction of 399 college students in Saint Louis University, Baguio City,
Philippines. Only 6 out of the 16 areas of the learning environment were identified with anexisting significant relationship between respondents’ perceived level of importance and level ofsatisfaction, that is, guidance office, computer laboratory, science laboratory, campus security,
clinic services, and janitorial services.
Finally, this issue contains a novelty: a section entitled “Key educational scholars”. Mariyana
Ivanova Ilieva offers a rigorous summary of Geraskov's theories and her paper is a fascinating
addition to the journal. Mikhail Geraskov (1874–1957) was an eminent Bulgarian educator andextraordinary professor. He developed the scientific foundations of didactics and methodology of
training. His work contributed a lot to the development of the Bulgarian pedagogy.

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  Please note that we welcome original research papers in the field of education submitted byteachers, scholars, and education professionals. They may send their manuscript even though they
did not participate to one of the conferences held by IAFOR. We also welcome book reviews,
reviews of the literature in the field, and contributions introducing key educational scholars. The
next issue scheduled for August 15, 2014 will also be a selection of papers submitted during theabove mentioned conferences.
IAFOR publications are freely accessible on the website (Open Access). Moreover, there is no
publication fee for authors. Please find the guidelines at this end of this issue. Follow the new
guide for authors if you wish to submit your paper. Finally, do not hesitate to join us on LinkedIn
via the group entitled IAFOR journal of Education.
Best regards,
Bernard Montoneri

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Volume 2 - Issue 1 - Winter	
  Value Innovation in Learner-Centered Design. How
to Develop Valuable Learning Tools.
Henning Breuer, Heinrich Schwarz, Kristina Feller, Mitsuji Matsumoto
	
  

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  Abstract

This paper shows how to address technological, cultural and social transformations with
empirically grounded innovation. Areas in transition such as higher education and learningtechniques today bring about new needs and opportunities for innovative tools and services. But
how do we find these tools? The paper argues for using a strategy of (user) value innovation thatcreatively combines ethnographic methods with strategic industry analysis. By focusing on unmet
and emerging needs ethnographic research identifies learner values, needs and challenges but
does not determine solutions. Blue-ocean strategy tools can identify new opportunities that alter
existing offerings but give weak guidance on what will be most relevant to users. The
triangulation of both is illustrated through an innovation project in higher education.

Keywords: User needs and values; Innovation, learner-centered design; Ethnography; Blue ocean
strategy; Triangulation.

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  Introduction
The reality of university students is in transition. New rules and regulations govern theireducation. Expectations from industry and society and their own self-image change while
emerging digital tools uproot time-tested methods of studying. In Europe, the Bologna process
fostering comparability in educational standards and ensuring quality of qualifications is only one
visible cornerstone of substantial changes driven by trends such as globalization, mobile
digitalization, and the knowledge economy. All stakeholders are being affected: Far from their
old image of ivory towers, universities struggle to cope with the mass inrush of students. Stillholding on to the Humboldtian model of unity between research and teaching, teachers are torn
between their own scientific curiosity within an overwhelming body of knowledge and thedemand to deliver innovative approaches to teaching and learning. Students are often
overstrained by requirements resembling those of corporate managers but without having theresources and tools that professionals use. The scope and multitude of these transformations
explain why educational technologies have struggled to keep up with providing the best potential
support to students and professors. All this demonstrates the need for innovative tools andservices outlining a new field for innovation in the higher education domain. But how can we
support learners in dealing with the transformation in the educational systems and media
landscapes? How can we grasp and specify opportunities for innovation in such a transitory field?
While numerous ways have been proposed to generate ideas at the fuzzy front end of innovation
management and to position new products in a market, what is lacking is a consistent perspectiveon the theoretical and operational links between them. We suggest that the notion of value may
provide such a theoretical perspective and a consistent anchor for the different activities involved
in innovation. Our argument is based on the assumption that it is the purpose of business to create
value for people and society. What is of value to individuals and to cultures, however, changes ineras and areas of transformation, like those currently taking place in domains like the financial
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  systems or higher education. A profound understanding of what is of value at a given historicalmoment is required to create relevant value propositions and enable sustainable new business. In
order to comprehend what is valuable to people we need to understand their needs and theirvalues.
On a theoretical level, we contrast different notions of value and propose an integrated concept of“value innovation” in order to create solutions that are both, valuable and relevant as well as
novel, innovative and different. Value innovation combines user-centered with market-strategic
approaches in order to create substantial new value for users by serving new or insufficiently
fulfilled needs or by supporting inadequately supported values. Ethnographic research is good at
identifying learner needs, desires, values and challenges but cannot define which solutions are
viable. Blue-ocean strategy techniques are able to identify new opportunities from existing
offerings but can only provide weak guidance on what will be truly relevant to users. We
illustrate our suggested approach of creatively combining both approaches through a recent
innovation project in learner centered design in Germany. The project on learning management
tools and services demonstrates how the triangulation of both approaches can help to generatequalified product ideas and maintain focus throughout innovation projects.
Value innovation in learner-centered design: Related works and theory
For laying out our thoughts on value innovation, we build on scholarly work on learner-centered
design (e.g., Breuer & Matsumoto, 2011), ethnographic explorations of customer needs, andgrounded innovation theorizing (Breuer & Steinhoff, 2010).
A key role is played here by the notion of value. Often in discussions in economic or business
contexts the notion of value refers to monetary value or price, what Marx had called exchange
value, and is closely linked to profit considerations. Yet in our discussion on value innovation weunderstand the term “value” to refer to the value that products have or create for the user outsideof its exchange value – how valuable it is for them in their use or in their life. There are several
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  ways, however, in which a product can have value for users (Boztepe, 2003). Of interest here atleast three: products can be valuable because they have utility, because they fulfill people’s(emotional) needs, or because they support their values (note the distinction here between “values”
and “value”). We argue that in order to be successful, value innovation needs to take seriously thelatter two meanings of value.
The most common view of value when referring to use, points to a product’s utility, its practical
purpose and functionality. Accordingly a wide-spread strategy for developing new products ismaking them useful in new ways or enabling new uses. Along these lines, in the Marxist traditionuse value refers to utility and the physical properties of a product in use (Marx, 1962). Marx
pointed out that in order to create use value the producer had to imagine what is useful to people
and build that into the product. This imagining of usefulness is not a trivial task, however, andMarx did not specify how to determine what is useful, nor did he move beyond a quite practicalbut somewhat limited understanding of use and usefulness. Baudrillard (1991) later criticized
Marx’ “naturalistic phantasm” of utility value and complemented the functional dimension with asymbolic dimension of products, which are not only appreciated for what they do but for what
they signify, resulting in their sign value. This way Baudrillard emphasized the importance of anunderstanding of value that includes emotional, social and identity-related aspects beyond purely
functional ones.
We believe that a forward-looking understanding of user value needs to move beyond utility andpay attention to people’s needs (especially their emotional needs), and values. Although theattention in the business world to customer need fulfillment has been growing in recent years, thisperspective is far from a given and there are still a lot of innovation attempts that fail by failing toserve people’s needs. Yet while needs are on the radar of companies at least to some degree, thevalue of supporting customer values and goals has received less attention. A notable exception is
Schrage (2012) who demands that product innovation should not only address customers’ needs
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Volume 2 - Issue 1 - Winter	  but also their desired futures – answering the question who customers want or need to become.
Therefore it is important to analyze their personal, communal and cultural values. The distinction
between needs and values may be worth pointing out. Needs always refer to a lack; they areexperienced individually and often emotionally as part of a mental state of being. Values incontrast are directions for human action by pointing to ideals. They do not just belong to one
individual, rather they are shared by cultures or communities or social groups, and like needs are
not always conscious. Values can motivate and guide needs, preferences, wants and goals of
people, and influence the interpretation of needs as well as decision making.
A focus on both needs and values is especially crucial when innovation is planned for domains intransformation, as it is the case in our example of digital learning tools or techniques in higher
education. Change, whether it is technological, social or cultural, often changes existing or
generates new needs and values. The task and opportunity for value innovation lies in uncoveringand addressing these shifting and newly emerging needs and values. In short, a comprehensive
notion of value innovations should recognize and include the value created by fulfilling people’semotional needs and by supporting or promoting their values, in particular if applied to shifting
everyday practices, social domains or technological fields. In order to involve customers to help
create value and to inform the innovation processes companies (or administrations) have
employed a range of structured approaches, from traditional market research to advanced user
studies.
In recent decades especially ethnographic research has become a preferred approach to see theworld from a customer point of view, by studying them in their natural habitat and by using
observation and participation as research techniques in addition to conversation and interviews(Atkinson & Hammersley, 1994). The key reason for the growing attention to ethnography incommercial contexts lies in its promise to enable the creation of value for customers and thus
ensure the relevancy of new products, services and marketing activities.
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Volume 2 - Issue 1 - Winter	  The characteristics and specific qualities responsible for the claimed success of ethnographic
insights have been widely discussed in the last decade (Sutherland & Denny, 2007; Cefkin, 2009;
Jordan, 2002; Mariampolski, 2005; Bockhahn & Schwarz, 2010): Ethnographic insights are seen
as more real and more true to the actual way people behave, think and make decisions than othermethods. They are seen as going further and deeper than traditional market research in that theycapture not just the rational but also the emotional side of people’s experience and theirinteractions with the world. They are seen as less reductionist since they see people as part ofsocial and cultural systems rather than simply as individuals with independent behavior. Finally,
ethnographic insights are seen to capture not just behavior and opinions but moreover uncoverintangibles such as e.g. needs and problems, fears and hopes, ambitions and values of people. In
short, ethnographic research has been established as a source of deep insight into why people
behave the way they do and what they intimately wish and need.
Yet such a rich and deep understanding of customers’ needs does not per se lead to novel andinnovative solutions. But we argue that ethnographic inquiry can encourage new ideas, for one
due to its exploratory nature. In contrast to hypothesis-based research or testing methods, theopen mind approach of ethnographic practice leaves the door open to findings and observations
that are not pre-defined, anticipated or expected and therefore carry the potential to be surprisingand new (Lindlof & Taylor, 2002). Yet more importantly ethnographic research can facilitate thedevelopment of new solutions in at least four ways: by focusing on unmet needs; byconcentrating on latent or hidden needs, values and motives; by aiming at newly emerging needs
and desires; and by paying attention to workarounds.
First, focusing on unpacking people’s needs that are currently not or not sufficiently met, theproduct opportunities defined by these needs are by definition not already filled by existingproducts. If the right offerings were already available to customers these needs would not remainunfulfilled. For reasons ranging from a lack of knowledge, accessibility, availability, to a poor
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  overall configuration of products, the unmet need indicates openings for an innovative productoffering, communication or distribution system.
Second, by uncovering latent or hidden needs, problems and values, ethnography increases thelikelihood to discover new or untapped opportunities. If needs or values are hidden they are noteasily discovered by traditional research approaches and thus are probably not yet part of the
public discourse and general awareness. Invisible cultural patterns and taken for granted culturalbeliefs and preferences are unknown to most people. People also do not always have access to theemotional drivers underlying their own decisions; rather motives tend to get rationalized after the
event. Finally, people’s ideals and impression management often obscure the reality of their lives
and selves, not only to outsiders but also to themselves. By not solely relying on what people
consciously articulate but rather by utilizing nonverbal cues, material artifacts, situational
contexts and actual behavior and taking seriously seeming contradiction, ethnography may both
circumvent the impression management of people and unpack hidden drivers and motives.
Third, investigating newly emerging needs and desires is likely to point towards newopportunities that can lead to novel solutions. Needs change in accordance with societal
structures, cultural practices, and new means of satisfying needs. New needs surfacing in asituation of cultural or social transformation and technological change are different from existingand established needs, and so must be the solutions designed to address them. For instance, theunfolding needs and desires of students, who find themselves in an environment with heightened
expectations on their performance and defined by a challenging mix of analog and digitallearning tools and techniques, tend to resonate with this unique situation and cannot be servedwith old solutions, products and services.
Fourth, by paying attention to everyday practices and routines, ethnography frequently finds
workarounds that people use. These are ad-hoc, improvised and often personal strategies thatpeople employ to reach their goals in the face of challenges or in situations lacking established
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  solutions and existing products. Sometimes workarounds carry the seed for the type of solutionthat is required. When a mother tapes her phone to the baby stroller so that she can write text
messages while pushing her child, there is a cue to a potential design solution. Like theinventions of lead users, workarounds found by ethnographic research can provide interesting
pointers towards innovative solutions.
In sum, a focus in ethnographic research on unmet, hidden and newly emerging needs, motives
and values and on everyday workarounds may guide the search for new solutions into new anduncharted territory. Yet, despite directing a guiding light into untapped directions and offeringsome inspirations for solutions or user requirements, an ethnographic approach cannot predetermine these solutions, guarantee their novelty, and ensure their potential for business. Other
techniques must complement the ethnographic approach.
Particularly, in order to turn ideas on potentially valuable solutions into an innovation on amarketplace knowledge of this marketplace is required. Strategic approaches like blue ocean
analysis (Kim & Mauborgne, 2005) aim at such an understanding of the strategic market valuethat new products and services can capture. Referring to the renewal of corporate strategy rather
than to incremental innovation in established business Kim and Mauborgne (2005, 218) remarkthat “value innovation is about redefining the problem an industry focuses on rather than finding
solutions to existing problems”. Putting a notion of (buyer) value and a focus on non-incremental
innovation into the center of attention blue ocean analytical tools and frameworks suit to theattempt to drive innovation based on empirical customer values.
It is important to point out the differences between our concept of ‘value innovation’ based onreal customer insights and the notion of value innovation on a corporate strategy level used in theliterature on blue ocean strategy. Kim and Mauborgne (2005) discuss value innovation as
strategic renewal impacting the corporate activity system rather than innovation in the sense of
new product development. Their concept focuses on the notion of exchange value as discussed
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  above, and defines value through the alignment of innovation with utility, price and cost positions(2005, 13) and distinguishes between buyer value and company value. As buyer value iscomprised of utility and price of a product, and company value is comprised of price and cost
structure both may be remodeled in order to create or enter into an “uncontested market space”.
Trying to transcend established market boundaries and industry structure blue ocean strategy
remains related to both as defined by the competition on the rather macroscopic level that isclosely related to business model innovation. While such market analysis can identify potential
new markets, the relevancy of the assumed, the potential real values for users, cannot be
determined by it.
Combining market analysis and ethnographic approaches through the notion of value, in thispaper we follow a user-centered and learner-centered paradigm, in which value is defined by theuser or learner. The value proposition links business to the existential needs and motivations ofdifferent groups of people, and thereby the existential reason for the whole endeavor, the job to
be done. A value proposition not only describes the functional utility, or what something can do,
but also implies personal needs and values. Value innovation then refers to the empiricallygrounded development of new and relevant value propositions. Value innovation in our
understanding is based on functional, emotional and symbolic user needs and values, backed up
by cultural trends, intersecting with novel product value factors (functional, emotional andsymbolic ones) backed up by market trends (see Figure 1 below).

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Figure 1 Value Innovation is based on an understanding of user / student values (backed up by cultural trends)
intersecting with new product utility factors (backed up by market trends).

Methodology for identifying a potential value innovation
Based on this understanding of value innovation we suggest the following methodologicalapproach within fields of cultural transformation such as today's higher education domain.
• A deep immersion into the world of the customer through ethnographic methods.
• Competitive analysis and contrasting market boundaries based on desk research and expert
driven business modeling.
• Triangulation of both perspectives supports the creative generation of qualified product ideas
and value propositions that also allow to maintain focus throughout innovation projects.
Immersion into students’ lives is meant to yield insights into the nature of learning activities andchallenges, reoccurring routines, obstacles, workarounds and problems as well as unfulfilledneeds and values. Participant observers of students focus on unmet, hidden and newly emerging
needs, values and motives and pay attention to workarounds in order to lay the direction forpotentially novel perspectives and solutions. In order to do so it may be important to observe
students in key learning situations, individual and social ones, in their homes and at otherlearning locations; to explore both digital and analog ways of studying, organizing material andnote-taking etc.; and to investigate what it means to be a student today more broadly. In order to
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  analyze the current market desk research may proceed top down starting from global trends (suchas the trend towards lifelong learning or the increasing importance of peer learning), or bottom up
looking up relevant keywords in order to retrieve inspiring cases in terms of new products, newbusiness (e.g. startups and corporate ventures) and emerging platforms and ecosystems. Most
interesting cases may be shortlisted based on criteria such as e.g. market reach, novelty, time tomainstream adoption and attractiveness of the business model being pursued.
Looking into a specific market or product category (such as learning-management systems ordigital textbooks) competitive factors of existing offerings represent the dimensions on which
products within this category compete, e.g. the price or feature range or editing capabilities of adigital textbook. In blue ocean strategy a “value curve” is used to depict corporate or productscores on the main competing factors. The value curves of competitors are used to identify
potentials for variation and extension. The so-called “four actions framework” promotes fourkinds of variation to the main competing factors within an industry in order to generate a newbuyer value curve. Variation eliminates, reduces or raises factors below or above the industry’s
standard or (in line with our approach to identify empirically grounded value innovation) creates
new factors. It aims at increasing buyer value by optimizing utility and price, and to increase
company value by optimizing price and cost structures (Kim & Mauborgne, 2005, 17). The
identification of new competitive factors plays the decisive role in the attempt to create
substantially new value for users. Several methods may be applied to identify new and uniqueproduct factors (such as a learner-centered modularity of content organized around learning goals
in the case of digital textbooks). The ethnographically grounded approach to value innovation
bears the greatest potential to introduce new product factors to blue ocean analysis based on a
profound understanding of changing values of individuals and society. Such understanding is asound basis for knowing which factors to eliminate-reduce-raise-create, and for knowing why to
do so.
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  Triangulation makes it possible to scrutinize a problem from various sides in order to validate
results and enable a broad understanding from multiple angles. The methodological and data setstriangulation suggested here can be also complemented by a triangulation with respect toresearcher (see Figure 2 below). According to Denzin (1970) researcher triangulation involves
different researchers during observation or data analysis. It is based on the assumption thatparticipation of more than one researcher can mitigate the problem of conflicts of interest that
may appear if it is the same researcher who both formulates a theory and empirically examines its
research results. Also, different skills and backgrounds on behalf of different researchers mayenrich the elaboration of results.

Figure 2 Triangulation of methods (I ethnography and II blue ocean), research teams (I anthropologists and II market
researcher) and data sets (I on student life and values and II market state and benchmarks); results are synthesized inworkshops aiming to find ideas for value innovation through interference of diverse knowledge types.

In this case, triangulating an empirically grounded understanding of learner values withknowledge about alternative market positions creates a productive foundation for identifying
qualified ideas for new value propositions and offerings. Doing so still requires a vivid
confrontation of different perspectives and (implicit and explicit) knowledge. The typical format
for this is a workshop where carefully selected representatives bringing to the table different
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Volume 2 - Issue 1 - Winter	  kinds of knowledge interact in a live environment. A moderator and group exercises pushparticipants to take their thinking off the beaten tracks of convention. Shifts in perspective arefurther encouraged through external participants, a thorough preparation and utilization of
instructions and media, and specific communication techniques like ad-hoc visual documentationof discussions. Such an interactive environment of changing conditions aims at helping the actors
generate new knowledge and ideas.
A Case on Learner-Centered Design

As an illustration for describing the approach and methodology for identifying a potential value
innovation we use a recent innovation project in higher education in Germany. The project had
the goal to identify potential new learner-centered tools and services for university students withhigh business potential. As suggested above, three different research methods were applied andcombined to achieve a broader and deeper understanding of the topic at hand: Ethnography, desk
research and blue ocean market analysis. The ethnographic part and the analytical part were eachperformed by two different research teams from different service providers; one specialized inmarket analysis, the other in ethnographic research.
Ethnographic research setup and results
One of the main challenges was to capture the broad variety of today's students’ learning
activities interests and values – and to find corresponding participants. Our sample contained 11
students between 19 and 27 who studied in or around Berlin, Germany. We strove for a balance
between female and male, freshmen and advanced students, and students from different
disciplines (law, business, and social sciences & humanities). The context and content of learning,learning techniques applied, as well as learning problems and needs differ widely depending on
the discipline or desired degree. We wanted to understand not just learning activities in a narrow
sense but also the organization of university life including issues like time management andcollaborative learning.
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Volume 2 - Issue 1 - Winter	  The ethnographic research had two parts: participatory observation with ethnographic in-depth
interviews followed by self-observation with online diaries. The observation aimed atunderstanding students’ daily routines and different learning situations in order to identify latent,
unmet or newly emerging needs and problems. Researchers participated in lectures and seminars,
accompanied the students to study groups or library visits. The observations usually took two to
three hours and were followed by a three-hour semi-structured interview in the student’s familiar
environment, usually their home. The interviews were designed to explore students’ motivation,
their social interactions, their learning behavior and strategies, the digital and analogue tools theyused and student life in general. The second research part consisted of a five-day online diary.
Students were asked to describe their learning activities, the use of digital and analogue tools, andpotential problems and challenges. They were also encouraged to describe their motivation,
dreams and ambitions by using pictures and short texts. The self-descriptive data helped to enrichand put into perspective the insights gained during field research.
The results were analyzed in a ten-day process of identifying patterns in the data collected andsubsequent insight development. One result, for example, revealed that most of the students were
struggling with time problems. Due to increasing study and difficulties to efficiently manage thetime, nearly every student complained about running out of time and time pressure. Literature
research, for example, appeared to be an especially time-consuming and costly activity. One of
the students complained about finding and getting literature: “I usually dedicate my Saturdays forsearching for books, getting them, going through them and copying the chapters we need.” Other
students reported on their struggles with limited access to online books and journals, especiallyfrom home, difficulty in assessing which article or book is worth reading, lack of overview andcentralized control over different lending sources and costs caused by purchasing articles andlending fees. The observations also revealed some workarounds such as for instance checking
reviews in Amazon before lending a book in order to save time.
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  More specifically, ethnographic research and analysis led to four different need or value clusters:
1. “Quality of learning” was reflected by students’ complaints about poor quality of educational
materials and a lack of support when needed. The cluster also refers to students’ concerns
about the quality of their education and their needs for effective learning techniques, from notetaking and marking up digital content to understanding and memorizing content.
2. “Motivation” illustrates students’ needs for motivational support during the semester and thewhole period of studies, their wish to sweeten study activities through little rewards andpleasures, their strong desire for feedback on learning outcomes, and their need to assess laborand time investments and progress in knowledge and skills.
3. The “efficiency” cluster describes students’ need to manage time and organize learning
activities efficiently in an environment free from distractions. This includes the need tocoordinate group activities and exchange insights and materials, also easy literature searchingand quick access.
4. “Productivity / organizing” deals with students’ need for easy-to-use resources, well organized
and managed study material, a flexible move between analogue and digital material, as well as
ubiquitous but one-place access.
These results were then explored in a concept workshop with the goal to develop product ideas
based on the obtained student needs.

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Volume 2 - Issue 1 - Winter	
  Desk Research and Blue Ocean
In order to understand the educational market and educational trends a comprehensive desk
research was conducted based on a wide screening of relevant publications and start-ups in thefield of education. It identified a number of socio-economic and technological drivers, such as a
growing demand for education and reorganization of knowledge, to name just a few. Based onthese drivers six key educational trends were derived. Examples include:• Open education: the growing amount of teaching content online and learner-generated content
available (Breuer & Matsumoto, 2011),• Edutainment – implementation of game mechanics in processes of learning, and• Enriched content – integration of audiovisual interactive and social media elements into
traditional content formats.
Some of the trend fields that resulted from desk research (e.g. enriched digital content) wereselected for close examination. A blue ocean workshop was designed to identify various value
curves of brands and products in order to distinguish the potential new business from its
competitors. Creative sessions involving “learning from other brands” and “brainstorming withmegatrends” revealed competitive factors for developing an innovative learning management
system e.g. based on an increase or creation of flexibility, openness, personality development,
emotions, fun and world of experience. Informed by the trend of enriched digital content and theempirical student need to quickly assess and find suitable literature, the attendees created new
ideas for modular digital textbooks such as the concept of “Digital ConText Book” (see Figure 3
below).

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

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Figure 3 The value curve depicts depict corporate scores on the main competing factors of digital content providers.

Its modular structure allows to focus on educational content and learning goals. Students can
purchase and work with relevant parts of a publication and do not have to buy an article or a book

as a whole. They can also subscribe to topics they are interested in to get content from different
journals, papers, single chapters of a book. In addition, learning materials, learner-generated

content and documents can be matched to one’s personal learning progress. Students can viewand edit content that is created or organized and validated by a lecturer. The idea of a “Digital
ConText Book” satisfies different needs identified through ethnographic research, e.g. the needfor easy literature searching and access from different work locations. It offers efficiency that do
not exist on the market yet and an added value by guaranteeing high quality of materials,
providing flexibility in note taking and text marking, and allowing feedback on the progress inknowledge and skills, thus providing for a sense of overview and success.
Synthesis
Due to integrating the two perspectives of ethnographic research and blue ocean analysis theobtained results enriched and encouraged each other. On the one hand student needs and values,
desires and problems described above could not be identified through desk research or blue ocean
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  strategies but rather only through a deep immersion into the students’ worlds by using
ethnographic methods. On the other hand ethnographic research cannot yield an overview overthe educational market, its competitors and market niches. Only in combination can the derived
ideas create a new market and meet customers’ needs at the same time. Results of eachmethodological approach have not only enriched each other but also encouraged the project
teams’ assumption that the search field of higher education bares substantial and qualified
business opportunities. These are based on uncovered customer values and needs and may beserved by an industry that currently does not provide them.
Conclusions
We described a green-field approach on how to drive innovation in user- and learner-centeredsolutions based on an empirical understanding of student values, needs, and requirements (e.g. interms of efficiency and time-management). Ethnographic results and a clear understanding of thestrategic market position based on extended value curves informed strategic decisions andspecification of propositions. Novel solutions were generated e.g. providing enhanced contexts tolearning materials. Encouraged through their participation in the discovery of real user needs,
values and strategic options, the business owners gained sufficient confidence in the concepts toinvest in their development within a newly found business unit. First patent applications areunderway. Their specification, implementation, marketing and validation in the marketplace arework in progress. Future review must show if a potential success of propositions may be traced
back to these value-based concepts. So far, understanding user values, needs and desires, andstrategic market analysis already created the indispensable basis for the attempt to develop new
and relevant products and to establish sustainable business.

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  Acknowledgements
Many thanks to Gregor Erkel and Friedrich Kurz for enabling the project and for contributing
essential ideas. They are working hard to turn these ideas into reality. We also thank ourcolleagues from User-Driven Innovation at Telekom Innovation Laboratories, Trommsdorff &Drüner, and Point Blank International for their support.

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  References
Atkinson, P., & Hammersley, M. (1994), Ethnography and participant observation. In N. Denzin& Y. Lincoln (Eds.), Handbook of qualitative research. (pp. 248-261). Thousand Oaks, CA:
Sage.
Baudrillard, J. (1991), Der symbolische Tausch und der Tod (Symbolic Exchange and Death).
Munich: Matthes & Seitz.
Bockhahn, S. R., & Schwarz, H. (2010), Anthropology as a tool for business innovation.
Ethnoscripts. 12 (2).
Boztepe, S. (2003), The Notion of Value and Design. Proceedings of the 6th Asian Design
International Conference, Tskuba, Japan, October 14-17, 2003.
Breuer, H., & Matsumoto, M. (2011), Ubiquitous Learning Environments: Notions of Context,
Application Scenarios and Reflective Stories. In T. Bastiaens & M. Ebner (Eds.),
Proceedings of World Conference on Educational Multimedia, Hypermedia andTelecommunications 2011 (pp. 2366-2374). Chesapeake, VA: AACE. Retrieved February
04, 2014, from http://www.editlib.org/p/38189
Breuer, H., & Steinhoff, F. (2010), Grounded Innovation – A Research Approach for the Fuzzy
Front End of Innovation Management. Proceedings of BAI International Conference on
Business and Innovation: Vol. 7 (ISSN 1729-9322). Kitakyushu, Japan.
Cefkin, M. (2009), Ethnography and the Corporate Encounter. New York: Berghahn Books.
Denzin, N.K. (1970), The Research Act in Sociology: A Theoretical Introduction to Sociological
Methods. London: Butterworth.
Jordan, A. (2003), Business Anthropology. Long Grove, IL: Waveland Press.
Kim, W.C., & Mauborgne, R. (2005), Blue Ocean Strategy. How to Create Uncontested Market
Space and Make the Competition Irrelevant. Boston: Harvard Business Press.
Lindlof, T., & Taylor, B. (2002), Qualitative communication research methods (2nd ed.).
Thousand Oaks, CA: Sage.

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  Mariampolski, H. (2005), Ethnography for Marketers. A Guide to Consumer Immersion.
Thousand Oaks, CA: Sage.
Marx, K. (1962), Das Kapital. Band I. Kritik der politischen Ökonomie. (Capital. A Critique of
Political Economy). In Karl Marx - Friedrich Engels - Werke, Volume 23, (pp. 11-802),
Berlin: Dietz Verlag.
Schrage, M. (2012), Who Do You Want Your Customers to Become? Boston, Mass.: Harvard
Business School Publishing.
Sutherland, P., & Denny, R. (2007), Doing Anthropology in Consumer Research. Walnut Creek,
CA: Left Coast Press.

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Volume 2 - Issue 1 - Winter	
  Student Attitudes about Distance Education:
Focusing on Context and Effective Practices.
Esther Smidt, Jennifer Bunk, Bridget McGrory, Rui Li, Tanya Gatenby
	
  

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  Abstract

There has been an unquestionable upsurge in distance education in recent years. Given this, it isextremely important to understand the experience of online courses from students’ perspectives.
The purpose of the current qualitative study is to understand student attitudes about distanceeducation in a specific context, namely that of a Mid-Atlantic mid-sized state university. We thentranslate our findings into practical recommendations for instructors. Data sources consist ofjournal entries written by 36 teacher candidates taking the course, Teaching English Language
Learners PreK-12. Findings are categorized according to Course Characteristics, e.g. students
have definite opinions about the use of the discussion forum, some of them negative, Instructor
Characteristics, e.g. students see the need for interaction/synchronous communication andeffective assessment, and Learner Characteristics, e.g. the appropriateness of distance education
depends on student learning style and practical factors.

Keywords: Distance Education; Student Attitudes; Effective Practices.

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Volume 2 - Issue 1 - Winter	
  Introduction
There has been an unquestionable upsurge in distance education in recent years. Between 2002
and 2011, the percentage of college students who were enrolled in at least one online course
increased from 9.6% to 32% (Allen & Seaman 2013). Given this, it is extremely important tounderstand the experience of online courses from students’ perspectives. The ultimate
beneficiaries of online education are, after all, the students.
The purpose of the current qualitative study is to understand student attitudes about distanceeducation. To clarify, first, this study is student-focused and not faculty-focused. While we
acknowledge the importance of investigating faculty attitudes about distance education, our goal
is to move the spotlight onto students as well. Second, our focus is on attitudes, which have beenclassically defined in the social psychological literature as “an evaluation or evaluative judgment
made with regard to an attitudinal object” (Weiss 2002, p. 175). Thus, student distance education
attitudes represent cognitive assessments made by students regarding distance education.
We extend previous research in two ways. First, we prioritize student needs in a specific context
by focusing on students from a mid-sized state university in the Mid-Atlantic region of the UnitedStates. Our goal is to understand the attitudes of these particular students in order to direct ourefforts accordingly. We thus acknowledge that online learning phenomena can be, and often are,context specific (Gibbs 2010). Second, we direct attention towards effective practices. Findings
have little practical use if they do not result in actionable knowledge. Therefore, we will translate
our findings into practical recommendations for instructors (along with the necessary contextual
caveats). Although changing teaching practices can be difficult, there is evidence that prior to
making changes, instructors rely on student needs more than empirical findings (Price &Kirkwood 2013). Our student-centered practical approach will conceivably inspire instructors tomake incremental changes to their online courses that will increase effectiveness and satisfaction.

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  What follows is a two-part review of the literature. First, we will present an overview of distanceeducation research. Then, we will review empirical findings that are relevant to the focus of ourcurrent study.
Literature Review
Distance Education Research: An Overview
Kehoe, Tennent and Becker (2005) provide a useful framework for understanding distanceeducation scholarship. Essentially, they divide the distance education experience into three parts:
online material delivery, online assessment, and online interaction and engagement. With regard
to online material delivery, research in this area is focused on the use of different delivery
modalities including synchronous versus asynchronous (e.g., Carswell & Venkatesh 2002), andspecific tools like discussion boards (e.g., Chapman, Storberg-Walker & Stone 2008) and
WebCT (e.g., Osman 2005). Research focused on online assessment is concerned with quality
and learning outcomes. For example, multiple meta-analyses have been conducted comparing
learning outcomes in face-to-face versus online courses (e.g., Bernard, Abrami, Lou,
Borokhovski, Wade & Wozney 2004; Means, Toyama, Murphy, Bakia & Jones 2009; Sitzmann,
Kraiger, Stewart & Wisher 2006).
The third area that Kehoe, Tennent and Becker (2005) discuss is our area of focus: online
interaction and engagement. Researchers in this area tend to be interested in student satisfaction
and similar attitudinal variables. We will examine empirical findings in this area in the second
part of our literature review. For now, it is worth stressing the utility of focusing on attitudinaloutcomes like satisfaction. Not only is there evidence that attitudes about technology are related
to performance outcomes (Petter & McLean 2009), but they can also help inform best practices.
For example, if we know that students are dissatisfied with the amount of technical support they
are receiving, we can focus our efforts on increasing the quality of such support. Another reason
that focusing on attitudinal outcomes is so important is that they are a necessary piece to the
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  bigger picture. In other words, if our ultimate criterion is “success in distance education,” thatcriterion would be deficient if we focused solely on learning outcomes. It would be difficult toargue that an online class was completely successful if the students learned a lot but did not havepositive attitudes about the experience.
Student Attitudes about Distance Education: Empirical FindingsInternal Factors
One of the goals of the current study is to prioritize student needs by taking a student-centeredapproach to understanding attitudes about online coursework. Part of doing so means
acknowledging that students’ individual differences—or factors internal to individuals—aregoing to play a role in predicting satisfaction. To this end, a variety of studies in this area havefound exactly this. For example, Sun, Tsai, Finger, Chen and Yeh (2008) found that learnercomputer anxiety was a critical factor in predicting satisfaction with e-learning. In this survey
study, computer anxiety was defined as feelings of nervousness and discomfort when working
with computers and satisfaction with e-learning was defined as students’ overall sense ofsatisfaction with the e-learning course in which they were enrolled. In addition, Holley andOliver (2010) used a biographical narrative approach to explore students’ accounts of online
learning. Analysis of the student narratives revealed that students’ ability to control technology,
along with students’ educational experiences and expectations of managing their “learning spaces”
played a role in students’ engagement with online learning.
Moreover, the utilization of asynchronous communication tools, such as discussion boards, also
points to the dissimilarities in student preferences which may be based on internal, individual
differences. For example, Gilbert, Morton, and Rowley (2007) found that while 68% of students
they surveyed were comfortable using discussion boards, 32% were “not sure” or “uneasy” aboutthem.

In addition, according to Osman (2005), 70% of students felt more comfortableparticipating in an online discussion forum compared to an in class discussion. These differences
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Volume 2 - Issue 1 - Winter	  in attitudes about discussion boards could be attributed to personality differences, where an
introverted student may enjoy the feeling of anonymity created by participating in an online
discussion compared to a face-to-face discussion.
Other studies have investigated satisfaction with the quality of online interactions. For example,
Felix (2001) found that students had a negative attitude towards online learning when there wasinadequate personal interaction. According to the results of this study, 10 students noted the lackof presence of a teacher to be a disadvantage compared to the 3 students who felt the exact
opposite—that it was an advantage. Additionally, Lee, Srinivasan, Trail, Lewis and Lopez (2011)
also found that students valued and benefitted from interaction with instructors and peers. When
students were asked, “How could this course support your learning better?” interaction withteachers and peers was found as a primary solution. Lee et al. proposed an online or on-campus
study group as a means to avoid feelings of isolation and discomfort with a lack of interaction.
These effects related to interpersonal interaction could be due to personality differences. For
example, an extroverted student may thrive on classroom interaction, feeling it is necessary totheir understanding of the material. In particular, this extroverted student may value the directinteraction with a teacher.
Continuing with the exploration of internal factors affecting students’ attitudes towards distanceeducation, it would appear that one’s self-discipline and drive will also play a role. A student
lacking motivation may find it difficult to stay focused while completing online assignments.
Smart and Cappel’s (2006) findings support this belief as students who were interested in thematerial or identified with it demonstrated a higher level of motivation. Additionally, disinterestand distraction could explain some students’ negative attitudes. Felix (2001) attributed distraction
to the “wealth of information” offered by online learning, a problem he proposed was not as
prevalent during the age of CD-ROM-based online learning. Currently, while participating in

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  online course work, the wonders of the internet and the potential for distraction are only a click
away.
Interaction with External Factors
These internal factors affecting students’ preferences are also influenced by external factors suchas enrollment in an elective versus a required course. In a study by Smart and Cappel (2006)
exploring students’ perception of online learning, students enrolled in an elective course rated
online classes positively, while those in a required course rated the online classes negatively.
Those students enrolled in the elective course felt online learning was “an effective way to learn,”
was “fun,” and were more likely to take online classes again in the future. This could be a resultof the degree of interest in an elective versus a required course or the level of motivation or selfdiscipline of the students.
Another factor that can affect students’ online course satisfaction is experience with technology.
A lack of experience can interact with the existence of technological problems to heighten
dissatisfaction. For example, Smart and Cappel (2006) suggested that students with more
technological experience would be more likely to take an online class than those who did nothave experience. They also suggested that the potential for technological problems andinexperience with technology could make lengthy assignments seem even longer and could
potentially contribute to the frustration students feel with the amount of time required to complete
online coursework. Indeed, Smart and Cappel found that 30% of students in their sample felt as if
the amount of time it took to complete online assignments was not worth what was gained.
Having experiences in an online learning unit in a blended context may likely benefit students inthe future as they make decisions about selecting between different educational or training
options. The results may suggest that students with more experience with technology and elearning rate it more positively.
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  Students taking online courses value control over course content and this can interact with the
choice of learning tools affecting satisfaction. Mockus, Dawson, Edel-Malizia, Shaffer, An, andSwaggerty (2011) demonstrated students’ preferences for control in their online learning
experience via a mobile learning study. Students used Androids, BlackBerrys, iPhones, iPhone
Touches, and iPads as platforms to access course material. Findings revealed that students foundcourse content delivered to their mobile device to be motivating and they enjoyed learning thisway. The authors explained that this pointed towards the desire of students to engage inpersonalized learning. This demonstrates the importance of taking students’ preferences into
account, and utilizing effective tools to address these preferences to ensure continued satisfaction
and participation in distance education.
External Factors
It is also essential to explore the role of external features on attitudes towards online learning.
Another goal of the current study is to highlight the importance of these external components inunderstanding student attitudes about distance education. Several studies have found that adiverse set of external factors can predict student attitudes. One factor is the length of files to be
downloaded, which will become increasingly important as instructors rely on more sophisticatedmultimedia like videos and podcasts. Related to this, Bolliger, Supanakorn, and Boggs (2010)
investigated the impact of podcasting on student motivation and found that the length of files
could have an impact on a learner’s level of satisfaction. Specifically, some students felt
downloads took too long, potentially causing them to lose focus.
Another external factor to consider is the kind of multimedia used in an online course. Boling,
Hough, Krinsky, Saleem, and Stevens (2012) found that online classes that relied heavily on textbased multimedia were very unengaging and not effective in helping students to learn. Theysuggested that the use of interactive Web 2.0 tools could be more effective. Furthermore, Boling
et al. proposed that the accessibility of instructors and information had an effect on determining
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Volume 2 - Issue 1 - Winter	  the overall impression of distance education, which was largely based on the design of online
programs.
Students’ perception of support is another external factor that can affect students’ attitudes.
According to a study by Lee et al. (2011), students’ perception of support had a positive
relationship with their degree of course satisfaction. When the above discussed technologicalproblems or assignment confusion takes place, it is imperative that students feel that they caneasily contact their instructor or an Information Technology (IT) staff member. Indeed, in a study
by Gilbert et al. (2007), comfort with the amount of support offered was positively related to
students’ satisfaction with their online learning environment. As further evidence for theimportance of support, Gilbert et al. (2007) found that a lack of resources and outdated materials
could leave students feeling dissatisfied and unhappy with their online learning experience. In
addition, Lee et al. also found course satisfaction to have a small yet notable correlation withfinal grades. This points to the importance of designing courses with a range of options of supportand resources. As Lee et al stated, “access to a learning experience that is tailored to his/herlearning style…may result in a more favorable course satisfaction” (pg. 161) and with that,
potentially higher grades.
Felix (2001) also found that several other external factors could impact satisfaction with online
courses. Specifically, he found that time flexibility, reinforced learning, privacy, wealth of
information, ability to repeat exercises, and gaining computer literacy were all cited asadvantages of online learning by students. This is promising, as it suggests that students
appreciate the pedagogical benefits of distance education and that online instructors should dowhat is possible to increase these factors in their classes.
In summary, our review of the research related to students’ attitudes about online learning reveals
that a combination of both internal and external factors can affect student attitudes. In addition, it
is clear that both positive and negative attitudes towards online learning exist. Our goal with the
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  current study is to build upon this research by prioritizing student needs in a specific context andidentifying best practices.
Methodology
As intimated in the Literature Review, the research question of this qualitative research study is:
What do students think about distance education?
Data sources consisted of 36 journal entries written by 36 teacher candidates taking the course,
Teaching English Language Learners PreK-12, after listening to a research presentation entitled“Reactions to and attitudes about asynchronous online discussion forums in an online faculty
development program.” Particulars about the 36 teacher candidates are as follows:
Level

NumberColleges

NumberFreshmen2

College of Education

16

Sophomores

5

Health Sciences

6

Juniors

12

Arts and Sciences

11

Seniors

10

Visual and Performing Arts

1

Graduate

7

Undeclared

2

Total

36

Total

36

We, the first three co-authors, met weekly and kept researcher journals. We underwent training in
NVivo 10, a qualitative research software. We then divided the journal entries into three groups,
one per researcher, and created nodes. After this first pass, we compiled a nodes master list andrecoded the journal entries, resulting in the following 16 nodes:
Nodes
OnlinePositive
Negative
Discussion Board
Interaction
Neutral
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References
71
67
63
46
34
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  Flexibility
Learning Style
Online Experience
Assessment
Blended Learning
No Online Experience
Workload
Synchronous
Experience
Face-to-Face

24
22
17
17
14
12
11
4
3
2

We then combined the three groups of journal entries and separated the nodes into “Negative”
and “Positive” categories, as follows:
Negative
Nodes
Online45
Discussion Board
24
Interaction
17
Learning Style
8
Workload
8
Online Experience
7
Assessment
6
No Online Experience
3
Positive
2
Blended Learning
2
Neutral2
Flexibility
1

Positive
Nodes
Online26
Discussion Board
26
Flexibility
20Interaction
12
Learning Style
11
Blended Learning
9
Online Experience
9
Assessment
4
Synchronous
3
Workload3
Negative
2
Face-to-Face
2
No Online Experience1

As an analysis of the tables above reveals, some nodes were consistent in placement in both thenegative and positive categories, for instance Online, Discussion Board, Interaction, Learning
Style, Online Experience, and Assessment, while other nodes occupied obviously different
placements, for example Flexibility, Workload, Blended Learning, and Synchronous.

We then conducted triangulation where we looked for representative excerpts of arising themes.
While we were doing this, we realized that most of the nodes coded in negative and positive
categories were related. We thus ended up recategorizing the nodes according to the themes of
Course Characteristics, Instructor Characteristics, and Learner Characteristics, which are the first
three learner satisfaction factors identified by Sun et al. (2008). It should also be noted that the
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  first two themes of Course and Instructor Characteristics would be subsumed under the External
Factors mentioned in the Literature Review while the Learner Characteristics would be
categorized under Internal Factors.
Discussion
Course Characteristics
Discussion Boards
The lack of well-designed tasks, particularly as they relate to discussion boards, was a negative
course characteristic students felt keenly. Students saw ill-designed tasks as busywork. Amongexamples cited include uninteresting coursework that incorporated closed-ended questions thatstudents could answer without actually having read the text. Students were also dissatisfied withthe preponderance of tasks that catered to visual rather than auditory or kinesthetic learners (8references of Learning Style/Negative). Implicit in these examples are the negative uses of
discussion boards, as demonstrated by 24 references of Discussion Board/Negative. Indeed, NB2
lamented that a too structured prompt stifles creativity:

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  In terms of structured assignments, professors should keep in mind that even the smallest
idea can spark thousands of new ideas within the minds of students, as everyone has adifferent perspective and might see something in a prompt that others might not see. WhenI see a prompt with a bunch of questions that need to be addressed, or that requires acertain number of posts, I lose all creativity. My response suddenly becomes aboutanswering the question, meeting my minimum post requirement, and calling it complete. A
discussion board that has too many guidelines or requirements feels like being given a
picture and told to color inside the lines. It dismisses any chance for creativity or
individuality by having all students conform to the same old cookie-cutter answers that
get the good grades.
The desire for creativity, collaborative learning and opportunities for open expression is aptly
encapsulated by NT:
My other two classes at my community college were way better, because they wereactually hands on. One of my teacher[s] would ask us to do something crafty, or makethings out of clay or blocks (it was teaching elementary education). After we would create
things she would ask us to take a picture of our ideas and post them. Then we would be
able to view everyone’s creative ideas and learn from each other. It did not always
involve writing, which I found to be excellent! I felt as though I was actually learning
something.
NT’s journal entry reiterated the point that asynchronous discussion does not have to be boring,nor does it have to leave out auditory and kinesthetic learners (11 references of Learning
Style/Positive). HM, however, highlighted the benefit of synchronous audiovisual communication
for multiple learning styles: “In my ideal online class, instant chat or Skyping with a professor
would be the best situation for learning.”

This sentiment is reiterated by 3 references ofSynchronous/Positive—there were no references of Synchronous/Negative.
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  Other positive experiences of discussion boards included the use of discussion leaders, groups,
and different types of discussion boards (non-course boards and boards for general course
questions). NB1 also specified the attraction of student generated questions:Also, online courses always have assigned discussions. I had to for my summer course
pick an article and ask my class questions one time. Then every other week I answered
everyone else[‘s] questions. I think this was the most effective discussion methods, to havethe students direct the questions because we were talking about what interested us.
Students’ positive experiences about well-designed discussion board activities were demonstrated
by the 26 references of Discussion Board/Positive.
Students also suggested two features that would make discussion boards a better experience,
firstly by making previous posts invisible:
I liked the idea of making other students’ posts invisible because it will encourage them to:
Actually do their own work and [d]o their work on time, because they will be forced tothink of their own answers instead of re-wording a compilation of their classmates work
five minutes before the deadline. (NL)
Secondly, students complained about the inability of their being informed about reply posts,
especially in situations where there was a significant lag time between posts and replies:
In online classes however, it is not as easy to communicate because the response is not
immediate. If I did have a question, or presented an argument, the other person may not
respond for a few days and I will forget what I was talking about. (FC)It should be noted that the new version of the Learning Management System allows students to
subscribe to particular threads so that they are informed of replies to their posts.
Learning and Distance Education
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  There appeared to be some misconceptions about learning and distance education on the part ofstudents that require some reeducation. Three participants considered collaborating and using
supplementary materials and textbooks for assessment purposes to be cheating. DR2, for example,
appeared to believe that learning consists of memorizing information and retaining knowledge:
Many times, classes that are online just state the facts and have open book tests andquizzes, which don’t benefit the students. This is due to the fact that they are not learningand memorizing the information and retaining this knowledge, rather looking up facts topass a class. Since the students aren’t technically required to know the material, I feelthat many online classes are easy A’s and do not benefit everyone.
Related to the excerpt above is the assumption by four participants that online courses are notrigorous and difficult—“you should not take any of your core major classes online” (UM1) and“it is [not] beneficial to the overall education of the students to have a 300 or 400 level classonline” (LG) because “[a]lthough they say online classes are more convenient, they areprobably the most neglected classes that students leave until last minute” (FC).
Underlying these misconceptions may be the philosophy that a face-to-face class occurs in the“real world” (SG) while an online class does not. Moreover, “too much technology creates asocial barrier between students and teachers” (SP). Indeed, SP goes on to state categorically that:
While I believe that some online learning activities are okay, too much of anything is
excessive. I am completely against online learning and it truly scares me for the future of
my career. I want to teach students in a real classroom in a real school, in person.
While no one would argue that face-to-face interaction is not real, the converse, that online
interaction is fake and problematic, especially in a world that is moving exponentially towards
social networking and telecommuting.
Blended Learning
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  Blended learning is one of the nodes that had different placements within the negative andpositive categories, namely 9 references of Blended Learning/Positive as opposed to 2 referencesof Blended Learning/Negative. BG1’s excerpt is representative of the positive attitudes about
blended learning:
and also one of my Tues/Thurs classes had in-class learning every Tuesday and online
learning/assignments due every Thursday. This was my absolute favorite because it
enabled us to meet with the teacher and our classmates at least once a week, yet we could
complete our assignments and outside of the classroom learning on our own time. I felt
more independent this way and my grades were actually better than the typical in-classonly learning. To me, this type of learning felt more like what I'd expected college tobe...what it was "supposed" to be, where our grades and how much effort/energy we put
into an assignment was totally on us.
Instructor Characteristics
Interaction
The lack of interaction, whether instructor-student or student-student, was one that students felt
keenly, as demonstrated by 17 references of Interaction/Negative (and confirmed in Felix 2001).
In particular, their inability to depend on non-verbal communication resulted in students’preference for agreeing with posts:
Interaction is key not only with your professor but also with your classmates. When you
don't see someone face-to-face, you don't know anything about them. You don't know their
tone of voice, their personality, etc. For this reason, in prompts like "respond to aclassmates thoughts", I usually look for ones that I agree with, because it's first of alleasier to agree with someone th[a]n it is to argue with them, but you also don't have to

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  worry about offending anyone, or coming off as rude, since the people you are interactingwith don't know your tone or your personality. (ML)This finding is illuminating since it provides a glimpse to the reason for the lack of criticalthinking in some discussion posts.
Instructor Support, Student Autonomy, and Workload
A familiar complaint, as demonstrated by 8 references of Workload/Negative and confirmed by
Smart and Cappel (2006), is that online courses have heavy workloads requiring student
autonomy and what students perceive to be a lack of instructor support:
My personal opinion about online classes is that online classes place more responsibility
and time on the student[s], rather than the professor. In previous online classes I havetaken, I found that I needed to spend more time throughout the week focusing on my
online classes than my classes that were face-to-face. I did not get the opportunity toattend class one to three times a week, and learn the information auditorally [sic].
Instead, I was teaching the information to myself over the course of many days. Also, I did
not find it appropriate that online classes had different assignments due all throughout
different times in the week. This resulted in confusion for both me and my classmates.
Whereas in a face-to-face class, assignments are usually due on the date that you attend
class. (FP)Organization and Clarity
Students also desired specific instructor characteristics, for example, prompt feedback and e-mailresponse from the instructor, and clear instructions and assessment requirements (asdemonstrated by 6 references of Assessment/Negative):
The way the teacher grades assignments is also unclear in online classes. In my current
class, my teacher is not clear with what she wants in her responses and as a result, someof the students are not doing as well as they deserve. (FC)
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Volume 2 - Issue 1 - Winter	  In particular, strong organizational skills were highly appreciated:
At the beginning of the semester everything was posted on the online syllabus and she
strictly followed the syllabus. For example, we even knew when ou[r] final was going to
be due months ahead of time. I loved her organization. (NT)
Learner Characteristics
Flexibility
One of the greatest advantages of online courses is students’ ability to decide when, where, andhow coursework should be completed, as demonstrated by 20 references of Flexibility/Positive.
This is particularly true for students who emphasize self-paced learning and possess an
independent learning style:
Another benefit to taking online classes is that it makes one’s schedule more flexible.
Instead of spending time in a classroom, online classes allow students to spend time intheir homes. Because almost all of the assignments are posted online, students cans[p]end as much or as little time on each assignment as they think that they need. Also,
some students learn and work better on their own time. Instead of sitting in a classlistening to a teacher lecture, students can read a textbook on their own or teachthemselves the material that they need to know. Also, if they need more time to work on anassignment, they are not restricted because they have all the time that they want to figureout a problem (LB)

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  Shy/Introverted Students
As confirmed by 3 participants, and reiterated by Osman (2005), shy or introverted students
express satisfaction with online courses:
But, on the other hand, I am a shy person, and I don’t normally speak out in class,especially in response to another student. I would never disagree with someone in class,so an online aspect makes this part better for me. I feel that I am able to actually speak
my mind through the computer, and not worry about someone judging my every spoken
word in class. Through typing, I am able to take my time to think out my response, or
erase my previous thought in order to rewrite my answer. (DR1)
I feel that online classes allow students to freely and openly express themselves,especially if the students are on the quieter side. Online classes allow students who do not
actively participate in classroom discussions a chance to voice their opinion through thecomputer. The safety of an online class allows shy students to show their intelligence
without feeling as self-conscious and worried about their responses. (DR2)Student Investment
Conversely, a lack of student investment would adversely affect student performance andsatisfaction in online courses. The lack of a captive audience and the need to be physically at acomputer with its distractions (Felix 2001) and technical problems are issues students have toface, as stated by QE:
I am not going to spend more time with the online class than I have to. I will just write mypost, fulfill the requirements, and then get on with my day. If there is a discussion in class
I might as well participate because I have a certain time frame blocked out of my day to
be in that class.

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  Practical Applications
This paper began with the argument that it is important to investigate students’ attitudes about
distance education—that their thoughts and feelings matter. These attitudes vary based on
students’ individual differences. For example, the introverted students in this study thought
differently about online courses when compared with their extroverted counterparts. It is also
important to consider context, e.g. commuter students or students who work full time think
differently about online courses when compared with traditional, on campus students. In otherwords, it is simplistic to decide that ‘face-to-face courses are always better’—online courses may
be better for some students in some contexts while face-to-face courses may be better for otherstudents in different contexts.
Having said that, here are six practical applications that can be drawn from the findings of thisstudy:
1. Implement discussion boards carefully: Ensure that tasks are well designed—they should
encourage critical thinking, creativity, collaborative learning, and open expression, andcater to a variety of learning styles. Avoid closed-ended questions. Instead, encourage
student generated questions. Also, task responses do not have to be text-heavy. Use
discussion leaders, small groups, and multiple types of discussion boards. Encourage
students to subscribe to discussion threads so that they will be informed of replies to theirposts.
2. Consider blended courses: These courses may be the best of both worlds, although moredata is required before this conclusion can be definitively drawn. However, students do
think very positively of these courses.
3. Focus on interaction and rapport: To make up for the lack of face-to-face interaction,cultivate instructor-student and student-student online interaction and rapport. Encourage
students to connect with the instructor and one another as individuals. Synchronous
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  audiovisual communication can feature greatly in this regard. In this way, it is hoped thatstudents would move away from a preference for agreeing with their peers’ posts inasynchronous discussion.
4. Give students a realistic preview of the course: Ensure that students understand thatonline courses require a new set of skills from them—autonomy, time management,
intrinsic motivation, and student investment. Set students’ expectations so that they can
decide whether an online course is right for them.
5. Be very organized: Explicit and clear guidelines for assignments and tasks are critical.
Prompt feedback and e-mail response is crucial.
6. Be clear about what does, and does not, constitute cheating: Online course instructors
must set clear guidelines regarding academic honesty. For example, if students are
expected to work alone for an assignment, this must be communicated. However, if
assessments are “open book,” the instructor should clearly communicate that using thebook and supplementary materials is completely acceptable.
Conclusion
By its very nature, a qualitative study is context-specific. In this instance, the findings are derived
from teacher candidates in a Mid-Atlantic mid-sized state university. Therefore, it is illuminatingthat this study’s findings confirm what has been found in previous studies and add nuances that
contribute to further knowledge in the field of distance education. Findings suggest students favor
blended learning format and value the flexibility of an online environment. This is especially true
for students who are shy or introverted in the face-to-face classroom. Students also expressedinteraction is key to course success not only with their instructor but also with their peers. On theother hand, instructors should provide clear structure and guidance in addition to educating
students about course expectations and responsibilities in online courses. It’s also important tooffer well-designed and creative tasks such as audiovisual content for multiple learning styles.
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  Using students’ perceptions about distance education to help identify best practices is a logicalapproach. We hope that these six practical applications would give instructors a place to begin as
they compare their online courses against the “evaluative judgment[s] made by [students] withregard to [distance education]” (Weiss 2002, p. 175).

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Volume 2 - Issue 1 - Winter	
  References
Allen, I. E., & Seaman, J. (2013). Changing course: Ten years of tracking online education in the
UnitedStates.

Pearson.

Retrieved

February

04,

2014,

from

http://files.eric.ed.gov/fulltext/ED541571.pdf
Boling, E. C., Hough, M., Krinsky, H., Saleem, H., & Stevens, M. (2012). Cutting the distance indistance education: Perspectives on what promotes positive, online learning experiences.
The Internet and Higher Education, 15(2), 118-126.
Bolliger, D. U., Supanakorn, S., & Boggs, C. (2010). Impact of podcasting on student motivationin the online learning environment. Computers & Education, 55(2), 714-722.
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., & Wozney, L. (2004). How
does distance education compare to classroom instruction? A meta-analysis of the empiricalliterature. Review of Educational Research, 74, 379–439.
Carswell, A. D., & Venkatesh, V. (2002). Learner outcomes in an asynchronous distanceeducation environment. International Journal of Human–Computer Studies, 56, 475–494.
Chapman, D., Storberg-Walker, J., & Stone, S. (2008) Hitting reply: A qualitative study tounderstand student decisions to respond to online discussion postings. E-Learning, 5(1), 2939.
Felix, U. (2001). A multivariate analysis of students' experience of web based learning.
Australian Journal of Educational Technology, 17(1), 21-36.
Gibbs, G. (2010). The importance of context in understanding teaching and learning: Reflections
on thirty five years of pedagogic research. Retrieved February 04, 2014, fromhttp://issotl10.indiana.edu/plenary.html
Gilbert, J., Morton, S., & Rowley, J. (2007). E-­‐learning: The student experience. British Journalof Educational Technology, 38(4), 560-573.
Holley, D., & Oliver, M. (2010). Student engagement and blended learning: Portraits of risk.
Computers & Education, 54(3), 693-700.

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  Kehoe, J., Tennent, B., & Becker, K. (2005). Using the web to enhance tertiary education
learning

experiences.

Retrieved

February

04,

2014,

from

http://ausweb.scu.edu.au/aw05/papers/refereed/kehoe/paper.html
Lee, S.J., Srinivasan, S., Trail, T., Lewis, D., & Lopez, S. (2011). Examining the relationshipamong student perception of support, course satisfaction, and learning outcomes in online
learning. The Internet and Higher Education. doi: 10.1016/j.iheduc.2011.04.001.
Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidencebased practices in online learning: A meta-analysis and review of online learning studies.
Washington, D.C.: U.S. Department of Education, Ofﬁce of Planning, Evaluation, andPolicy Development.
Mockus, L., Dawson, H., Edel-Malizia, S., Shaffer, D., An, J., & Swaggerty, A. (2011). The
impact of mobile access on motivation: Distance education student perceptions. World
CampusLearning

Design.

Retrieved

February

04,

2014,

from

http://learningdesign.psu.edu/research/MLRTWhitePaper.pdf
Osman, M. E. (2005). Students’ reaction to WebCT: Implications for designing online learning
environments. International Journal of Instructional Media, 32(4), 353-362.
Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS
success model: An examination of IS success at the individual level.

Information &Management, 46(3), 159-166.
Price, L., & Kirkwood, A. (2013). Using technology for teaching and learning in higher
education: A critical review of the role of evidence in informing practice. Higher Education
Research and Development (in press).
Sitzmann, T. M., Kraiger, K., Stewart, D. W., & Wisher, R. A. (2006). The comparative
effectiveness of web-based and classroom instruction: A meta-analysis. Personnel
Psychology, 59, 623–664.
Smart, K. L., & Cappel, J. J. (2006). Students' perceptions of online learning: A comparative
study. Journal of Information Technology Education, 5(1), 201-219.

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  Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008) What drives a successful elearning? An empirical investigation of the critical factors influencing learner satisfaction.
Computers & Education, 50(4), 1183-1202.
Weiss, H. M. (2002). Deconstructing job satisfaction:

Separating evaluations, beliefs, andaffective experiences. Human Resource Management Review, 12, 173-194.

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Volume 2 - Issue 1 - Winter	
  Human Resource Management Strategies andTeacher’s Efficiency within Schools:
A Co-relational Study.
Kiran Hashmi

Acknowledgement
Dr. Margaret Madden RSM
Margaret.madden@acu.edu.au
Australian Catholic University
	
  

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  Abstract
The aim of the paper is to study Human Resource Management and Development (HRMD)
strategies and their effect on teachers’ efficiency within the Catholic Board of Education (CBE)schools of Pakistan whose teachers are graduates in educational leadership courses from a private
teacher education institutes in Karachi. The study endeavored to build a simple theoretical andconceptual framework where the effectiveness of HRMD strategies in educational leadershipwere studied to explore their impact on enhancing teachers’ efficiency. Leadership education is arelatively a new field of study in the Pakistani education and the concept of Human Resource
Management (HRM) is regarded as novel and its effective usage is rarely seen. HRM strategies
if effectively utilized may become a source of developing a transparent performance
management system, a collaborative and cooperative environment in the schools and of
promoting teachers’ efficiency in the areas of knowledge, values, skills and development as
professionals as well as enhancing a school’s productivity and improving its overall
performance.
A survey methodology was adopted for the current research with purposive sampling to select 50
research participants and a questionnaire was used for data collection using an attitudinal scale.
The results of the study revealed firstly that no relationship exists between the organization of theschool and the newly acquired knowledge and skills of HRM. The school leaders are unaware of
the various functions and strategies which are necessary to promote teachers’ efficiency.
Secondly, the study showed that some of the educational leaders are striving to meet theeducational requirements of the times and to face challenges while using the learnt strategies of
HRM to promote teachers’ efficiency for the improvement of their particular schools.
Keywords: Human Resource Management and Development; teachers’ efficiency; Pakistan.

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  Introduction
Pakistan’s most recent Education Policy, (Ministry of Education [MoE] 2009) identified two gaps
as the fundamental causes of the weak performance of its education sector. The first was named
as the commitment gap, highlighting the lack of commitment to making education of goodquality and accessible to all children. The second gap concerned the lack of implementation
which has disaffected the implementation of policies with their relevant and updated educational
practices. The two gaps are linked, as such ‘a lack of commitment leads to poor implementation’
while ‘weak implementation leads to problems’ (p.14) that can be traced to a lack of commitment
and competence at governance and leadership levels (p.22).
The professional standards and expertise exercised by the Pakistani policy makers in the Nationaland Provincial Ministries of Education as well as the principals and middle managers in theschools are fundamental to bridging the implementation gaps. Yet these pivotal educators are
unprepared. While countries across the world place emphasis on educating school leaders and theestablishment of academies for school leadership, in contrast, almost no persons in management
positions in Pakistan’s education sector have skills training in the function of educational
leadership and are appointed to positions with little management experience (MoE 2009, p.28).
In 2008 the minorities’ system of Catholic Education through its Board of Management for the
Programme Office for Education (POE) took steps to address the dire need for quality leadershipat both its system and individual school levels as a means to ensuring the long-term benefits of its
programmes. Notre Dame Institute of Education (NDIE) was commissioned by the POE todesign and implement an intervention to include the components of educational policy
development and planning; curriculum development and implementation; and effective
management structures and strategies. The Institute took the position that short term leadershipin-service programmes would be neither effective nor efficient for long-term outcomes. With the
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  support of Australian Catholic University’s (ACU) School of Educational Leadership three longterm systematic Award courses were designed and encultured for the Pakistani context.
To fill in the desired gap, in 2010 NDIE piloted a two year programme of educational leadershipoffering the (ACU Awards of Graduate Certificate (GradCert), Post- Graduate Certificate(PGCert) and Masters in Educational Leadership (MEdLead). An outcome of the implementation
process was the development of the type of curriculum and instruction which aimed to create anenvironment of self-directed learning and decision making in committed and professionallyqualified educational leaders who in turn contribute to the creation of a national educational
environment where both equity and diversity are honored (Mission Statement of NDIE 1991;
2009).
Leadership in and for education and its development is a relatively new field of study in Pakistan
as are the components of its curriculum. Human Resource Management and Development(HRMD) was included as a unit of study in the NDIE Masters course to help develop the skills ofpractical and strategic management of the personnel within a school. HRMD studies, while
originating in the field of business studies, are equally relevant and critical for the effective
management of educational institutes.
HRMD is considered as an important field of study for professionals in the corporate as well as in
the education context. Such studies equip the leadership and management of different
organization to deal with the human resources within an organization in multiple ways while
utilizing its strategies to reach their goals (Akbar 2009; Guttel 2010; Bibi, Lanrong & Haseeb
2012; Wisdom & Ebimobowei 2013). Many studies have been conducted and provided valuable
insights on HRMD in the corporate sector in the recent years; while neglect of such studies isevident in the paucity of utilization of effective HRMD in the education sector (Akbar 2009).
Erdamar (2013) pointed out that the knowledge, awareness and application of HRMD is integral
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Volume 2 - Issue 1 - Winter	  to the effective functioning of education leaders as it helps to provide a foundation for the growthand promotion of education systems. Skilled and professionally qualified leaders in HRMD are
considered to perform better for the development of the organization than the unqualified andunskilled ones (Iqbal, Arif & Abbas 2011). Furthermore, Hoffman and Shrew (2013) laid stresson the fact that the leaders’ knowledge and skills of HRMD help in promoting the efficiency andefficacy of the staff leads to the development of their organization at large. The concept ofutilizing HRMD in the corporate sector to achieve the desired goals has almost the same
implication in the education sector. Leaders are required to be acquainted with the skills neededfor effective leadership and management for the development of their institutions and thewellbeing of the human resource employed.
Considering the importance of HRMD and its practical implications for the effective performanceof leaders in schools, the recent study involved participants from various geographical areas ofPakistan enrolled in the pilot NDIE-MEdLead course. The study’s intent was to spotlight andinvestigate specifically selected strategies such as compensation, job description, training,
performance appraisal, employee participation, leadership and team work in HRMD used by theunit participants as leaders in their local school settings in order to promote the teachers’
efficiency. The study also aimed to be an evaluative tool for the researcher in identifying the corelation between the content and learning-teaching strategies employed in teaching the HRMD
unit of study and the participants’ abilities to make relevant application in their work settings.
From an analysis of this data, the research will gain practical insights for redesigning the study
unit with a focus on ensuring the MEdLead students will gain better professional skills ofmanaging HRMD having a balance of knowledge, understanding, creative and critical thinking
within their personal and interpersonal capacities. Pakistan based research into the effects ofconscious use of (HRMD strategies in the schools to promote teachers’ efficiency is minimal andthis fact urged the researcher to undertake the study.
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  Objectives of the Study
The objective of the study was to investigate how far applied HRMD strategies such ascompensation, collaboration, team work, payments and rewards, professional development,
employee management and performance appraisal have been effectively utilized in selected CBEschools across Pakistan and the impact these strategies have on teachers’ efficiency. Efficiency ofstaff in an educational environment is not a tangible phenomenon which can be easily measured,as efficiency accounts for multiple psychological and social traits and little consensus has beenreached in terms of its definition, attributes and construct as described by Hoffman and Shaw(2013, p.1). However, the research provided a critical attempt to check the applicability of
HRMD strategies in the CBE schools which employ the NDIE MEdLead students.
Research Question
The problem to be probed through this research was the effect of HRMD strategies used byeducational leaders professionally qualified from NDIE in the unit of Human Resource
Management and Development (EDLE 679) offered under the ACU EdLead Award in promoting
teachers’ efficiency to improve the standard of the CBE schools.
The research problem of this paper is presented in the following question:
What effect does the use of Human Resource Management and Development (HRMD)
strategies by school leaders have on the efficiency of teachers in Catholic Board Schools
in Pakistan?
The study adopted the following hypothesis:
There exists a positive relationship between the Human Resource Management andDevelopment (HRMD) strategies used by school leaders on the efficiency of teachers in
the Catholic Board Schools in Pakistan.
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  µHRMDS ≠ µTE
Purpose of the Study
The purpose of the study was to investigate the links between what was learned in a unit of studyof HRMD and the participants’ implementation of that specific learning in their workplaces. The
study considered the recently established link between the participants’ actions with identifiable
and measurable efficiency criteria among teachers of the respective CBE schools, focusing on theefficiency criteria that were not present in the teachers prior to the interventions made by the unit
participants. Furthermore, an attempt was made to find a measure of the improvement which theunit participants made in managing their staff more effectively through using a variety ofstrategies to develop and promote efficiency in them.
An anticipated outcome from the study is the assistance it will provide selected educational
leaders to improve their practices of management and leadership for a sustained and accelerated
outcome of their school. This study’s importance for NDIE is the insights it will offer towards
improving the set curricula for better applied outcomes most particularly as the EdLead
programme is at the completion of its two year pilot phase. Through this study it is anticipatedthat NDIE will be able to evaluate classroom based efficiency and effectiveness of its educational
leadership graduates working within the CBE school system across Pakistan
Study Organization
Following the introduction, the study presents the theoretical linkages between HRMD strategies
and teachers’ efficiency within schools. Section three provides a review of selected empiricalstudies on human resource strategies with the conceptual framework developed. The model ofregression analysis is used to analyze data, the details of which are discussed in section four
while the fifth section assesses the HRMD strategies utilized by the unit participants and
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  discusses the extent of the impact they create on teachers’ efficiency in the selected CBE schools
in Pakistan. The final section sets the directions for further measures and concludes the study.
Review of Literature
Theoretical Framework
Researchers such as Simatwa 2013; Kelly & Odden 2008; Wang, Chich-Jeng & Mei-Ling 2010;
Jane, Mattew & Bedi 2010; Raccah 2012 suggests that the study of HRMD implies a
combination of theories dealing with the social, psychological and economic dimensions of theleadership and employees. Theories of motivation, behaviorism and humanism form the
proposition of theories used in this particular study as it investigates human resources within an
organization. A critical analysis of these foundation theories leads to the development of threedifferent perspectives of HRMD, namely the behavioral, normative and economic perspectives
that can enhance employees’ efficiency in an organization. The behavioral perspective highlights
the analysis of employees’ actions to identify behavior patterns that separate an effective
employee from a non-performing employee, hence provide support to the leadership in managing
them. The normative perspective of HRMD links workforce management to organizational
strategy. HRMD stresses the linkage of functional areas such as manpower planning, job analysis,
recruitment, compensation and benefits, performance evaluations, contract negotiations and labor
legislations to corporate strategy. This link enforces the organization’s interests over theemployees' conflicting ambitions and interests. It views the workforce as passive resources thatthe organization can use and dispose of at will. On the other hand, the economic perspective
holds the view that the strong natural inclination of people working in groups is to reduce theirperformance and rely on the efforts of others in the group. When one person delegates
responsibility to another person, conflicts of interests invariably arise. The major role of humanresource management in such a context is to promote alternative ways of controlling behavior to
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  reduce the effects of such conflicts and minimize the cost to the organization. This includes thetwo approaches of monitoring and incentive giving (Act of Managing Institutes, UK, 2009).
HRMD is arguably one of the challenging units of study in the field of business and has
influenced the education sector in Western countries over the past 30 years (Nakpodia 2010).
Recently it has stepped into the education sector of Pakistan (MoE 2009). While HRMD can be
defined as the utilization of individuals to achieve organizational goals, effective HRMD isrequired in organizations to get things done (Koc 2010). Individuals dealing with HRMD mattersface a multitude of challenges, ranging from a changing work force to government regulations,
technological revolution and the recent global competition. Those engaged in its management
must develop and work through an integrated HRMD system comprising such functions as
staffing, human resource development, compensation and safety and employee labor relations(Mondy2009). Badri and Mourad (2012) stated that HRMD strategies enhance productivity andthe effectiveness of the organization. When the leaders within organizations employ such
personal practices as internal career ladders, formal training systems, result-oriented performanceappraisal, employment security, employee voice and participation, broadly defined jobs andperformance based compensation; they are more able to achieve their targets. The effective
application of HRMD strategies by the educational leaders is likely to attain the desired outcomesof the institution.
Dessler and Varkkey (2011) highlighted the importance of HRMD for any organization to workand prosper. They hold that the paradigm shift in HRMD from the corporate sector to theeducation sector is a result of rapid globalization in the field of knowledge and education,
increased competition in the education market, reduced financial budgets for the education sector
and changing economic downturn. The economic blow from the West has affected the East as

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Volume 2 - Issue 1 - Winter	  well and therefore the education sector of Pakistan has incorporated HRMD in the studies ofleadership at least in theory, in order to manage its human resources more effectively.
As research in the field evolved, scholars presented many different viewpoints on HRMD
strategies. The theory of planned behavior by Azjen (2011) emphasized the viewpoint that
HRMD managers tend to guide the human behavior of employees based on three beliefs, namely
a belief about the likely consequence; a belief of the normative expectations of others; and beliefs
about the presence of factors that may facilitate or impede the performance of the planned ordesired behavior. In HRMD managers’ respective aggregates, behavioral beliefs produce afavorable or unfavorable attitude toward the behavior; normative beliefs result in perceived socialpressure; and control beliefs give rise to perceived behavioral control. In combination, attitude
toward the behavior, the subjective norm and the perception of behavioral control lead to theformation of a behavioral intention.
Following theory of Azjen, McClelland (2008) claimed that effective HRMD revolves aroundthree major categories: achievement, affiliation and power. In an educational organization, theleaders use effective HRMD to build a framework where employees with different needs are
motivated differently. To manage the employees suitably, high achievers in the organization
should be given challenging projects with reachable goals and be provided frequent feedback. It
is expected that the employees with a high affiliation need, perform best in a cooperativeenvironment, hence HRMD managers strive to develop a collaborative environment in theirrespective organizations. Furthermore, the potential leaders within the educational organization
should be picked and assigned with tasks and opportunities to manage others. In this way aneffective system of management would be developed and the process of goal seeking would bemade relatively easy (Mabin 2007). HRMD mainly works to promote the productivity,

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  performance and efficiency of the staff for the achievement of organizational objectives andprogress.
Conceptual Framework
The conceptual framework of this study has been designed while keeping the determinants of the
independent and dependent variables in consideration. The independent variable was the selected
HRMD strategies (team work, performance appraisal, employee participation, job description,compensation and leadership), whereas, the dependent variable was teachers’ efficiency
accounting for the determinants of competency, compensation, work environment, job
satisfaction and professional development.
If HRMD strategies such as compensation, pay, reward, benefits and policies withinorganisations are well thought out beforehand and applied effectively, it helps in the promotion
and development of the commitment and performance of the employees. Self-directed and selfcommitted employees are considered an asset to an organization as such attributes among
employees foster the productivity of the organization at large and help in sustaining it for a longer
period. The applied HRMD strategies in the organization help in creating a meaningful way tomeet the outcomes utilizing the physiological, psychological and social variables related to
employee development (Erdamar 2011). Furthermore, that the efficiency of teachers/ employees
can be enhanced if the educational leaders know which HRMD strategy is appropriate to be used
at which time (Badri and Mourad 2011). To Koc (2011), the overall performance of the school
depends on both the leadership and the employees as they need to operate in harmony whileconsidering the qualitative and quantitative aspects of the operation of educational institutions. If
HRMD strategies are applied in an effective manner, it is predicted that they develop a twofold
environment where one outcome is to achieve the set targets by promoting the performance,
productivity, efficiency, innovations reliability and security of the employees. The second
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  outcome concentrates on the wellbeing of the employees in terms of health and safety,
satisfaction, pleasure, learning and personal development which enhances the morale, efficacy
and efficiency of the employees through a system design.
HRMD strategies are a set of inner-organizational personal management strategies (Wang,
Chich-jen, & Mei-ling 2010). The effective application of the HRMD strategies in different
situations can help organizations use employees effectively for the completion of organizationaltargets. However, classifications of the HRMD strategies made by various scholars differ fromeach other. For example, the inducement strategy, the investment strategy and the participation
strategy are presented by Dyer (1988), while Schuler (1989) addresses accumulation, utilizationand facilitation. The development strategy, the motivational strategy, the reinforcement strategy
and the transfer strategy as presented by Huang (1998) were taken as the dimensions of the
HRMD strategies for the purposes of this research.
HRMD practices in organizations depend largely on relative powers of organizational actors topush innovation to enhance productivity. The nature of the relationship of the HRMD department
with the different levels of management and employees develops a strategic plan that assists inthe attainment of the set organizational goals (Jain, Mathew, & Bedi 2012). Agarwala (2003)
examined the relationship between organizational commitment and the dimensions associatedwith HRMD practices, the extent of their introduction, their importance for goal achievement andthe satisfaction with their implementation. He further found that among all dimensions, theintroduction of such practices explained the maximum amount of variance in organizational
commitment and thus were most effective in enhancing employee attachment to the organization.
Agarwala’s research indicated that HRMD practices such as innovative and an open work
environment, opportunities for career development, development-oriented appraisal system and

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  comprehensive and customized training programs were positively linked with organizational
commitment.
Methodology
The researcher adopted a survey methodology because of its strength in investigating the effect of
the HRMD strategies used by the EdLead unit participants of NDIE to effect teachers’ efficiency
within the Catholic Board schools of Pakistan.
Target Population
The accessible population for this research was GradCert, PGCert and MEdLead students of
NDIE who undertook their courses in educational leadership between 2010 and 2012. From thetotal accessible population, a sample of 50 participants was selected comprising of a total of 9
males and 41 females.
Sampling Technique
The purposive sampling technique was used in collecting data from the research participants as
the focus of the research was to analyze the effect of HRMD strategies promoting teachers’
efficiency by NDIE Edlead Graduates. The total research population was 76 out of which 9
expressed their non-availability to participate in the research activity; 11 had not completed the
EdLead program; and 6 participants were not employed by the CBE. Therefore the researcher
had available a total population of 50 participants who agreed to take part in the research activity
and filled in the required questionnaire. All 50 research participants received a copy of thequestionnaire which was the main data gathering tool and 44 returned the questionnaires
completed according to the given instructions.
responses.
Instrument Development
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Volume 2 - Issue 1 - Winter	  The questionnaire used for data collection was divided into two sections.

Section A wasdesigned to acquire demographic information from the research participants in response to themost suitable variables while sections B was based on attitudinal scales. The two main types ofattitudinal scales, namely Likert scale and rating scale, were used in developing the datacollecting instrument.
Instrument Reliability
The value of Cronbach’s Alpha calculated for data collected from the EdLead Unit participants of
NDIE from all across Pakistan in relation to the overall reliability of the instrument wascalculated to be 0.922 indexes, which shows high reliability value.
Table 1
Reliability Statistics
Cronbach's Alpha

N of Items

.922

15

Regression Model
For this study the Linear Regression Model (LRM) was used. The regression analysis focused onseven types of human resource management strategies which were training, performanceappraisals, team work, employee participation, job description, compensation and leadership
constituting together as the independent variable. The teacher efficiency variable consisted ofknowledge, professional development, values and skills, and collaboration as indicators ofdependent variable.
To examine the effectiveness of HRMD strategies on teachers’ efficiency, the following
empirical equation of the linear regression model was developed:
β0HRMD= +β1Kn +β2 Pd+β3Vs+β4 C
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  Where HRMD are the Human Resource Management strategies, KN is the knowledge of theteachers, PD is the professional development, VS are the required values and skills of theteacher and C is teachers’ collaboration.
Data, Estimation Results and Findings
The estimation of the results is stated below:
Frequency Distribution
Figure 1

Descriptive Statistics Analysis
Table 2
Descriptive Statistics

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N

MinimuMaximu

m

m

Std.
Mean

Deviation

Skewness
Std.

Statistic Statistic

Statistic

Statistic Statistic

Statistic Error

HRMDS

44

71

40.98

.535

Valid

N 44

22

10.909.357(listwise)
The descriptive statistics above display the values of the measures of central tendency. The
statistics exhibit that the HRMD strategies used at schools by leaders have a critical value lessthan 5 percent equivalent to 0.05 which indicates that the data is normally distributed. Moreover,the histogram presented above presents the same distribution of data.
The descriptive statistics reported in Table1 illustrate that the HRMD strategies used in the CBEschools are not according to the strategies applied in the other the educational institutes as
described by literature. A possible reason for this result is that HRMD is a newer field ofexperience for the educational leaders of the CBE schools. A second possible reason is thatteaching the unit through a mixed mode approach did not give a sufficient and holistic
understanding of the application of the strategies, hence the educational leaders are notsufficiently aware of the effective use of the strategies. Furthermore, the results of the descriptive
statistics shows that as the practicing and potential leaders are currently in the state of gaining
professional qualifications, important aspects of increasing and improving teachers’ efficiency
within their schools are not skillfully utilized. The results also show the trend that current
practices HRM by the educational leaders at CBE schools are not effective to an extent where it
improves teachers’ efficiency. The human resource management and development strategies were
not effectively utilized by the educational leaders due to loosing leaders, within-system sorting,lack of finances for professional development and unqualified leadership (CBE Rule Book, 2006,

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Volume 2 - Issue 1 - Winter	  p.26). The value of the standard deviation is high which shows that the dispersion of the datafrom the midpoint and the critical value are at almost half of the mean for most of the variables.
Regression Analysis
The following section presents the result of the regression analysis undertaken using the above
mentioned equation.
Table 3
Model

UnstandardizedStandardized

Coefficients

Coefficients

B

Std. Error

1(Constant)

41.2797.591

Knowledge

-.168

4.125

2(Constant)

36.862

8.834

Knowledge

-.611

4.152

Professional development 1.182

1.208

3(Constant)

50.46510.873Knowledge-1.813

4.049

Professional development .912
Values and Skills

t

Sig.

5.438

.000

-.041

.968

4.173

.000

-.023

-.147

.884

.152

.979

.333

4.641

.000

-.068

-.448

.657

1.173

.117

.778

.441

-4.065

2.018

-.306

-2.015.051

4(Constant)

52.677

11.448

4.601

.000

Knowledge

-.892

4.309

-.033

-.207

.837

Professional development .546

1.304

.070

.418

.678

Values and Skills-3.637

2.133

-.274

-1.705.096

Collaboration-1.102

1.664

-.118

-.662

.512

a. Dependent Variable: Teachers’ Efficiency

Regression Findings

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Beta

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  In order to see the effect of HRMD adopted by the EDLE 679 unit participants from NDIE toenhance their teachers’ efficiency within schools, a linear regression analysis was done. The
estimated growth equation displayed that in the regression model run with four independent
variables, the model with collaboration showed a strong negative correlation. The rest of thevariables, such as knowledge of the staff, their professional development and inculcation ofvalues and skills had no effect on teachers’ efficiency in their respective CBE schools.
The β value of the dependent variable (HRM strategies) shows that there exists a negative sign inthe relationship. This accounts for multiple interpretations and inferences. Although theeducational leaders were professionally qualified having degrees of Bachelors in Education (BEd)and Masters in Education (Med), still there is question on the quality of the implementation of thelearnt skills in the professional education programmes. In the Med programme, althoughleadership and HRM are taught, its practical implication is not according to what is expected by
the educational leaders. Secondly, it has been interpreted that as leadership education andparticularly HRMD is a newer field in the education system in Pakistan, the educational leaders
were not aware of the effective application of a HRMD system and hence did not apply it
effectively. Another possibility could be the fact as HRMD is considered more of a concern ofthe corporate sectors therefore its effective utilization and implication in the education sector
particularly in the schools system is rarely to be seen. This study was conducted amongst
participants who had recently completed the unit EDLE 679 and perhaps the study had notallowed sufficient time for the participants to introduce and implement HRMD strategies into
their local schools. Such changes do take time if they are to be effectively implemented. If thisstudy is conducted again after 3 years, then there is a probability that the results would be
different and more in line with what other researchers have documented.

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Volume 2 - Issue 1 - Winter	  As the regression result indicated a high degree of negative correlation between the two variables,
it made little sense for the researcher to focus on the underlying possible internal and external
factors which might have created an imbalance in the relationship between the two.

The

regression results have opened many avenues for improvement amongst the educational leadersof the CBE schools in particular. It is assumed that if educational leaders clearly define the job
descriptions of their teachers and provide room for professional development, it is likely todevelop a positive relationship between the selected variables of teachers’ efficiency anddeterminants of the human resource management and development strategies. It is also
recommended that if teachers are encouraged to contribute in quality enhancement of the
managerial and academic processes at school, they would feel more empowered and thelikelihood of a positive correlation will also occur. If a properly developed and managed staff
performance management system is in place, it is expected that its measures will assist inenhancing teachers’ efficiency within schools in the expected areas of concern. If teachers areprovided performance based feedback and counseling, they will develop faith in the transparencyof the performance appraisal system which in turn will enhance their efficiency at school. It isalso expected that if teachers in the school are allowed to make decisions related to budget,functions and events, it will enhance their efficiency as well. Professional development
programmes if conducted at intervals throughout the year for human resource personnel in eachjob specification, it will assist in enhancing teachers’ efficiency. Through formal induction,orientation and training programmes new inductees will learn the required skills to perform theirjobs in schools more efficiently. It is also expected that if teachers are provided opportunity tosuggest improvements in the way things are done in the school, new knowledge and skills will be
periodically imparted to the teachers which will help in enhancing their efficiency.
The findings of this study differ from the insights contained in the literature reviewed to support
the study. The reviewed literature showed a positive relationships described by Akbar 2009;
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  Guttel 2010; Bibi, Lanrong & Haseeb 2012; Wisdom & Ebimobowei 2013 whereas in this study
the Durban-Watson test showed a negative correlation. Therefore, the research hypothesis isrejected as the research found a negative correlation between HRM strategies and teachers’
efficiency in the selected CBE schools of Pakistan.
Direction for Future Research
Overall the regression model is significant. However, the adjusted R2 value and Durbin-Watson
value do not show the complete causal-effect relationship between the effect of HRMD strategies
and teachers efficiency in the CBE schools of Pakistan. Therefore, further in-depth analysis isrequired in order to bring more authentic results.
Conclusions and Implications
In this paper the effect of HRMD strategies on teachers’ efficiency within selected CBE schools
was studied. A simple theoretical framework was built where the effects of HRMD strategies
were contrasted with teachers’ efficiency. Leadership and HRMD theories were taken into
account and a theoretical framework was constructed. Moreover to further support the theoreticalframework, a conceptual framework of the selected dependent and independent variables was
also constructed to comprehend the research study. The result of the correlation test showed anegative correlation between the variables. The general lesson that emerges from this study is thatthe practical implication of the learnt theories is important in the current leadership scenario.
Although CBE schools have shown their commitment, contribution, service and dedication in the
improvement of the education sector, they now need to shift their attention towards teachers’
growth and development by focusing more on the application of HRMD strategies. If CBE’s
HRMD department takes an account of the effectiveness of the strategies in the registered schools,
the desired outcomes can possibly be achieved.
References
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  Achua, F. C., & Lussier, R. N. (2007), Leadership: Theory, application and skill development,
3rd edition, Cengage Learning, Canada.
Afza, T., & Nazir, M. S. (2007), Economic Competitiveness And Human Resource Development :An FDI Perspective, Pakistan Economic and Social Review, 45(2), 167-180.
Ali, A. (2009). The Role of Leadership in Human Resource Management a Comparative Study ofSpecific Public and Private Sectors in Pakistan, Journal of Management and Social Sciences,5(2), 180-194.
Aloo, J. O., Simatwa, E. M. W., & Nyang, R. A. (2011), Impact of the School Based Teacher
Recruitment Policy on the Distribution and Retention of Teachers in Public Secondary
Schools in Kenya, A case study of Nyando District, 2(March), 1006–1020.
Armstrong, M. (2011), Strategic Human Resource Management: A guide to action, Kogan page,
New Delhi.
Budhwar, P. S., & Sparrow, P. R. (2002), Strategic HUMAN RESOURCE MANAGEMENT
Human Resource Management through the Cultural Looking Glass  , Mapping the Cognitionof British and Indian Managers, 599–639.
DeCenzo, D. A., Robbins, S. P. (2010), Human Resource Management 10th Edition. Balaji
Enterprise, New Delhi.
Dessler, G., & Varkkey, B. (2011), Human Resource Management, 12th edition. Dorling
Kindersley, New Delhi.
Franekel, J. R., Wallen, N. E., & Yuhan (2012), How to design and evaluate research ineducation, 6th edition, McGraw Hills Publication, New York.

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  Jain, H., Mathew, M., & Bedi, A. (2010), The International Journal of Human HUMANRESOURCE MANAGEMENT innovations by Indian and foreign MNCs operating in India  :a survey of HUMAN RESOURCE MANAGEMENT professionals, (March 2013), 37–41.
Johnson, L., & Shields, J. (2007), Lessons from management–union partnership in teacher
performance appraisal in the New South Wales public education system, International
Journal of Human Resource Management, 18(7), 1214-1227.
Koç, G. E. (2011), An investigation of student teachers' study strategies with respect to certain
variables, Educational Research and Evaluation: An International Journal on Theory andPractice, 17(2), 69-83.
Mondy, R. W. (2010), Human Resource Management, 10th edition. Prentice Hall New Delhi.
Ministry of Education (2009), National Education Policy, Government of Pakistan, Islamabad.
Of, A. C., & Telecom, P. (2010), Impact of Human Resource Management (Human Resource
Management) practices on employees performance.
Pierce, J. L., & Newstorm, J. W. (2012), Leaders and the leadership process: Reading, selfassessments and application 6th edition, Mc Graw Hills Publication, New York.
Starratt, J. R. (2011), Refocusing school leadership: Foregrounding human development Human
Resource Management throughout the work of the school, Routledge, New York.
Tomlinson, H. (2004), Educational Leadership: Personal growth for professional development,
Sage Publication, London.
Wang, F., Chich-jen, S., & Mei-ling, T. (2010), Effect of leadership style on organizational
performance as viewed from Human Resource Management strategy, African Journal ofBusiness Management, 4(18), 3924–3936.
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  Wichenje, K. M., Simatwa, E. M. W., Okuom, H. A., & Kegode, E. A. (2012), Human Resource
Management  : challenges for head teachers in Public Secondary Schools in Kenya , a casestudy of Kakamega East District, Educational Research, 3(2), 159–171.

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“I prefer to think for myself”:
Upper Secondary School Pupils’ Attitudes towards
Computer-based Spanish Grammar Exercises.
Kent Fredholm

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Volume 2 - Issue 1 - Winter	
  Abstract

There is an increasing pressure from school leaders in many countries for teaching to be based
solely on ICT tools. The present study is interested in what this does to pupils’ attitudes towards
ICT in language classrooms. Is a digital monopoly a good way for pupils to learn languages? Is it
what they want?
To understand for which tasks students feel that computers are an appropriate tool, a qualitative
survey mapping upper secondary school pupils’ attitudes towards the ICT use for learning
Spanish has been conducted. The study looks at ICT use for grammar practice. A group of pupils
have completed lesson diaries, reflecting upon web-based grammar exercises, comparing them topaper-based exercises, and a questionnaire survey on general attitudes towards ICT in language
learning.
The results indicate that the majority of participating pupils ask for a greater variety of tasks andsee a need also for traditional forms of grammar practice, especially written exercises which givetime to reflect upon grammar, syntax and vocabulary. They want ICT use to be an option, not a
constraint. Many complain on flaws in the design of web-based grammar exercises. This shows aneed for more research into the effects of different designs of web-based tools. It also becomes
clearer that decision-makers and teachers must focus more on the pedagogical purpose oflearning tasks and that the first question to ask is: “How can I teach this in a way that suits mypupils?” rather than: “How can I add more ICT to my teaching?”.

Keywords: ICT; CALL; Foreign language learning; Pupils’ attitudes; Grammar learning.

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Volume 2 - Issue 1 - Winter	
  Introduction and background
I am one of many teachers witnessing the Information and Communications Technology (ICT)revolution reaching our schools, as an ambitious 1:1-laptop programme is being implemented in
the public upper secondary school where I teach. When private schools started offering freelaptops, it was seen as a way to attract pupils from public schools (Lund, 2006, 2007; Odlander,2007). The current 1:1-implementation is motivated otherwise: we need to prepare today’s youth
for tomorrow’s future, increase entrepreneurial thinking and find new teaching methods toenhance pupils’ learning (examples from discussions among local school authorities).
Educational challenges like these are seemingly all to be solved by giving computers to the pupils.
As is often the case, much thinking and dreaming goes on before the computers arrive, but fewer
efforts are done after that to make something out of the technology (cf. Svärdhagen et al., 2011).
A worrying tendency, locally but also reported in international reports (e.g. Zucker et al., 2005),
is the wish to use ICT to save money on other teaching material.
Many researchers and opinion-makers seem fairly agreed on the need to use ICT in school. Cobo
Romaní & Moravec (2011) discuss how Drucker’s (1959) vision of the “knowledge worker” hasrealised itself and that pupils need to know how to handle the new technique, an opinion
expressed also in Motteram (2011). Cobo Romaní and Moravec observe, nevertheless, that thisdoes not necessarily mean that ICT is always the best method. The voices heard on ICT in school
are, however, mostly focusing on the need of getting more teachers to use ICT, rather than
discussing when, how or why (from a pedagogical point of view) ICT should be used.
Computers are often thought to automatically motivate pupils (Zucker et al., 2005; Ware et al.,2006; Kahraman et al., 2011; Edmunds et al., 2012; AlAmmary, 2012; Tallvid et al., 2009).
According to Usta (2011), however, neither traditional nor web-based teaching methods influenceon pupils’ attitudes towards computers or the Internet; considering this, the methods per se would
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Volume 2 - Issue 1 - Winter	  not automatically constitute a motivating (or demotivating) factor; what is needed is rather awell-planned and varied teaching adapted to student needs and preferences. There are indications
that pupils grow weary of computers as the charm of the novelty wears off (Wiebe et al., 2010;
Lim et al., 2006; Warschauer, 1996; Chiu et al., 2013). Few seem to bother, though, to ask pupils
what they perceive as instructive methods.
As Svensson (2008) and others (e.g. Enkvist, 2002, 2011; Roszak, 1994) point out, there issometimes an “almost regularly occurring overconfidence in new media” (Svensson, 2008, p. 145,
my translation). This overconfidence may be forcing ICT-based teaching methods prematurely onteachers and students, thus neglecting other ways of teaching and learning, as well as impeding awell thought-out use of ICT tools in classroom practice. Ware et al. (2006) stress
that, ”Justification for the new uses of technology must be based, not on unmitigated, unrealistic
optimism, or on uninformed, a priori rejection, but on empirical data matched to particular uses in
specific contexts.” (p. 4). Chapelle (2011) also says that it is difficult to conclude what are theeffects of ICT use in language instruction, and Buskqvist et al. (2011) write that it is “problematicthat implementations of ICT-based forms or elements of instruction are based neither onscientific evidence nor are followed up by scientific studies” (pp. 68 – 69; my translation). In
New Millennium Learners, the OECD admits the “intrinsic difficulty when researching the effects
of technology on educational performance”, and mentions “inconclusive results” (OECD, 2008, p.
7; cf. Rosén, 2012), a view shared by Chapelle (2011). According to Nutta (1998), ICT-based
grammar instruction can be as effective or more so than traditional one, while Lim et al. (2006),
on the other hand, have found that CALL does not necessarily give better results than traditional
instruction. Kroksmark (2006) suggests that pupils might prefer traditional teaching. Interestingly,
Wiebe & Kabata, (2010) have found in several studies that teachers perceive ICT use as more
useful than many pupils do, and Svärdhagen et al. (2011) point out that school leaders, in their

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  turn, put more faith in it than teachers do. It may be time to find out more about what the pupils
who use the technology actually think of it.
Aim of the present study
A better understanding of pupils’ views on purposeful and instructive ICT use in language
learning could help us construct better programs and software, and make us understand whatneeds to be studied more (Larsson, 1986). To be able to perform research on how ICT use
changes learning outcomes, we first need to gain a better understanding of what pupils do with
their computers in school, and what their feelings towards these study methods are (cf. Wiebe etal., 2010).
According to Ayres (2010), ICT is particularly useful for practicing spelling, writing andgrammar skills, but less motivating in other cases. The present study is particularly interested insituations where ICT can be perceived of as obstructing or disrupting the learning, or simply not
functioning well, from the pupils’ point of view. This is less studied than ICT as a motivating
factor; cf., though, Granath et al. (2008) and Andersson (2010), among others.
The aim of the present study is, thus, to investigate attitudes among Swedish upper secondary
school pupils towards ICT use for Spanish grammar learning. In order to clarify these opinions,computer-based learning methods are compared to “paper-based” methods. This can hopefully
contribute to a better understanding of learning processes in 1:1 language classrooms and of
pupils’ views on appropriate ICT use for language learning.
The main research questions are:• When do pupils see computers as an appropriate tool for learning Spanish grammar?
• When do they not see them as appropriate?
• What didactic and scientific implications can be drawn from these results?
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Volume 2 - Issue 1 - Winter	
  Methods
Data were collected at three occasions during the autumn of 2012, using two lesson diaries and aquestionnaire. In both diaries, the pupils evaluated and reflected on the teaching methods andgrammar exercises they had worked with. The questionnaire, designed according to guidelines inDörnyei (2010, chap. 2), focused on general attitudes towards computer-based and paper-based
grammar learning. The study shows the pupils’ thoughts over a few months, thus reducing theissue of attitudinal changes over time (cf. Dörnyei and Ushioda, 2011).
The diaries and the questionnaire were distributed through a course management system (CMS)1
used at the school and chosen for practical reasons, being already there, ready to be used andknown to the pupils.
For the lesson work preceding the lesson diaries, online exercises were chosen to reflect types of
exercises easily accessible on the internet and regularly used at the school of current interest.2
The exercises consist of fill-in-the-blanks, matching, verb conjugations exercises and similar
activities, which, according to Tomlinson (2011), still make up the major part of self-accessonline material for language practice. The paper-based exercises were produced by teachers or
taken from a Spanish textbook (Vanäs Hedberg et al., 2008), and other commercially available
material such as Grönwald (1999a, 1999b). The main difference between the exercises was thatthe paper-based ones also contained sentences to translate to and from Spanish, which will befurther commented on later.
The analysis of the lesson diaries and the questionnaire follows a theme-based qualitative content
analysis, inspired by phenomenographic methods such as described by Larsson (1986).
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
1

See www.itslearning.com. “Courseware”, “virtual learning environment”, “learning management system” are otherterms for this kind of platform (Svensson, 2008; Cavus et al., 2010).
2
Established through personal experience and discussions during language teachers’ conferences. The online
exercises were mainly from http://cvc.cervantes.es/ensenanza/actividades_ave/aveteca.htm and http://www.vertaal.com/.

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  Participants
Twenty-six pupils in a group of twenty-seven, age 17, gave their informed consent to be part ofthe study. The average answer rate was 89%. There were 6 boys and 21 girls, reflecting theuneven distribution of Swedish language students at their level (Lannvik Duregård, 2010). The
participants being my own pupils, I have avoided to discuss views on learning methods or inother ways alter their opinions. A variety of teaching methods has been used, involving
computers as much as other modalities. It has also been clearly pointed out that the study has no
relation to grading or other forms of assessing their language skills.
The group was chosen for its mix of pupils from different study programmes: the Arts
Programme (henceforth “Arts”, 5 pupils); the Business Management and Economics Programme(“Economics”, 4 pupils); the Natural Science Programme (“Science”, 15 pupils); and theInternational TIME Programme3 (1 pupil). The TIME pupil’s answers are analysed with the
Science pupils’. It was their sixth year of Spanish studies and their Spanish proficiency
corresponded approximately to the B1 level of the CEFR scale (cf. Skolverket, 2013). They had
their own laptops, provided by their schools.
A note on terminology
Exercises, grammar explanations, etc. in books and on loose sheets of paper are referred to as“paper-based”, exercises etc. in digital form as “computer-based”. The term “online” is used for
explanations and exercises on the Internet. The term “ICT” (information and communication
technologies) is used for discussing not only computers but other digital technologies as well (cf.
Kern, 2006, p. 185).

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
3

This is a Natural Science programme specialising in “telecommunication, IT, media and interactive entertainment”(Karlstads kommun, 2012).

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Volume 2 - Issue 1 - Winter	
  Results and reflections
Results from Lesson diaries
The lesson diaries focused on pupils’ perceptions of grammar exercises on the Spanish futuretense and gerund constructions.4
According to Edmunds et al. (2012), using the “Technology Acceptance Model” developed by
Davis (1989), the perceived ease of use and the perceived usefulness influence on the user
acceptance of a technology. Bearing this in mind, the pupils were asked to grade the instructive
value of the computer-based exercises, on a Likert-scale from 1 to 5. Diagram 1 shows the mean
percentage from both diaries.

Diagram	  1	
  –	
  Perceived	
  instruc3ve	
  value	
  of	
  exercises	
  (group	
  level)	
  
70%	
  
61%	
  
60%	
  
49%	
  

50%	
  

Computer-­‐based	
  

40%	
  

32%	
  

Paper-­‐based	
  

30%	
  

24%	
  
16%	
  
11%	
  

20%	
  
11%	
  
10%	
  
0%	
  

2%	
  

0%	
  

1	
  

3%	
  
2	
  

3	
  

4	
  

5	
  

	
  

More pupils rated computer-based exercises than paper-based ones “5”, but on a whole they
preferred the paper-based exercises. Views differed more within the computer-based exercise
answers. The Science pupils were more negative to computer-based exercises than the otherpupils. It is unlikely that this is due to differing computer skills or experience, as most of thepupils considered their computer skills good (Diagram 3).
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
4

These areas were part of the participants’ on-going curriculum.

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Volume 2 - Issue 1 - Winter	  The computer-based exercises rated higher in the second diary than in the first. The mostcommon rating was still “3”, though, whereas the perceived instructive value of the paper-based
exercises continued to rate higher than the computer-based. The increase in popularity for the
online exercises can be explained by the fact that they were better structured than the exercises in
the first lesson diary. Pupil 8 (Science) commented that the instructions were easy and that her
opinion depended “on the quality of the web-sites”.
When asked which kind of exercise they generally prefer, (keeping instructive value in mind but
also considering other criteria such as being fun, user friendliness, etc.), the pupils answered as in
Diagram 2. (No Economics pupils answered this question.)

Diagram	  2	
  –	
  Preferences:	
  computer-­‐based	
  or	
  paper-­‐based	
  exercises	
  
45%	
  
40%	
  
35%	
  
30%	
  

23%	
  

Science

25%	
  

Arts

20%	
  

27%	
  

15%	
  
10%	
  

27%	
  
18%	
  

5%	
  

5%	
  

0%	
  
Paper-based

Combination/variation

Computer-based	
  There was a slight preference for paper-based exercises. Some of the motivations for this werethat the pupils felt that they learned better when they wrote by hand, that it was easier to focus on
the task and that they “sort of get the feeling in the hand” (pupil 16, Arts) when writing by hand.5
Every Arts pupil but one preferred paper-based exercises, and no one wanted only computerbased exercises. Only 6 out of 22 pupils (27%) preferred to use only the computer, none of them
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
5

Cf. Longcamp et al. (2008) and Velay et al. (2004a, 2004b), for neurocognitive studies where young and adultlearners recognised and remembered letters better when they had learned them by handwriting, compared to typing
on a computer.

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Volume 2 - Issue 1 - Winter	
  Arts pupils, while the remaining 73% preferred to work with paper-based exercises or with a
combination. This wish for combined teaching methods is in line with Motteram’s (2011) opinion
that web-resources do not cross out the use of text-books but can be a way to enhance them or
update their information. These results might also be compared with Wiebe et al. (2010), saying
that, “students chose their textbooks to be the most effective for materials in their course” (p. 226)
and Hegelheimer et al., (2006) writing that “learners often want to focus on form and wish for apedagogical tool to serve as a reference and an easy-to-use resource” (p. 259).
In the general comments on computer-based and paper-based exercises, only one pupil thoughtthat the paper-based exercises were “fun”; many appreciated them, however, seeing them as
instructive and presenting them with a good opportunity to review old knowledge and learn more.
Several pupils mentioned the instructive value of tasks involving translation of entire sentences,(something rarely seen in computer-based exercises), and asked for more of them. In a Swedish
school context, this is worth noticing, as the national curriculum for foreign languages does notinclude translation (Skolverket, 2013; cf. Council of Europe, 2001, chap. 2.1.3).
Several pupils stated that they learned more easily when working with pen and paper. Only threepupils believed that they learned more from online exercises then from paper-based, and somepointed out that a combination of methods is preferable. One pupil (5; Science) said that online
exercises facilitate revising grammar at home, but others thought that papers are easier to save forreviewing. The variation of working with both paper-based and computer-based exercises also
made it easier for her to work for longer without getting tired or bored. Another pupil (2; Science)commented that being able to choose from many different types of exercises makes it easier tocater for different learning styles. A few pupils preferred the online exercises because they did
not have to keep any papers, whereas others wanted papers as they felt that it was easier to gather
all the papers in one place and keep them for reviewing or studying for tests later.

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Volume 2 - Issue 1 - Winter	
  Results from the Questionnaire survey
The questionnaire focused on general attitudes towards the use of ICT, compared to paper-based
methods. Questions were also asked about general computer competence and confidence, andcomputer use in and outside of school.
Computer competence and general computer use
As indicated in Diagram 3, a majority of the pupils had high or very high confidence in their
computer competence. Most of them were frequent computer users at home and at school(Diagrams 4 and 5). Negative attitudes towards the use of ICT can apparently not be explainedwith lack of computer competence or experience, in this study.
Diagram	
  3	
  -­‐	
  Es3mated	
  computer	
  competence	
  
60%	
  
50%	
  

Science

40%	
  

Arts

30%	
  

Economics

20%	
  
10%	
  
0%	
  
1 - Very low
computercompetence

2

3

4

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Volume 2 - Issue 1 - Winter	
  Diagram	
  4	
  -­‐	
  Frequency	
  of	
  computer	
  use	  at	
  home	  for	
  school	
  purposes	
  
40%	
  
35%	
  
30%	
  
25%	
  

Science

20%	
  

Arts
Economics

15%	
  
10%	
  
5%	
  
0%	
  
Hardlyever

1 day/
week

2

3

4

5

6

7 days/week	
  Diagram	
  5	
  -­‐	
  Frequency	
  of	
  computer	
  use	
  during	
  lessons	
  (all	  subjects)	
  
45%	
  
40%	
  
35%	
  
30%	
  

Science

25%	
  

Arts

20%	
  

Economics

15%	
  
10%	
  
5%	
  
0%	
  
Hardly ever 1 day a week

2 days aweek

3 days aweek

4 days aweek

5 days a
week

	
  

The pupils used computers mostly in language lessons and social sciences. Pupil 21 (Economics)
commented that he hardly ever used the computer in any subject, except for oral presentations.
He preferred to use his smartphone, as it can perform everything he needs during the lessons andis easier to carry around. He was not alone: most pupils used the computer regularly during
Spanish lessons (Diagram 6), but 80% also used smartphones to look up words or otherinformation. More pedagogical uses of the smartphone, such as applications for vocabulary
practice or watching instructive videos, were rarely found.

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  Diagram	
  6	
  -­‐	
  Individually	
  chosen	
  computer	
  use	
  during	  Spanish	
  lessons	
  
90%	
  
80%	
  
70%	
  
60%	
  
50%	
  
40%	
  
30%	
  
20%	
  
10%	
  
0%	
  

ScienceArts
Economics

1 - Hardly ever useit

2 - Once or twice 3 - A short time most 4 - Almost all theeach termof the Spanish
time on mostlessons
Spanish lessons	  Four main reasons to explain differences in computer use between subjects can be distinguished(Diagram 7). Languages and social sciences involve more information search and writing.
Several pupils pointed out that it is more difficult in some subjects (mathematics, physics, andchemistry) than in others to make notes on the computer, as they require drawing of diagrams,
graphs, etc. The computer use also seems to depend on teachers’ preferences and ways ofteaching (cf. Svärdhagen et al., 2011; Thullberg et al., 2009). Different schools seemingly havedifferent ICT culture; especially the Economics pupils made little use of their computers.
Whether this depends on teacher beliefs, lack of teacher training, or other factors, needs to befurther investigated.

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50%	
  
45%	
  
40%	
  
35%	
  
30%	
  
25%	
  
20%	
  
15%	
  
10%	
  
5%	
  
0%	
  

Diagram	
  7	
  -­‐	
  Reasons	
  for	
  diﬀering	  computer	
  use	  in	
  diﬀerent	
  school	
  subjects	
  ScienceArts
Economics

Information Depends on Essay andEasier to
Oral
Onlinesearch.
teaching style. report writing. make notes/ presentations dictionaries.
draw by hand. or hand-in
tasks.

	  Some pupils did not clearly link their computer use to specific subjects, but rather stated personalreasons for (not) using the computer. Pupil 15 (Science) commented that she starts her computer
only if the teacher says that it is going to be used during the lesson; she preferred not to use it as
it makes her focus less on the lesson content. Pupil 18 (Science), showing a clear aversion tocomputers, stated that she chooses to use papers, unless the teacher tells her to use the computer.
An Economics pupil (17) wrote that the computer makes storing information from the lessons
easier. This can explain why she preferred to use the computer in subjects where the teachers giveout digitalised information, but it does not explain why the computer use in those particularsubjects is elicited by the teachers.
The pupils reported many uses of their computers during the Spanish lessons (Diagram 8).
Facebook interaction, dreaded by many teachers, was scarce, although there was much “lesson
irrelevant information search” going on, including looking at the online schedule, finding out
what is for lunch, checking bus time tables etc. Again, reading, writing, searching for informationand doing exercises were among the main areas of computer use; surprisingly, though, essay
writing did not score higher. According to Warschauer et al. (2010), “the greatest impact ofindividual laptop use is on student writing” (p. 221).
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Volume 2 - Issue 1 - Winter	  Few pupils used the computer for making notes, and many expressed clearly that they saw great
disadvantages in using the computer for this. (Only one pupil stated the opposite.)	
  Diagram	
  8	
  -­‐	  Areas	
  of	
  computer	
  use	  by	
  pupils	
  during	  Spanish	
  lessons	
  
100%	
  
90%	
  
80%	
  
70%	
  
60%	
  
50%	
  
40%	
  
30%	
  
20%	
  
10%	
  
0%	
  

ScienceArts
Economics	
  Advantages and disadvantages of computer or pen/paper use
As shown in Diagram 9, the most useful use of the computer, according to the pupils, is forwriting essays (although, as seen in Diagram 8, this use could increase among the participants).
Almost half of the pupils saw online dictionaries as useful, and about a third mentioned grammar
exercises and information search; even fewer online grammar explanations (they preferred
explanations by the teacher). Only Economics pupils talked about the use of computers for oralpresentations, with PowerPoint. Again, this might depend on different school or study
programme cultures.

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  Diagram	
  9	
  -­‐	  Perceived	
  usefulness	
  of	
  computer	
  use	  in	
  Spanish	
  lessons	
  
80%	
  
70%	
  
60%	
  

Science

50%	
  

Arts

40%	
  

Economics

30%	
  
20%	
  
10%	
  
0%	
  

	
  

Diagram 10 shows the areas that the pupils did not see as good for computer use.

40%	
  
35%	
  
30%	
  
25%	
  
20%	
  
15%	
  
10%	
  
5%	
  
0%	
  

Diagram	
  10	
  -­‐	  Perceived	
  disadvantages	
  of	
  using	  computers	  in	
  Spanish	  lessons	
  ScienceArts
Economics	
  Making notes was repeatedly commented on in the questionnaire. Many pupils found it difficult
to make notes on the computer, whereas only one preferred to use the computer. Teachers
wishing to increase ICT use in their classes probably need to take this opinion into account andteach suitable techniques for making notes and filing them (be it on computers or by hand).
Several pupils also wrote that they did not enjoy reading longer texts on the computer, as it was
tiring for the eyes. Working on the computer was also seen as distracting by some pupils.
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  Grammar explanations are also an area not suitable for computer use, according to some pupils,
who preferred teacher-led oral explanations at the whiteboard and/or individual explanations by
their desks.
	  The major advantage of online Spanish grammar exercises (Diagram 11), according to many ofthe pupils, is the instant corrective feedback. One of the Science pupils also mentioned the spell
checker function in Word as an advantage.
Diagram	
  11	
  -­‐	  Perceived	
  usefulness	
  of	
  using	  computers	
  for	  Spanish	
  grammar	
  learning	
  
60%	
  
50%	
  

ScienceArts
Economics

40%	
  
30%	
  
20%	
  
10%	
  
0%	
  
Instant Big array of Exercises No need to Easier to More fun Easy to findcorrective exercises to can be done keep track revise (e.g. than papers information
feedbackchooseseveralof papers at home)
from
times

	
  

In a study on electronic feedback and development of writing skills in a second language, Ware etal. (2006) conclude, though, that automated grammar feedback has unclear influences on students’
writing skills. Pupils’ reactions to this type of automated correction may be further researched.
Many pupils enjoyed the automatic feedback but were aware of its drawbacks, and commented
that without the automatic correction they were forced to think more for themselves, andperformed the paper-based exercises with greater care.

Features such as big variety of exercises to choose from and repeatability (without having to use
an eraser) were also mentioned as advantages of computer-based exercises, as opposed to typical
paper features (Diagrams 12 and 13).
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60%	
  

Diagram	
  12	
  -­‐	  Perceived	
  advantages	
  of	
  using	
  paper-­‐based	
  grammar	  exercises	
  

50%	
  

Science	
  
Arts	
  
Economics	
  

40%	
  
30%	
  
20%	
  
10%	
  
0%	
  
Easier	  /	
  faster	
  to	
   Easy	  to	
  save	   Need	  to	
  think	  for	
   Muscle	
  memory.	
   Reliable,	
  few	  learn.	
  papers	  /	
  consult	  yourself.	
  errors.	
  book	
  and	  review.	
  

	
  

Several pupils conveyed strong opinions on advantages of paper-based exercises. Pupil 9(Science): “there’s no automatic correction [and] you have to know what you’re doing”. Pupil 18(Science): “you get a very concrete feeling, and it absolutely [enters] your brain a hundred percent faster, when things are in paper-form. You can quickly ask the teacher or look things up on
the internet if you’ve made a mistake.” Pupil 14 (Science): “I feel that I learn the spelling better if
I can write by hand instead of using the computer”. Pupil 17 (Economics) also mentions spelling,
and that it is an advantage to have to think for yourself instead of getting the correct spelling fromthe spell checker in Word. Pupil 16 (Arts) says, “I get a better feeling for the grammar when I
write by hand” and “I also think it’s important to keep writing by hand so that we don’t lose it
completely just because the computers soon take over”.
Several pupils liked the auto-correction feature of many online exercises, but here, pupils 23 and
13 (Science) said that it is good for learning to have to do your own corrections or revisions.

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  Diagram	
  13	
  -­‐	  Perceived	
  disadvantages	
  of	
  using	  computers	
  for	  Spanish	
  grammar	
  learning	
  

25%	
  

Science

20%	
  

Arts
15%	
  

Economics

10%	
  
5%	
  
0%	
  

	
  

Some pupils mentioned the possibility to review online exercises at home as an advantage ofcomputer-based exercises. Nevertheless, when it comes to perceived disadvantages of computerbased exercises (Diagram 13), several pupils pointed out that in order to review the content ofmany online exercises at a later occasion, they must do them all over again, something notneeded with paper-based exercises. They also found computers distracting (either because they
were tempted to do other things online, or because the exercises themselves were distracting due
to bad structure, irrelevant pictures or other design flaws). Unclear grammar explanations or
instructions can also be confusing and take attention away from the instructive purpose of theexercise – pupil 10 (Arts) explained how she sometimes focused more on the exercise layout thanon its content. To cite Brett et al. (2011), “Teaching material’s design stands out as one of theimportant questions for pupils, both in paper format and online”.
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  Errors in feedback, online dictionaries or translation sites also annoyed the pupils. Pupil 18(Science), wrote, “Google translate [...], it’s the worst thing I know! Many times it absolutely
doesn’t work; many times the sentences are incorrectly constructed. I prefer to think for myself!”.
Discussing advantages and drawbacks of using interactive whiteboards and multimedia in
language classrooms, Cutrim Schmid (2008) raise similar thoughts among pupils, pointing outthat the technology does provide them with easy answers but makes them think less forthemselves, thus not evolving their imagination or learning strategies.

Diagram	
  14	
  -­‐	  Perceived	
  drawbacks	
  of	
  using	
  paper-­‐and-­‐pen	
  grammar	  exercises	
  
45%	
  
40%	
  

Science

35%	
  

Arts

30%	
  

Economics

25%	
  
20%	
  
15%	
  
10%	
  
5%	
  
0%	
  

	
  

Many pupils saw the fact that papers are easy to lose or forget as the main drawback of paperbased exercises (Diagram 14). Pupil 10 (Arts) pointed out, however, that it is up to the pupil not
to lose papers and that he/she can purchase a loose-leaf binder.
Pupil 20 (Science) found it boring to correct the exercises manually, saying that this leads to notdoing any corrections and thus not learning as much. Pupil 11 (Arts) had similar thoughts and
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  mentioned that manual corrections are time consuming. Pupil 23 (Science) also thought that
paper-based exercises are boring, since “most of the things you do at school are done in paperform”, and she said that this made her less focused. Pupil 12 (Arts) said that paper-based
exercises generally are less individualised.
Recommendations for the use of computers or paper and pen
The pupils’ most frequent recommendations for computer-based grammar exercises design(Diagram 15) focus on layout, instructions and feedback. The design of exercises influenced
greatly on several pupils’ opinions on whether they were useful (cf. Brett et al., 2011). The
researcher could arguably have found better exercises; however, as mentioned before, efforts
were made not only to find exercises with a clear layout and a well thought-out instructional
purpose, but also to choose material reflecting what is actually used and easily accessible forteachers.

Diagram	
  15	
  -­‐	  Computer-­‐based	
  exercise	
  design	
  recommenda3on	
  
60%	
  
50%	
  
Science

40%	
  

Arts

30%	
  

Economics

20%	
  
10%	
  
0%	
  

	
  

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  Again, many pupils appreciated the instant corrective feedback. However, automated correction
might be most appropriate as a complement to traditional corrections, as the interactive parts ofordinary feedback from a teacher ought not be underestimated (Ware et al., 2006). Several pupils
stressed that the automatic correction is only useful if the feedback is correct (which was notalways the case), and if it is not too “picky”, i.e. that variations or synonyms should be allowed.6
The most frequent recommendations for design of paper-based grammar exercises are shown in
Diagram 16.

Diagram	  16	
  -­‐	
  Paper-­‐based	
  exercise	
  design	
  recommenda3ons	
  
45%	
  
40%	
  
35%	
  
30%	
  

Science

25%	
  

Arts

20%	
  

Economics

15%	
  
10%	
  
5%	
  
0%	
  

	
  

The diagram sums up some of the main points of the questionnaire and the diaries: pupils prefervaried learning material, with well-structured and easily understood exercises that force them to
use their mental capacities, providing them with good explanations of the grammar to learn. They
like “fill-in-the-blanks”, although not few pupils expressed the feeling that they learn more, betteror faster when writing by hand (making notes, doing exercises, translating, writing essays) as this
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
6

A good example is an exercise asking pupils to conjugate verbs in the “you”-form. Spanish has five verb endings
translatable as “you”. Erroneous corrections were not uncommon.

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Volume 2 - Issue 1 - Winter	  makes them think more. The pupils also asked for more written exercises, computerised or byhand, such as translations and essay writing.
Conclusions and discussion
The main research questions in the present study were:• When do pupils see computers as an appropriate tool for learning Spanish grammar?
• When do they not see them as appropriate?
• What didactic and scientific implications can be drawn from these results?
To the pupils, some things seem more important than others in computer-based grammar
exercises: the corrective feedback (preferably instant, but not too picky; it must on the other handmake no mistakes); the interface design (not confusing or distracting, and providing clear
instructions). Many of the participants, thus, enjoyed online grammar exercises, if they are wellstructured, instructive and provide accurate automatic corrective feedback with explanations to
the errors. If these wishes for online exercises design are to be met, teachers (and/or pupils) need
to be able to modify the exercises, as much of the available material is poorly constructed(Pegrum, 2009; Kervin et al., 2011; Motteram, 2011). The question is whether teachers are – orfeel – competent to do so, and if they can find the time for it. If Tomlinson (2011) is correct thatthese kinds of auto-corrected exercises function best for pupils who learn easily on their own, butless for others who need more teacher explanations, schools need to be aware and not put too
much faith in them.
Rosen (2010) writes that pupils “thrive on multimedia, multitasking, social environments forevery aspect of their lives except education” and that “we must find new tools to engage ourstudents and help them learn in ways that work for them and for teachers” (pp. 3 – 5). The present
study contradicts this somewhat, as the participants appreciated traditional learning and teaching
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  styles when they were challenging and well thought-through. One might ask, as Roszak (1994), if“the curriculum [is] to adapt to the computer, or the computer to the curriculum?” (p. 52).
The participating pupils saw computers as useful for writing essays, searching for information
and using online dictionaries. These might be the areas of language instruction most suitable for
ICT-based learning. As for online dictionaries, it is important that pupils learn how to use them(as well as printed dictionaries), and which ones are reliable. School authorities should invest ingood digital dictionaries – probably also for mobile phones – rather than suggest that teachers andpupils rely on non-cost online alternatives. The results of Chiu et al. (2013), finding that theretention of new words is better when pupils have used printed dictionaries, compared toelectronic versions of the same dictionaries, ought probably to be taken into account as well.
Most of the pupils saw computers as less useful for making notes. Teachers may teach thembetter ways to make notes and to file information, if it is desirable that computers be used more.
Considering, however, that not few pupils stated clearly that they learn more easily and retain theknowledge better when writing by hand, schools should ask themselves whether computer use ismore important than pupils’ learning. An open dialogue in the language classroom on learning
methods and their advantages or disadvantages may be recommended.
Further research suggestions
The present study does not claim to provide any absolute answers to how or when to use ICTbased teaching methods in the language classroom, but indicates, nevertheless, several paths tofollow in future research and for teachers to consider in their daily teaching practice. The field ofteaching material design would benefit from further studies, especially comparing the effects ofdifferent designs on pupils’ attitudes and reactions and the way the design influence on pupils’

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Volume 2 - Issue 1 - Winter	  interactions with the exercises and their experienced learning outcome.7 Multimodal studies
could further elucidate how pupils interact with different learning methods in the language
classroom, and for what purposes.
Further studies on how pupils use and perceive automated corrective feedback would beinteresting, especially in the context of vocabulary and grammar practice, where few studies havebeen conducted. Compared outcomes of vocabulary and grammar learning using online exercisesand exercises written by hand would be of great interest.
Another perspective benefiting from further studies might be the opposite of the one adopted here:teacher incentives to use ICT in the language classroom. Which ICT practices do teachers choose(or not choose), and why? Mechanisms directing teachers’ choice of teaching methods are highlyinteresting in an era where ICT is often seen as the big promising solution to declining pupil
performances. Are choices consciously made or do schools succumb to prevailing ideas andcomputer company lobbyists?
	
  

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
7

It is very difficult to evaluate actual learning outcome of a given modality or technique, considering the many otherfactors involved in any learning situation. Experienced learning outcome may on the other hand have much to say
about the appropriateness of different teaching methods.

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  References
AlAmmary, Jaflah (2012), Educational Technology: A Way to Enhance Student Achievement at
the University of Bahrain. 3rd. International Conference on New Horizons in Education INTE 2012, 55: 248–257.
Andersson, Patrik (2010), IKT i skolan. En studie rörande gymnasieelevers attityder till IKT i
undervisningen. Växjö: Linnéuniversitetet, Institutionen för pedagogik, psykologi och
idrottsvetenskap.
Ayres, Robert (2010), Learner Attitudes Towards the Use of CALL. Computer Assisted
Language Learning, 15(3): 241 – 249.
Brett, David and González-Lloret, Marta (2011), Technology-Enhanced Materials, 351 – 369, in:Long, M. H. and Doughty, C. J. (Eds.), The Handbook of Language Teaching. Malden;
Oxford; Chichester: Wiley-Blackwell.
Buskqvist, Ulf and Molin, Lennart (2011), Forskningsanknytning och IKT - Röster frånlärarutbildningen vid Karlstads universitet. Karlstad: Karlstads universitet, Estetiskfilosofiska fakulteten, pedagogik.
Cavus, Nadire and Kanbul, Sezer (2010), Designation of Web 2.0 Tools Expected by theStudents on Technology-based Learning Environment. Innovation and Creativity in
Education, 2(2): 5824–5829.
Chapelle, Carol A. (2011), Computer-Assisted Teaching and Testing, 628 – 644, in: Long, M. H.
and Doughty, C. J. (Eds.), The Handbook of Language Teaching. Chichester: WileyBlackwell.

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Volume 2 - Issue 1 - Winter	
  Chiu, Li-Ling and Liu, Gi-Zen (2013), Effects of Printed, Pocket Electronic, and Online
Dictionaries on High School Students’ English Vocabulary Retention. The Asia-PacificEducation

Researcher.

Retrieved

February

04,

2014,

from

http://link.springer.com/article/10.1007%2Fs40299-013-0065-1
Cobo Romaní, Cristóbal and Moravec, John W. (2011), Aprendizaje Invisible. Hacia una nueva
ecología de la educación. Barcelona: Col·lecció Transmedia XXI. Laboratori de Mitjans
Interactius / Publicacions i Edicions de la Universitat de Barcelona.
Council of Europe (2001), The Common European Framework for Language Learning. Retrieved
February

04,

2014,

from

http://www.coe.int/t/dg4/education/elp/elp-

reg/Source/Key_reference/CEFR_EN.pdf
Cutrim Schmid, Euline (2008), Potential Pedagogical Benefits and Drawbacks of Multimedia Usein the English Language Classroom Equipped with Interactive Whiteboard Technology.
Computers & Education, 51(4): 1553–1568.
Davis, F. D. (1989), Perceived Usefulness, Perceived Ease of Use, and User Acceptance ofInformation Technology. MIS Quarterly, 13(3): 319 – 339.
Drucker, Peter (1959), The Landmarks of Tomorrow. Heinemann.
Dörnyei, Zoltán (2010), Questionnaires in Second Language Research: Construction,
Administration, and Processing. New York: Routledge.
Dörnyei, Zoltán and Ushioda, Ema (2011), Teaching and Researching Motivation. Harlow:
Pearson Education Limited.

116	
  
	
  

The IAFOR Journal of Education
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Volume 2 - Issue 1 - Winter	
  Edmunds, Rob, Thorpe, Mary and Conole, Grainne (2012), Student Attitudes Towards and Useof ICT in Course Study, Work and Social Activity: A Technology Acceptance Model
Approach. British Journal of Educational Technology, 43(1): 71–84.
Enkvist, Inger (2002), Feltänkt. En kritisk granskning av idébakgrunden till svensk skolpolitik.
Stockholm: SNS Förlag.
Enkvist, Inger (2011), La buena y la mala educación: Ejemplos internacionales. Madrid:
Encuentro.
Granath, Solveig and Estling Vannestål, Maria (2008), IKT i språkundervisningen i teori och
praktik, in: Fönster mot språk och litteratur. Karlstad: CSL (Centrum för Språk- ochlitteraturdidaktik.
Grönwald, Bo (1999a), Övningar i spansk grammatik - Del 1. Kolmården: EntreVista Läromedel.
Grönwald, Bo (1999b), Övningar i spansk grammatik - Del 2. Kolmården: EntreVista Läromedel.
Hegelheimer, Volker and Fisher, David (2006), Grammar, Writing, and Technology: A Sample
Technology-supported Approach to Teaching Grammar and Improving Writing for ESL
Learners. CALICO JOURNAL, 23(2): 257.
Kahraman, Sakıp, Çevik, Ceren and Kodan, Hülya (2011), Investigation of University Students’Attitude Toward the Use of Powerpoint According to Some Variables. World Conferenceon Information Technology, 3: 1341–1347.
Karlstads kommun (2012), Karlstads internationella TIME-utbildning (NAES). Retrieved
February

04,

2014,

http://karlstad.se/afiler/Programblad/TIME2012%20liten%20storlek.pdf

117	
  
	
  

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Volume 2 - Issue 1 - Winter	
  Kern, Richard (2006), Perspectives on Technology in Learning and Teaching Languages. TESOL
Quarterly, 40(1): 183 – 210.
Kervin, Lisa and Derewianka, Beverly (2011), New Technologies to Support Language Learning,
328 – 351, in: Tomlinson, B. (Ed.), Materials Development in Language Teaching.
Cambridge: Cambridge University Press.
Kroksmark, Tomas (2006), Innovativt Lärande. Didaktisk tidskrift, 16(3): 7–22.
Lannvik Duregård, Maria (2010), Moderna språk - ämnen i kris. Lärarnas Nyheter. Retrieved
February 04, 2014, from http://www.lararnasnyheter.se/alfa/2010/04/15/moderna-sprakamnen-kris
Larsson, Staffan (1986), Kvalitativ analys - exemplet fenomenografi. Lund: Studentlitteratur.
Lim, Kang-Mi and Shen, Hui Zhong (2006), Integration of Computers into an EFL Reading
Classroom. ReCALL, 18(2): 212 – 229.
Longcamp, Marieke, Boucard, Céline, Gilhodes, Jean-Claude, Anton, Jean-Luc, Roth, Muriel,
Nazarian, Bruno and Velay, Jean-Luc (2008), Learning through Hand-or Typewriting
Influences Visual Recognition of New Graphic Shapes: Behavioral and Functional
Imaging Evidence. Journal of Cognitive Neuroscience, 20(5): 802–815.
Lund, Stefan (2006), Marknad och medborgare: elevers valhandlingar i gymnasieutbildningens
integrations- och differentieringsprocesser.
Lund,

Stefan(2007),

Valfrihetochkonkurrens:

Utvecklingstendenser

gymnasieutbildningen. Pedagogisk forskning i Sverige, 12(4): 281–300.

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Volume 2 - Issue 1 - Winter	
  Motteram, Gary (2011), Developing Language-learning Materials with Technology, 303 – 327, in:Tomlinson, B. (Ed.), Materials Development in Language Teaching. Cambridge:
Cambridge University Press.
Nutta, Joyce (1998), Is Computer-based Grammar Instruction as Effective as Teacher-directed
Grammar Instruction for Teaching L2 Structures? Calico Journal, 16(1): 49 – 62.
Odlander, Johanna (2007), Uppsalaskolor lockar elever med resor. UNT.se. Retrieved February
04,

2014,

from

http://www.unt.se/inc/print/uppsalaskolor-lockar-elever-med-resor-

300098-default.aspx
OECD (2008), New Millennium Learners. Initial Findings on the Effects of Digital Technologies
onSchool-age

Learners.

Retrieved

February

04,

2014,

from

http://www.oecd.org/dataoecd/39/51/40554230.pdf
Pegrum, M. (2009), From Blogs to Bombs. Crawley, Western Australia: University of Western
Australia Press.
Rosen, Larry D. (2010), Rewired: Understanding the iGeneration and the Way They Learn. New
York: Palgrave Macmillan.
Rosén, Monica (2012), Förändringar i läsvanor och läsförmåga bland 9- till 10-åringar. Resultatfrån internationella studier, 111 – 139, in: Läsarnas marknad, marknadens läsare – enforskningsantologi SOU 2012:10. Stockholm: SOU.
Roszak, Theodore (1994), The Cult of Information. A Neo-Luddite Treatise on High-Tech,
Artificial Intelligence, and the True Art of Thinking. New York: Pantheon.
Skolverket (2013), Om ämnet Moderna språk. Retrieved February 04, 2014, fromhttp://www.skolverket.se/
119	
  
	
  

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Volume 2 - Issue 1 - Winter	
  Svensson, Patrik (2008), Språkutbildning i en digital värld Informationsteknik, kommunikationoch lärande. Norstedts Akademiska Förlag.
Svärdhagen, Jan and Embretsén, Eva-Lena (2011), Nästa generations lärande. Högskolan
Dalarna: IT och lärande i PUD-regionens kommuners förskolor och skolor. Högskolan
Dalarna.
Tallvid, Martin and Hallerström, Helena (2009), En egen dator i skolarbetet – redskap för
lärande? Utvärdering av projektet En-till-en i två grundskolor i Falkenbergs kommun.
Delrapport 2. Falkenbergs kommun: Barn-och utbildningsförvaltningen.
Thullberg, Per and Szekely, Christina (2009), Redovisning av uppdraget att bedömaverksamheters och huvudmäns utvecklingsbehov avseende IT-användningen inom
förskola, skola och vuxenutbildning samt ge förslag på insatser. Stockholm: Skolverket.
Tomlinson, Brian (2011), Access-self Materials, 414 – 432, in: Tomlinson, B. (Ed.), Materials
Development in Language Teaching. Cambridge: Cambridge University Press.
Usta, Ertugrul (2011), The Effect Of Web-Based Learning Environments On Attitudes Of
Students Regarding Computer And Internet. World Conference on Educational
Technology Researches - 2011, 28: 262–269.
Vanäs Hedberg, Margareta, Herrador Quero, Elvira and Vaccia Izami, Sylvia (2008), Alegría
Paso cuatro. Stockholm: Liber.
Ware, Paige D. and Warschauer, Mark (2006), Electronic Feedback and Second Language
Writing, 105 – 123, in: Hyland, K. and Hyland, F. (Eds.), Feedback in Second Language
Writing: Contexts and Issues. Cambridge: Cambridge University Press.

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Volume 2 - Issue 1 - Winter	
  Warschauer, Mark (1996), Motivational Aspects of Using Computers for Writing andCommunication, 29 – 46, in: Telecollaboration in foreign language learning:
Proceedings of the Hawai’i symposium. Technical Report. Honolulu, Hawai’i: Universityof Hawai’i, Second Language Teaching & Curriculum Center.
Warschauer, Mark, Arada, Kathleen and Zheng, Binbin (2010), Laptops and Inspired Writing.
Journal of Adolescent & Adult Literacy, 54(3): 221 – 223.
Velay, Jean-Luc, Longcamp, Marieke and Zerbato-Poudou, Marie-Thérèse (2004a), De La Plume
Au Clavier: Est-il Toujours Utile D’enseigner L’écriture Manuscrite. Comprendre lesapprentissages: Sciences cognitives et éducation: 69–82.
Velay, Jean-Luc, Longcamp, Marieke and Zerbato-Poudou, Marie-Thérèse (2004b), Le stylo et leclavier. Notre mode d’écriture influence-t-il notre perception de l’écrit  ? Langues etécritures: 37 – 54.
Wiebe, Grace and Kabata, Kaori (2010), Students’ and Instructors’ Attitudes Towards the Use of
CALL in Foreign Language Teaching and Learning. Computer Assisted Language
Learning, 23(3): 221 – 234.
Zucker, Andrew A. and McGhee, Raymond (2005), A Study of One-to-One Computer Use in
Mathematics and Science Instruction at the Secondary Level in Henrico County Public
Schools. SRI International.

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  Online resources:
http://cvc.cervantes.es/ensenanza/actividades_ave/aveteca.htm
http://www.itslearning.com
http://www.ver-taal.com

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Volume 2 - Issue 1 - Winter

	
  
	
  
	
  

Teaching Improvement Model Designed with DEA
Method and Management Matrix.
Bernard Montoneri

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Volume 2 - Issue 1 - Winter	
  Abstract

This study uses student evaluation of teachers to design a teaching improvement matrix based onteaching efficiency and performance by combining management matrix and data envelopment
analysis. This matrix is designed to formulate suggestions to improve teaching. The researchsample consists of 42 classes of freshmen following a course of English in Taiwan. The empiricalfindings show that proposed model can distribute all the evaluated classes into 4 quadrants
depending on their performance and efficiency, identify the importance of each performanceindicator, and suggest the improvement direction in different quadrants for all the evaluatedclasses. A study case of one inefficient class is presented in order to demonstrate the proposedmodel utility and feasibility.

Keywords: Data envelopment analysis; Teaching improvement matrix; Evaluation of teaching;teaching performance and efficiency.

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Volume 2 - Issue 1 - Winter	
  Introduction
Students’ evaluation of teaching (SET) has become, over the years, one the most importantmeasures of teaching quality and performance in universities of Taiwan. An increasing number ofhigher education institutions (HEIs) use online and anonymous SET to evaluate educators. In thecurrent system in Taiwan, SET typically occurs at the end of the semester and teachers receive
the results during the vacation or at the beginning of the following semester. However, the resultsof SET can provide detailed and applicable suggestions neither to educators who wish to improvetheir teaching, nor to administrators who want to guide and encourage educators. Therefore, thisstudy addresses the issue of improving classroom teaching from the viewpoint of first line
educators and administrators and tries to provide a systematic procedure which combines thewell-know concept of matrix in the field of management and data envelopment analysis (DEA), a
famous quantitative evaluation method which has already been applied to various fields. Under
DEA model, efficiency is relative to the other evaluated units in the same group. Montoneri et al.
(2011) showed that some units may obtain a high performance but a low relative efficiency, andvice versa. This ambiguous and disturbing situation needs to be addressed and explained. By
consequence, this paper presents a new teaching improvement matrix based on teachingefficiency and performance and develops teaching improvement procedures in order to formulate
concrete suggestions. An empirical analysis is conducted to test the applicability of the proposedmodel.
The research data consist of 42 classes of freshmen following a course of English in a universityof Taiwan during the academic year 2004 and 2005. Two inputs (teaching clarity and teachingenthusiasm) and two outputs (students’ learning interest and students’ satisfaction about grades)
are used in this study because they are highly correlated. The four indicators selected here
demonstrate the utility and feasibility of the model. Other and more indicators could be selected

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Volume 2 - Issue 1 - Winter	  as long as they show a high degree of correlation. This paper not only conducts a general analysisof the 42 classes, but also presents the case study of one inefficient class, that is, C30.
Literature review
Students’ evaluation of teaching
Stronge (1997) and Theall & Franklin (2000) identified SET as the most frequently studied
aspect of education. Most HEIs use student ratings as a measure of teaching quality andperformance (Cashin, 1999; Zabaleta, 2007). According to Wilson (1997), around 2,000 studies
were conducted on SET in the 20th century. Various studies show that SET are used for bothformative (for teachers to improve teaching) and summative (for administrators to monitor
quality) reasons (Edström, 2008; Arthur, 2009). A large number of studies focused primarily on
the validity of SET (Marsh, 1987, 2007; Wachtel, 1998), and even though some scholars identify
possible biasing factors (Marsh & Roche, 1987; Huston, 2005; Al-Issa & Sulieman, 2007), mostpublications agree that SETs are useful to both teachers and administrators. Following Marsh(1987), who states that the central purpose guiding student evaluations of professors should be toprovide feedback for the improvement of teaching, we provide, in our study, concrete advices foreducators to improve their teaching. Penny (2003) for example considers that SETs research has
yet to consider seriously that student ratings are an interaction between the students’ own
conception of learning and the teaching process. In our study, the selected indicators reflect
students’ perception of good teaching (for example, students’ perception of fairy grading). An
increasing number of HEIs use online SET to evaluate teachers. Sorensen and Johnson (2004)
edited a publication focusing on how online SET was used to evaluate both on-campus and online
classes. Carle (2009) analyzed student perceptions of teaching effectiveness across time for faceto-face and online courses. There is a trend in HEIs to increase the use of the Internet in
conducting SET (Achtemeier, Morris, & Finnegan, 2003; Harrington & Reasons, 2005). Many
universities tend to prefer online, anonymous and confidential end-of-term course evaluation.
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  There are obviously many advantages in implementing online ratings: significant cost savings(Bothell & Henderson, 2003), improved turnaround time (Sorenson & Reiner, 2003), and greater
convenience for students to respond without using valuable class time (Hmieleski & Champagne,
2000; Sorenson & Johnson, 2004). In order to measure teaching effectiveness, various indicators
have been tested and studied. Montoneri et al. (2012) review the literature in detail and list all theindicators used in studies from various countries such as China, Taiwan, the UK, the US, andSpain (notably from page 384 to 387). Some indicators such as communication skills, attitude
toward the student, knowledge of the subject, organizational skills, enthusiasm, fairness,flexibility, and encouragement of the student are identified as strongly related to teachingeffectiveness (Kim et al., 2000).
Efficiency assessment using data envelopment analysis
Efficiency can be assessed by applying various quantitative evaluation methods such as
stochastic frontier analysis (SFA), regression, statistics, ordinary least-squares (OLS), structural
equation modeling (SEM), data envelopment analysis (DEA), and multi-level modeling (MLM).
Which method is more appropriate depends on the research environment (Ferrier & Knox Lovell,1990). DEA is an attractive tool because it can measure the performance of educational
institutions, departments and courses (Montoneri et al., 2011; Montoneri et al., 2012). DEA
model evaluates the relative efficiency of each decision making units (DMUs) within a sample(Samoilenko & Osei-Bryson, 2008) and can receive multiple inputs and produce multiple outputs(Lee, 2009; Lin et al., 2009). There is a large body of literature concerning DEA. Among themost influential studies, Førsund & Sarafoglou (2002) cite Farrell’s seminal 1957 paper on
concepts of efficiency and the study published by Charnes, Cooper, & Rhodes (1978), which wasparticularly influential in developing and expanding Farrell (1957). Their model, called the“Charnes-Cooper-Rhodes (CCR) model” or “CCR model”, notably includes the function andconcept of benchmarking. According to Johnes (2006), the multiple input and output nature of
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  production in HEIs makes DEA rather than SFA the ideal choice of method in this context. Many
studies assess the efficiency of universities (Ng & Li, 2000; Abbott & Doucouliagos, 2003;
Johnes, 2006) and university departments (Colbert, Levary, & Shaner, 2000; Martin, 2006). Even
though many scholars apply statistical analysis or qualitative methods to assess the performanceof various courses (Leshem & Bar-Hama, 2008; Richards, 2010), there is a growing trend to use
DEA (McGowan & Graham, 2009; Montoneri et al., 2011; Montoneri et al., 2012).
Various applications of management matrix
A number of studies have designed two-dimensional, categorical conceptions of performance
quality collectively called management matrices; these matrices have been found to be useful inunderstanding and improving a variety of job performances. Management matrix was first
implemented in the aerospace industry at the end of the 1950s. In the 1960s, Professor Allan Pred
criticized normative location theories and introduced the concept of the behavioral matrix inconnection with a theory of behavior and location (Pred, 1967). Davis & Lawrence (1977)
showed that a matrix organization could include various organizing principles such as function,
product, and area. Selby (1987) proposed to use Pred's behavioral matrix as a tool for the analysisof enterprises in rural areas. The time management matrix, popularized by Covey (1989), divides
time into four quadrants: quadrant 1-urgent and important; quadrant 2-important but not urgent;quadrant 3-urgent but not important; quadrant 4-neither urgent nor important. Jung (2005)
designed a matrix divided into four quadrants focusing on information and communication
technology (ICT). Taylor et al. (2004) analyzed why so few non-credentialed teachers remainedin teaching in the Los Angeles Unified School District (half of the new teachers leave after theirfirst year). They proposed a matrix of teaching practice classification based on works by notably
Coloroso (1994) and Edwards (2000).

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Volume 2 - Issue 1 - Winter	
  Methodology
The study extends the concept of management matrix to construct a teaching improvement matrix
model. This proposed matrix divides classes into quadrants according to their performanceindicators’ room for improvement. Applicable steps are developed to test model’s feasibility andutility in order to formulate concrete suggestions for both administrators and educators.
Teaching improvement matrix model
The average values of teaching performance and teaching efficiency can segment the matrix into
four quadrants, named I, II, III, and IV.
lTeaching performance: average value of classes’ performance indicators selected fromstudents’ ratings to teachers at the end of each semester (in y-axis).

l

The teaching efficiency: relative efficiency value calculated by applying DEA model and byusing the above-mentioned selected performance indicators as input and output indicators(in x-axis).

Classes are located in quadrant I if their teaching performance and their teaching efficiency areboth superior to the average values; on the contrary, the classes having both values inferior to theaverage are in quadrant III. Classes are in quadrant II if their teaching performance is superior to
the average value and their teaching efficiency is inferior to the average value. Classes with ateaching performance inferior and a teaching efficiency superior to the average value are inquadrant IV.
Analysis of classes’ improvement direction
Once classes have been located in different quadrants, the improvement direction for each class is
explored. We take into consideration indicators’ contribution in calculating the relative efficiency
and their room for improvement in order to identify the importance of each performance indicatorand to suggest the improvement direction. Classes’ relative efficiency can be increased by
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Volume 2 - Issue 1 - Winter	  minimizing inputs’ value or by maximizing outputs’ value. An output orientation evaluates the
maximum output performance needed under the current input resources, while an input
orientation evaluates the minimum input effort needed to maintain the current output
performance. However, Montoneri et al. (2011) indicate that minimizing input effort in order toobtain an efficiency value equal to one can mislead educators, because input orientation means to
obtain a higher relative efficiency by reducing teaching efforts. This will probably discourage
hard-working teachers from making tremendous efforts to improve their teaching skills.
Therefore, we choose an output oriented analysis and we only discuss how to increase theperformance of output indicators. Accordingly, classes’ relative teaching efficiency can beenhanced by additional improvement effort in output indicators. We define for each class the
additional effort needed for any output indicator, Oi, as the ratio of the importance of Oi’s
improvement needed in calculating relative efficiency to the importance of all the outputs’
improvement needed. It is expressed as follows (1):Oi ' s contribution in efficiency× Oi ' s room for improvement ×100
DMU' s additional effort needed for Oi (%) = numberof outputs∑ O j ' s contribution in efficiency× O j ' s room for improvement
j=1

In equation (1), Oi represents selected output indicators; i varies from one to the number of
outputs. If indicator Oi’s contribution is 100%, it means that the relative efficiency value of thisclass is totally owing to this indicator. For example, an empirical study chooses only two outputs,
such as Ouput1 and Ouput2, to evaluate classes’ relative efficiency. Assuming the outputs’
contribution in calculating efficiency value are 0% and 100%, and the outputs’ rooms for
improvement are 3.4% and 1.0%, respectively.
Then, the additional improvement effort needed in
Ouput1 =0 × 3.4 × 100
100 × 1.0 × 100= 0% and in Ouput2 == 100% .
0 × 3.4 + 100 × 1.0
0 × 3.4 + 100 × 1.0

It means that this class only needs to improve the indicator Ouput2 and can neglect Ouput1 inorder to increase its efficiency value in the short term. Similarly for all the classes, the equation
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Volume 2 - Issue 1 - Winter	  (1) suggests that they should concentrate or accentuate more improvement effort on the output
indicator needing highest improvement effort value. According to this rule, we are able tosegment all the classes into several categories, such as: “100% effort on Ouput1”, “Effort on
Ouput1> Effort on Ouput2”, “Effort on Ouput2> Effort on Ouput1” and “100% effort on Ouput2”.
This segmentation aims at providing classes with concrete information about the additional effort
in what direction they need to concentrate on in order to effectively improve their efficiency andperformance.
Construction steps for formulating teaching improvement suggestions
This section presents the detailed steps to apply, from micro angle, the proposed matrix toconstruct improvement suggestions. This analysis concerns a specific study for an individual
inefficient class. It can help teachers to know in what quadrant they and other classes are locatedand how much effort they should make to improve their efficiency and their performance. This
phase consists of two stages: calculating the relative efficiency of each class and applying the
proposed teaching improvement matrix. They are described as follows:Stage one: Relative efficiency calculation
This stage gathers the results of relative efficiency calculated by DEA approach for a specificclass in order to support the formulation of improvement suggestions.
Step 1. Calculating all the classes’ relative teaching efficiency by applying DEA method in order
to identity the inefficient and efficient ones.
Step 2. Finding out each inefficient class benchmark reference classes in order to define its rolemodels.
Step 3. Listing each reference class contributions to the inputs’/outputs’ optimal values in orderto suggest a better choice of role models’ output or input indicators.

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Volume 2 - Issue 1 - Winter	
  Step 4. Ranking reference classes’ contributions for each indicator in order to know their impact
order, since the highest contribution does not always come from the same efficient class.
Step 5. Listing the rooms for improvement of each input/output indicator in order to provide
suggestions to inefficient classes.
Step 6. Listing each input/output indicator’s contribution in calculating classes relative efficiency
in order to provide some clues in finding indicators’ importance.
Stage two: Teaching improvement matrix application
This stage applies the proposed teaching improvement matrix in order to design applicable
improvement suggestions.
Step 7. Calculating the average value of all the classes’ relative teaching efficiencies and teaching
performance (the average value of all the classes’ indicators) in order to draw a teaching
improvement matrix.
Step 8. Comparing each class relative teaching efficiency and indicators’ average value with theaverage values obtained in Step 7 in order to locate them in the quadrants of thepreviously defined matrix.
Step 9. Engaging the analysis of indicators’ improvement effort in order to identify theimportance of each performance indicator and indirectly to indicate the improvement
direction.
Step 10. Formulating improvement suggestions for the inefficient classes.

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Volume 2 - Issue 1 - Winter	  The data source
The study case is a private university established in 1956 in Taiwan. The data comes from theuniversity’s online student rating system, which provides student feedback to teachers at the endof each semester. The characteristics of the data source and research object are as follows:
1. 42 classes are selected during the academic years 2004 and 2005. They are the decision
making units (classes), that is, the evaluated units, named from D1 to D42. There is an averageof 35 students per class and 42 classes. Therefore, the data consists of around 1470 students.
The sample is big enough to draw reliable conclusions.
2. Freshmen students in a university of Taiwan are chosen as a research object; Students are all
freshmen, so they are 18-19 years old. Earlier data were used to protect undergraduate
students' privacy.
3. Because of major modifications in the questionnaires in 2007, this paper uses data prior to thisdate for the sake of consistency.
4. The English course is a two-credit course (two hours/week).
5. Each teacher teaches only one class, that is, the 42 classes are taught by 42 different teachers.
6. The data are based on questionnaires (10 questions) filled out by the students at the end of eachsemester for each class. Each question is rated from one (very unsatisfied) to five (verysatisfied).
7. All the students are required to fill out the questionnaires online if they want their grades to bevalidated. So it is assumed they all did it.
Selection of input and output indicators
Two inputs and two outputs are selected for the empirical study based on the focus of this study,
that is, to find indicators having a significant impact on students’ motivation and satisfaction in
taking a course of English language. This paper aims at demonstrating the importance of teaching
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Volume 2 - Issue 1 - Winter	  clarity and teacher enthusiam and their impact on students’ learning interest and perception of
their scores. A correlation analysis is performed to test the reliability of the selected indicators.
All the 10 questions in the questionnaires have been tested, however, only the four questions
selected below are very positively correlated (with scores higher than 0.9; please see Table 1
below) and are reliable enough to draw scientific and useful conclusions (the highest correlations
for the other indicators is 0.882, between Q7 and Q10; however, it seems odd to correlateteachers’ attendance with students’ perception about their scores).
The results of Pearson correlation coefficients between input and output indicators are
summarized in Table 1. The inputs and outputs are all significantly positively correlated, reachinga statistically significant level of 1%, which is in line with the principle of equal expansion andmeans that the increase in inputs will result in the increase in outputs. The four indicators
abbreviated by I1, I2 and O1, O2 respectively are presented as follows:
Input indicators:
I1.

Teaching clarity (Q3: “Teachers explain clearly, make the content is easy to assimilate”): it
refers to the degree of assimilation by the students in relation with teachers’ professional
knowledge and preparation of teaching materials.

I2.

Teaching enthusiasm (Q6: “Teachers show enthusiasm for the course taught”): it indicates
whether teachers can actively answer students’ queries and clear their doubts. It signifies
whether teachers can positively respond to students’ questions and the maturity of teachers’
teaching skills and communication skills.

Output indicators:
O1. Students’ learning interest (Q5: “Teachers can increase your interest in this course”):
students’ interest and motivation are generally proportional to their learning performance.

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Volume 2 - Issue 1 - Winter	  O2. Students’ satisfaction about grades (Q10: “Teachers give a very fair assessment of student
achievement”): It does not mean that students are happy to have good grades or upset tohave bad grades, but that they consider they have been graded fairly and objectively.
Table	  1.	
  Pearson	
  correlation	  coefficients	
  between	
  input	
  and	
  output	
  indicators.	
  a	
  
	
  

	
  

Inputs	  I1	
  (Teaching	
  clarity)	
  

	
  

I2	
  
(Teaching	
  enthusiasm)	
  Outputs	
  

***

O1	
  (Students’	
  learning	
  interest)	
  0.965 	  ***0.905 	
  

***

O2	
  (Students’	
  satisfaction	
  about	
  grades)	
  0.934 	  ***0.953 	  ***

	  Significant	  levels	
  at	
  1%	
  and	  p	
  value<0.001.	
  a	
  The	
  number	
  of	
  observations	
  is	
  42.	
  Empirical study
The empirical study illustrates the feasibility of the proposed teaching improvement matrix model.
We first calculate the 42 classes’ overall relative efficiency.
Overall relative efficiency
Stage one: Relative efficiency calculation
The selected input and output indicators data is fed into the software Frontier Analyst to calculate
relative teaching efficiency values and relevant efficiency factors of the selected classes. The
results under CCR model of DEA are listed in Table 2:
The column “Teaching efficiency” ranks classes by descending order. Classes with an efficiency
value equal to 1 are efficient and constitute “reference sets” of efficiency benchmark for
inefficient classes (classes with efficiency value inferior to one). These efficient classes form
efficiency frontier curves; the efficiency value of each class is calculated by the distance between
their location and these efficiency frontier curves. Eight classes (C33, C13, C3, C22, C29, C27,
C5, and C25) are efficient and represent about 19% of all the classes. They do not need any
improvement in the input and output indicators. The average efficiency of all the classes is 0.978.
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Volume 2 - Issue 1 - Winter	  The column “Reference DMUs” includes only efficient classes. The classes with relative teachingefficiency do not have to refer to other classes; but each inefficient class has its proper referenceclasses and can emulate their features and take them as role models. As a result, inefficientclasses can approach to their efficiency frontier curves and by consequence enhance their relative
teaching efficiency.
The column “Reference times” indicates the number of times an efficient class acts as a peer. By
finding out the most popular reference class, it helps to identify a benchmark class and toformulate improvement suggestions for inefficient classes. Table 2 shows that C13 is the mostpopular reference class (24 times). Most of the inefficient classes refer to two or three efficientclasses which constitute their efficient frontier curves and become their reference classes. C16
has only one reference class, C5. This means that C16’s efficiency frontier curve is only
constituted by C5. Thus, all the efficiency factors concerning C16 are calculated based on C5’svalues.
The column “Room for improvement” indicates the additional effort needed to become an
efficient class. The calculation of the room for improvement of inefficient classes is based on
their reference classes. An increase or decrease of the inputs or outputs may increase classes’
efficiency value. Under the output oriented model, an increase of outputs’ performance undercurrent input resources can enhance the relative efficiency of classes until they become efficient.
This explains why the values of inputs’ room for improvement are always zero or negative.
Table 2 shows that the room for improvement in outputs for all the inefficient classes’ varies
from 0.3% to 9.2%. Inefficient classes have to pay different effort to O1 and O2 according toeach output’s room for improvement. C28 and C37 need to improve O1 more than O2; however,C12, C16, and C20 need to improve O2 more than O1.
The column “Contribution in calculating CCR efficiency” can provide useful information
concerning the importance of each input and output indicator in designing improvement
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Volume 2 - Issue 1 - Winter	
  suggestions for inefficient classes. Averagely speaking, O1 is the most important factor in
determining classes’ relative teaching efficiency (63.3%); the next most important factor is I2(59.0%). However, for the efficient classes, O1 is the most important factor (69.5%), followed byI1 (52.8%).
Table 2. Teaching efficiency and efficiency factors a of evaluated classes.

DMU name TeachingRankbefficiency

Reference
DMUs

Quadrant in Room for improvement(%)
Referen efficiency andce times performanceO1 O2 I1
I2
matrix

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Contribution in calculating
CCR efficiency (%)
O1

O2

I1

I2

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Volume 2 - Issue 1 - Winter

	
  
C33

1.000

1

C33

7

I

0.0

0.0

0.0

0.0

100.0

0.0

65.1

34.9

C13

1.000

1

C13

24

I

0.0

0.0

0.0

0.0

100.0

0.0

60.9

39.1

C3

1.000

1

C3

0

I

0.0

0.0

0.0

0.0

100.0

0.0

28.8

71.2

C22

1.000

1

C22

6

I

0.0

0.0

0.0

0.0

88.4

11.6

58.1

41.9

C29

1.000

1

C29

19

IV

0.0

0.0

0.0

0.0

67.8

32.2

42.8

57.2

C27

1.000

1

C27

1

IV

0.0

0.0

0.0

0.0

0.0 100.0

66.4

33.6

C5

1.000

1

C5

16

IV

0.0

0.0

0.0

0.0

0.0 100.0

0.0

C25

1.000

1

C25

19

IV

0.0

0.0

0.0

0.0

0.0 100.0

0.0 100.0

C8

0.997

9

C13, C25

0

I

0.3

0.3

-0.3

0.0

45.7

54.3

0.0 100.0

C42

0.995

10

C13, C25, C29

0

I

0.5

0.5

0.0

0.0

48.5

51.5

23.4

76.6

C14

0.995

11

C13, C25, C29

0

I

0.6

0.6

0.0

0.0

48.7

51.3

23.3

76.7

C28

0.991

12

C5, C25

0

IV

4.4

1.0

0.0

0.0

0.0 100.0

40.1

59.9

C15

0.990

13

C5, C22, C33

0

I

1.0

1.0

0.0

0.0

98.3

1.7

65.2

34.8

C34

0.990

14

C13, C25

0

IV

1.0

1.0

-0.1

0.0

45.2

54.8

0.0 100.0

C26

0.988

15

C5, C13, C29

0

I

1.2

1.2

0.0

0.0

68.5

31.5

43.4

56.6

C17

0.987

16

C13, C25, C29

0

I

1.3

1.3

0.0

0.0

48.6

51.4

23.3

76.7

C11

0.987

17

C5, C13, C29

0

I

1.4

1.4

0.0

0.0

68.8

31.2

43.8

56.2

C10

0.985

18

C5, C22, C33

0

I

1.5

1.5

0.0

0.0

98.3

1.7

64.5

35.5

C35

0.983

19

C13, C25

0

IV

1.7

1.7

0.0

0.0

45.9

54.1

0.0 100.0

C31

0.981

20

C13, C25, C29

0

I

2.0

2.0

0.0

0.0

47.9

52.1

23.1

76.9

C19

0.980

21

C13, C25, C29

0

I

2.0

2.0

0.0

0.0

49.1

50.9

23.5

76.5

C36

0.979

22

C13, C25, C29

0

I

2.1

2.1

0.0

0.0

48.5

51.5

23.2

76.8

C41

0.978

23

C5, C33

0

III

2.2

2.2

0.0

0.0

100.0

0.0

67.0

33.0

C18

0.977

24

C5, C13, C29

0

III

2.3

2.3

0.0

0.0

68.5

31.5

43.2

56.8

C37

0.977

25

C5, C27

0

III

4.9

2.4

0.0

0.0

0.0 100.0

66.6

33.4

C21

0.977

26

C13, C25, C29

0

II

2.4

2.4

0.0

0.0

48.4

51.6

23.1

76.9

C4

0.975

27

C5, C22, C33

0

II

2.5

2.5

0.0

0.0

98.3

1.7

64.7

35.3

C39

0.975

28

C13, C25, C29

0

II

2.5

2.5

0.0

0.0

48.7

51.3

23.2

76.8

C12

0.974

29

C5, C33

0

II

2.6

4.8

0.0

0.0

100.0

0.0

66.4

33.6

C7

0.966

30

C13, C25, C29

0

III

3.6

3.6

0.0

0.0

48.1

51.9

22.7

77.3

C23

0.965

31

C13, C25, C29

0

140	
  

II

3.7

3.7

0.0

0.0

48.2

51.8

22.9

77.1

	
  
C24

0.963

32

C13, C25, C29

0

III

3.9

3.9

0.0

0.0

47.3

52.7

22.9

77.1

C40

0.962

33

C13, C25, C29

0

II

3.9

3.9

0.0

0.0

46.9

53.1

23.2

76.8

100.0

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Volume 2 - Issue 1 - Winter	
  Average of
all the
DMUs

0.978

2.4

2.4

0.0

Average ofthe efficient
DMUs

1.000

0.0

0.0

0.0

Average oftheinefficient
DMUs

0.973

3.0

3.0

0.0

-0.1

63.3

36.7

41.0

59.0

69.5

30.5

52.8

47.2

61.9

38.1

38.3

61.7

0.0

-0.1

Notes. a I1 indicates teacher’s teaching clarity; I2 indicates teacher’s teaching enthusiasm; O1 indicates students’learning interest; O2 indicates students’ satisfaction about grades.
b

DMU denotes the evaluated class. The number of observations is 42.

Stage two: Teaching improvement matrix application
The average values of teaching efficiency and teaching performance of all the classes are 0.978
and 3.91; they segment the matrix into four quadrants and divide all the classes into different
locations in the matrix, as shown in Figure 1. There are 15 (representing 35.7%), 10 (23.8%), 10(23.8%), and 7 (16.7%) classes in quadrant I, II, III, and IV, respectively.

High	
  

Quadrant I: 15 DMUs

C21,C4,C39,C12,C23,C40,C32,C1,C6
,C30	
  

C33,C13,C3,C22,C8,C42,C14,C15,	
  Quadrant III: 7 DMUs

Quadrant IV: 10 DMUs

C41,C18,C37,C7,C24,C2,C16,C38,	
  C29,C27,C5,C25,C28,C34,C35	
  C26,C17,C11,C10,C31,C19,C36	
  

l 	
  

3.91	
  

Teaching	
  performance	  Quadrant II: 10 DMUs a

C20,C9	  l 	
  0.978	
  

Low	
  
Low	
  

Teaching	
  efficiency	
  

High	
  

Note. a DMUs located in each quadrant are in descending order of relative teachingefficiency.
Figure 1. Distribution of classes in the teaching improvement matrix.

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  In order to figure out the improvement direction for classes in different quadrants, we take into
consideration input and output indicators’ contribution in calculating the relative efficiency andtheir room for improvement to identify the importance of each indicator. Since this study uses an
output oriented model to engage the analysis, the inefficient classes’ relative teaching efficiency
can be increased by making an additional effort in output indicators, as defined in the equation(1). The results are listed in Table 3.
We observe that there are 11, 10, 10 and 3 inefficient classes located in quadrants I, II, III and IV,
and they are identified in red, blue, green and violet colors, respectively in Figures 1-2 and in
Tables 2-3. Two classes, C28 (in IV) and C37 (in III), are suggested to improve indicator’s
performance only in O2 (students’ satisfaction about grades); four classes (C12 in II and C41,
C16, C20 in III) are suggested to improve indicator’s performance only in O1 (students’ learninginterest). Most of other inefficient classes (18 classes) are suggested to improve O2 more than O1.
Moreover, for the more efficient classes (those located in quadrants I or IV), none is suggested to
improve only O1; for the classes with better performance (those located in quadrants I or IV),
none is suggested to improve only O2.

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Volume 2 - Issue 1 - WinterTable 3. Additional effort needed to increase teaching efficiency.
additional

Inefficientclasses’

Locatednamequadrant

O1 (%)

C8

I

C42

additional

Inefficientclasses’

LocatedO2 (%)

namequadrant

O1 (%)

O2 (%)

45.7

54.3

C41

III

100.0

0.0

I

48.5

51.5

C18

III

68.5

31.5

C14

I

48.7

51.3

C37

III

0.0

100.0

C28

IV

0.0

100.0

C21

II

48.4

51.6

C15

I

98.3

1.7

C4

II

98.3

1.7

C34

IV

45.2

54.8

C39

II

48.7

51.3

C26

I

68.5

31.5

C12

II

100.0

0.0

C17

I

48.6

51.4

C7

III

48.1

51.9

C11

I

68.8

31.2

C23

II

48.2

51.8

C10

I

98.3

1.7

C24

III

47.3

52.7

C35

IV

45.9

54.1

C40

II

46.9

53.1

C31

I

47.9

52.1

C2

III

48.3

51.7

C19

I

49.1

50.9

C16

III

100.0

0.0

C36

I

48.5

51.5

C32

II

47.7

52.3

C38

III

88.3

11.7

C1

II

98.3

1.7

C20

III

100.0

0.0

C9

III

68.3

31.7

C6

II

88.0

12.0

C30

II

47.7

52.3

Average of

II & III

67.1%

33.0%

Average ofaeffort needed in

I & IV

54.4%

b

45.6%

a

effort needed inb

Average of I, II, III, IV: 61.9% in O1, 38.1% in O2
Notes. a The located quadrant indicates the area where the classes are located in the teaching improvement matrix.
b

O1 indicates students’ learning interest; O2 indicates students’ satisfaction about grades.

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High	
  

Quadrant II: 10 DMUs a
100% in O1>O2: O2>O1: 100% in
O1:
O2:
C4	
  
C21	
  
C12
N/A
C1	
  
C39	
  

Teaching	
  performance	
  

C6

C23	
  

C11	
  

C14	
  

C22

C17	
  

100% O1>O2: Inputs= O2>O1: 100%in O1:
Outputs C34	   in O2:
N/A	
  
C29
N/A	
  
C28	
  
C35	
  
C27

100% in O1>O2: O2>O1: 100% in
O1:
O2:
C18	
  
C7	
  
C41
C37
C38	
  
C24	
  
C16
C9	
  

C3

Quadrant IV: 7 DMUs

Quadrant III: 10 DMUs

C20
Low	
  

Quadrant I: 15 DMUs
100% O1>O2: Inputs= O2>O1: 100%in O1:
in O2
Outputs
C8	
  	
  
C15	
  
N/A	
  
N/A
C33
C42	
  
C26	
  
C13

C5

C2	
  

C25

	
  
Low	
  

Teaching	
  efficiency	
  

High	
  

Note. a N/A means that there is no DMU located in this area. O1 indicates students’ learning interest; O2 indicates
students’ satisfaction about grades.

Figure 2. Indicator’s improvement priority in four quadrants.
Individual analysis: case of C30
C30 is ranked last in relative teaching efficiency according to DEA model. However, C30 has
teaching performance score higher than the average value of all the classes and is located inquadrant II of the matrix. Therefore, C30 is a good example to demonstrate how to formulate
improvement suggestions for the classes having good teaching performance but low relative
teaching efficiency. The analysis procedure is divided into two stages:
Stage one: Relative efficiency calculation
Step 1. The results of relative teaching efficiency analysis show that only eight classes are
efficient (C33, C13, C3, C22, C29, C27, C5 and C25).
Step 2. C30’s relative efficiency value is 0.916. C30’s reference classes are C13, C25 and C29.
Step 3. C13, C25 and C29’s contributions to C30’s inputs’/outputs’ benchmark values are listed
in Table 4.
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  Step 4. C13, C25 and C29’s contributions ranking for each input/output indicator are listed inTable 4 below.
Step 5. The rooms for improvement for C30’s input/output indicators are listed in Table 4.
Step 6. C30’s input/output indicators’ contributions in calculating C30’s relative efficiency arelisted in Table 4.
Table 4. Efficiency improvement analysis for the inefficient DMU C30.
Outputs a

Inputs

O1

O2

I1

I2

C13

28.9(3) b

27.0(3)28.6(3)27.7(3)C25

33.9(2)35.4(2)35.2(2)34.5(2)C29

37.2(1)37.6(1)36.2(1)37.8(1)Room for improvement (%)

9.17

9.17

0

0

Outputs/Inputs contribution (%) in
calculating relative efficiency

47.7

52.3

23.0

77.0

52.3

-

-

Stage 1: Relative efficiency calculation
Reference set’s
contributions to indicators’
benchmark values (%)

Stage 2: Teaching improvement matrix application
Analysis of indicators’
improvement effort (%)

47.7

Notes. a I1 indicates teacher’s teaching clarity; I2 indicates teacher’s teaching enthusiasm; O1 indicates students’learning interest; O2 indicates students’ satisfaction about grades.
b

Numbers in the parentheses indicate the contributions ranking for each input/output indicator.

Stage two: Teaching improvement matrix application

Step 7. The average value of all the classes’ relative teaching efficiencies and teaching
performance are 0.978 and 3.91. The teaching improvement matrix is drawn.
Step 8. C30’s relative teaching efficiency (0.916) is inferior to the average value of all the classes(0.978) and teaching performance (4.04) is superior to the average value of all the classes(3.91). Therefore, C30 is located in quadrant II of the matrix.

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  Step 9. The analysis of indicators’ improvement effort shows that C30 needs an additional effortof 47.7% in O1 and 52.3% in O2.
Step 10. Teaching improvement suggestions for C30:
1. C30’s two output indicators should be improved equally to 9.17%.
2. C30’s two inputs, I1 and I2, can be maintained at the same level. It means that the teacher of
C30 does not need to improve teaching clarity and teaching enthusiasm in order to improve
his/her global evaluation.
3. All the input and output indicators have contribution in calculating C30’s relative efficiency.
O1 represents 47.7% and O2 represents 52.3% for the output indicators; I1 represents 23.0%
and I2 represents 77.0% for the input indicators. Accordingly, the priority of indicators for
C30 is I2>O2>O1>I1. (I1: teaching clarity; I2: teaching enthusiasm; O1: students’ learninginterest; O2: students’ satisfaction about grades.)4. Taking into account both the room for improvement in inputs and outputs and theircontribution in calculating efficiency, the indicators with values not equals to zero at the sametime should be improved in a priority in order to increase the class relative efficiency.
Concretely speaking, it means that C30 needs to make efforts only on students’ learninginterest (O1) and students’ satisfaction about grades (O2), and concentrate on improving more
O2 than O1. It means that the teacher of C30 should, according to students, give theimpression that the way the educator grades them is fair and objective. It implies giving
feedback to students just after they receive their score (individually, not in public, as most
students will feel unconfortable about it, making things even worse). In our experience,
students appreciate when teachers give them a feedback and an explanation after the exam,even if they fail, or problably we should say, especially if they have a low score.

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Volume 2 - Issue 1 - Winter	  5. If C30 hopes to increase its relative efficiency in the short term, it should mainly refer to C29’s
students’ satisfaction about grades (O2) up to 37.6%, to C25’s O2 to 35.4% and to C13’s O2
to 27.0%; then refer to C29’s students’ learning interest (O1) up to 37.2%, to C25’s O1 to33.9% and to C13’s O1 to 28.9%.
6. If C30 hopes to increase its overall performance in each input and output indicators in the longterm, its performance improvement measures can not merely refer to one single efficient class,even though C29 is the major model for C30. C30 is suggested to mainly refer to all of C29’s
input and output indicators around 37%, then refer to all of C25’s indicators around 35%, andrefer to all of C13’s indicators around 28%. Concretely, one way to improve teaching is to ask
other teachers who obtain higher evaluation for advice. It is also recommended to attend
classes taught by some colleagues (if they agree) to benefit from their experience. It is also
advised to ask students why they appreciate one teacher’s class. In our experience for example,
some teachers are severe, grade students relatively low and still receive a high score because
students feel they were fairly graded. As a result, they don’t blame their teacher for the results.
7. C30, currently located in quadrant II of the matrix, might make progress in teaching efficiency
and upgrade to quadrant I, through the above-mentioned suggestions.

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Volume 2 - Issue 1 - Winter	
  Conclusion
Contribution
The present paper addresses the issue of improving classroom teaching by using online
students’ ratings of teachers at the end of each semester for the academic year 2004 and 2005.
The three main contributions of this study are:1.

Combining the concept of management matrix and a quantitative evaluation method to build
a teaching improvement matrix based on teaching efficiency and teaching performance;2.

Developing teaching improvement procedures in order to formulate concrete suggestions toimprove teaching;3.

Conducting an empirical study to demonstrate the proposed model’s feasibility and utility.

These contributions may help educational administrators to have an overview of classes’
efficiency and to obtain information concerning the number and the proportion of classes fromthe viewpoint of performance and efficiency. Applying this matrix every year may allow
administrators to assess the progression or regression of classes’ efficiency and performancetrend for each academic year.
Main findings
An empirical study is conducted and provides an overall analysis of all the evaluated classes andan individual analysis in order to construct a teaching improvement matrix. This matrix is drawn
according to the classification of classes under the CCR model of DEA. Classes are distributed in
the four quadrants depending on their performance and efficiency. Once classes have been
located in different quadrants, we take into consideration indicators’ contribution in calculating
the relative efficiency and their room for improvement in order to identify the importance of eachperformance indicator and indirectly to indicate the improvement direction in different quadrants
for all the efficient and inefficient classes. The results of the overall analysis show that the
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Volume 2 - Issue 1 - Winter	
  average values of teaching efficiency and teaching performance of all the classes are 0.978 and
3.91, respectively; they segment the matrix into four quadrants and divide all the classes into
different quadrants in the matrix. There are 15, 10, 10, and 7 classes in quadrant I, II, III, and IV,
respectively. The results of the individual analysis are based on the case C30; because this class islocated in quadrant II, it demonstrates how to formulate improvement suggestions for the classes
having good teaching performance but low relative teaching efficiency. C30’s relative efficiency
value is 0.916; it needs to make efforts only on O1 (students’ learning interest) and O2 (students’satisfaction about grades), and concentrate on improving more O2 than O1. Then, we formulate
improvement directions and suggestions in the short term and in the long term.
Future directions
In the current system in Taiwan, SET typically occurs at the end of the semester and teachers
receive the results during the vacation or at the beginning of the following semester. As a result,no matter whether educators are willing to improve their classroom teaching, they can only apply
changes to the students of the next year. Teachers and students often find little use for theevaluation process because there are no real time improvement suggestions during the semester.
Since students have become courted customers, universities lacking of financial support anddepending on student tuition fees for survival should pay more attention to students’ opinions andsatisfy their demands.

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Volume 2 - Issue 1 - Winter	
  References
Abbott, M., & Doucouliagos, C. (2003), The efficiency of Australian universities: A dataenvelopment analysis. Economics of Education Review, 22(1), 89–97.
Achtemeier, S., Morris, L., & Finnegan, C. (2003), Considerations for developing evaluations on
online courses. Journal of Asynchronous Learning Networks, 7(1), 1-13.
Arthur, L. (2009), From performativity to professionalism: lecturer’s responses to student
feedback. Teaching in Higher Education, 14, 441-454.
Al-Issa, A., & Sulieman, H. (2007), Student evaluations of teaching: perceptions and biasing
factors. Quality Assurance in Education, 15(3), 302-317.
Bothell, T. W., & Henderson, T. (2003), Do online ratings of instruction make Sense? In D. L.
Sorenson & T. D. Johnson (Eds.), Online student ratings of instruction [Special issue]. New
Directions for Teaching and Learning, 96, 69-80. Hoboken, NJ: Jossey-Bass.
Carle, A. C. (2009), Evaluating college students’ evaluations of a professor’s teachingeffectiveness across time and instruction mode (online vs. face-to-face) using a multilevelgrowth modeling approach. Computers & Education, 53(2), 429–435.
Cashin, W. (1999), Student Rating of Teaching: Uses and Misuses. In P. Seldin, Changing
Practices in Evaluating Teaching: A Practical Guide to Faculty Performance andPromotion/Tenure Decisions (pp. 25-44). Boston: Anker Publishing Company, Inc.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978), Measuring the Inefficiency of Decision
Making Units. European Journal of Operational Research, 2(6), 429–444.
Colbert, A., Levary, R., & Shaner, M. (2000), Determining the Relative Efficiency of MBA
Programs using DEA. European Journal of Operational Research, 125(3), 656–660.
150	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Coloroso, B. (1994), Kids Are Worth It: Giving Your Child the Gift of Inner Discipline. New
York: William Morrow.
Covey, S. R. (1989), The Seven Habits of Highly Effective People. New York: Free Press.
Davis, S. M., & Lawrence, P. R. (1977), Matrix. Reading, MA: Addison-Wesley Publishing Co.
Edström, K. (2008), Doing course evaluation as if learning matters most. Higher Education
Research & Development, 27, 95-106.
Edwards, C. (2000), Effective Classroom Management. New York: Allyn Bacon.
Farrell, M. J. (1957), The measurement of productive efficiency. Journal of the Royal StatisticalSociety Series A. General, 120(3), 253-282.
Ferrier, G. D., & Lovell, C. A. K. (1990), Measuring cost eficiency in banking: Econometric andLinear Programming Evidence. Journal of Econometrics, 46(2), 229-245.
Førsund, F. R., & Sarafoglou, N. (2002), On the Origins of Data Envelopment Analysis. Journalof Productivity Analysis, 17(1-2), 23–40.
Harrington, C. F., & Reasons, S. G. (2005), Online student evaluation of teaching for distanceeducation: A perfect match? The Journal of Educators Online, 2(1), 1-12.
Hmieleski, K., & Champagne, M. V. (2000), Plugging into course evaluation. The Technology
Source.

Retrieved

February

04,

2014,

from

http://technologysource.org/article/plugging_in_to_course_evaluation
Huston, T. (2005), Research report: Race and gender bias in student evaluations of teaching.
Retrieved February 04, 2014, from Seattle University, Center for Excellence in Teachingand Learning Web site: http://www.seattleu.edu/cetl/cetl_006.htm

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The IAFOR Journal of Education
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Volume 2 - Issue 1 - Winter	
  Johnes, J. (2006), Measuring teaching efficiency in higher education: an application of dataenvelopment analysis to economics graduates for UK universities. European Journal ofOperational Research, 174(1), 443-456.
Jung, I. (2005), ICT-Pedagogy Integration in Teacher Training: Application Cases Worldwide.
Educational Technology and Society, 8(2), 94–101.
Kim, C, Damewood, E., & Hodge, N. (2000), Professor Attitude: Its Effect on Teaching
Evaluations. Journal of Management Education, 24(4), 458-473
Lee, C. C. (2009), Analysis of overall technical efficiency, pure technical efficiency and scaleefficiency in the medium-sized audit firms. Expert Systems with Applications, 36(8), 1115611171.
Leshem, S., & Bar-Hama, R. (2008), Evaluating teaching practice. ELT Journal, 62(3), 257-265.
Lin, T. T., Lee, C. C., & Chiu, T. F. (2009). Application of DEA in analyzing a bank’s operating
performance. Expert Systems with Applications, 36(5), 8883-8891.
McGowan, W. R., & Graham, C. R. (2009), Factors contributing to improved teaching
performance. Innovative Higher Education, 34(3), 161-171.
Martin, E. (2006), Efficiency and Quality in the Current Higher Education Context in Europe: anapplication of the data envelopment analysis methodology to performance assessment of
departments within the University of Zaragoza. Quality in Higher Education, 12(1), 57-79.
Marsh, H. W. (1987), Student’s evaluations of university teaching: Research findings,
methodological issues, and directions for further research. International Journal of
Educational Research, 11(3), 253-388.

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  Marsh, H. W. , & Roche, L. A. (1987), Making Students' Evaluations of Teaching Effectiveness
Effective. The Critical Issues of Validity, Bias, and Utility. American Psychologist, 52(11),1187-1197.
Marsh, H. W. (2007), Students’ evaluations of university teaching: Dimensionality, reliability,
validity, potential biases and usefulness. In R. P. Perry & J. C. Smart (Eds.), Thescholarship of teaching and learning in higher education: An evidence-based perspective(pp. 319–383). New York: Springer.
Montoneri, B., Lee, C. C., Lin, T. T., &. Huang, S. L. (2011), A Learning Performance
Evaluation with Benchmarking Concept for English Writing Courses. Expert Systems with
Applications, 38(12), 14542-14549.
Montoneri, B., Lin, T. T., Lee, C. C., & Huang, S. L. (2012), Application of data envelopment
analysis on the indicators contributing to learning and teaching performance. Teaching andTeacher Education, 28(3), 382-395.
Ng, Y. C., & Li, S. K. (2000), Measuring the research performance of Chinese higher education
institutions: an application of data envelopment analysis. Education Economics, 8(2), 139–
56.
Penny, A. R. (2003), Changing the agenda for research into student’s views about university
teaching: four shortcomings of SRT research. Teaching in Higher Education, 8(3), 399-411.
Pred, A. (1967), Behavior and location: Foundations for a geographic and dynamic location
theory. Part I. Lund Studies in Geography, Series B, 27.
Richards, J. C. (2010), Competence and performance in language teaching. RELC Journal, 41(2),101–122.

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  Samoilenko, S., & Osei-Bryson, K. M. (2008), Increasing the discriminatory power of DEA in
the presence of the sample heterogeneity with cluster analysis and decision trees. Expert
Systems with Applications, 34(2), 1568-1581.
Selby, J. A. (1987), On the Operationalization of Pred's Behavioral Matrix. Geografiska Annaler.
Series B, Human Geography, 69(1), 81–90.
Sorenson, D. L., & Reiner, C. (2003), Charting the uncharted seas of online student ratings of
instruction. In D.L. Sorenson & T.D. Johnson (Eds.), Online student ratings of instruction[Special issue]. New Directions for Teaching and Learning, 96, 1-24. Hoboken, NJ: JosseyBass.
Sorenson, D. L., & Johnson, T. D. (2004), Online student ratings of instruction [Special issue].
New Directions for Teaching and Learning, 96. Hoboken, NJ: Jossey-Bass.
Stronge, J. H. (1997), Improving schools through teacher evaluation. In J. H. Stronge, Evaluatingteaching: A guide to current thinking and best practice, (pp. 1-23). Thousand Oaks, CA:
Corwin Press.
Theall, M., & Franklin, J. (2000), Creating responsive student ratings systems to improve
evaluation practice. In K. E. Ryan, Evaluating teaching in higher education: A vision for
the future [Special issue]. New Directions for Teaching and Learning, 83 (pp. 95-107). San
Francisco: Jossey-Bass.
Taylor, C., Jones, A., Shindler, J., & Cadenas, H. (2004), "Architect and Steward: Shaping a
Vision of Learning". Examining the Role of the Principal in the Immersion of New
Teachers into Existing Urban School Climates. Charter College of Education, California
State University, Los Angeles.

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  Wachtel, H. K. (1998), Student evaluation of college teaching effectiveness: a brief review.
Assessment and Evaluation in Higher Education, 23(2), 191-210.
Wilson, V. (1997), Focus groups: a useful qualitative method for educational research? British
Educational Research Journal, 23(2), 209-224.
Zabaleta, F. (2007), The use and misuse of student evaluation of teaching. Teaching in Higher
Education, 12, 55-76.

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  Appendix
Online questionnaire given to students, academic year 2004 and 2005. Original questions in
Chinese with our personal translation. The questions were designed by the university andapproved by the Ministry of Education in Taiwan.
1. 教師對課程有充分的準備
Teachers are well prepared for the course
2. 教師準備的教材內容適當
Teachers prepare appropriate teaching materials
3. 教師講解清楚易於吸收Teachers explain clearly, make the content easy to assimilate
4. 教師對學生提出的問題有積極回應
Teachers respond positively to the issues raised by students
5.教師能提高您對本課程的學習興趣
Teachers can increase your interest in this course
6.教師對本課程具有授課熱誠Teachers show enthusiasm for the course taught
7.教師不缺課，不無故遲到或早退
Teachers are not absent, late or leave early without a (good) reason
8.您從本課程收穫很多You learned a lot from the course
9.教師有依照事先安排的綱要或進度授課
Teachers teach in accordance with pre-arranged lectures outline or progress
10.教師考核學生成績十分公平
Teachers give a very fair assessment of student achievement
	
  

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Volume 2 - Issue 1 - Winter	  To What Degree are Undergraduate Students Using
their Personal Computers to Support their Daily Study
Practices?
KwongNui Sim, Russell Butson

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  Abstract

This scoping study examines the degree to which twenty two undergraduate students used theirpersonal computers to support their academic study. The students were selected based on their
responses to a questionnaire aimed at gauging their degree of computer skill. Computer activity
data was harvested from the personal computers of eighteen students and video footage of thestudents personal study sessions was gathered from a further four students. Three core themes
emerged: (1) Academic Use vs. Non-academic Use; (2) Computer Orientated vs. Paper
Orientated; and (3) Self-reports of Practice vs. Actual Practice. Overall results suggested threefundamental behaviors relating to technology use: 1] they were more likely to engage in nonacademic work than academic work on their personal computer; 2] they were more inclined touse paper-based approaches compared to digital ones despite the high rate of personal computer
ownership and internet access; 3] there was a disparity between students’ self-reports of thedegree to which they used their personal computers for academic purposes (high) and nonacademic purposes (low) to what we found from computer logs which showed academic use as
low and non-academic use as high. From these results we conclude that for this group of students
computers played an important role in their day to day lives, but the degree to which they wereused in their academic study was lower than we had expected.

Keywords: Student learning; E-learning; Higher education; E-literacy; Student study habits.

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Volume 2 - Issue 1 - Winter	
  Introduction
As universities become more digital and computer technologies become increasingly
sophisticated and ubiquitous, understanding the extent to which students integrate thesetechnologies into their daily study practice is essential if we wish to understand their future
potential to advance learning (Butson and Thomson, 2011). Nevertheless, there has been little
research to date that explores students’ first-hand experiences of using new technologies tosupport their academic practice (Sharpe et al., 2005). For example, the degree to which students
today can be regarded as competent computer users in terms of utilising academic software inorder to excel in their studies is hazy. While the literature shows an increasing number ofundergraduate students own a computer and have a broadband connection (Aspden and Thorpe,
2009, Guidry and BrckaLorenz, 2010, Smith and Caruso, 2010, Dahlstrom, 2011), it is unclear towhat extent these personal computers are utilised in the academic study practices of students. The
typical assumption is that these ‘digital natives’ (Prensky, 2001) have a high level of computer
literacy and are therefore likely to utilise their laptops to support their learning in advanced ways.
It is also worth noting that much of the research we found into student use of computer
technologies has been based on surveys and interviews (perception data). By this we mean
students reporting on what they believe they do through post-event recollection. The primaryendeavor in regard to this investigation was to explore the use of datasets other than post-event
recollections. This would require us to locate data collection as close as possible to the students’
daily studying practices. Two approaches were explored and subsequently used: 1) computer
usage data was extracted from the student laptops (Computer Activity Data) and 2) student’s usedvideo cameras to film their study sessions within their home study space (Cohort Behavioral
Data). To ascertain if there was a difference between perception data and naturally occurring dataa traditional self-report questionnaire was included.
Prior to the commencement of the study, three core areas of inquiry were established:
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•

The degree to which students utilised their personal computers for academic purposes ascompared with non-academic use,•

The extent to which computer use had been adopted over traditional paper-based
approaches,•

The degree to which student self-reports (post-event recollections) align with data captureof their actual practice.
MethodGiven the exploratory nature of the study and the researchers social constructivist orientation, thestudy adopted the interpretive, naturalist enquiry approach of Guba and Lincoln (1989), and theanalysis approach of Constructivist Grounded Theory of Kathy Charmaz (2006). This approach
unpins the decision for the selection of a small number within a particular context to understandtheir experiences rather than a focus on generalisable findings. Two separate cohort groups wereused from conveyance and not for any particular purpose, one capturing usage data from their
computers (Computer Activity Data) and the other filming their home-based study practices(Cohort Behavioral Data) with considerably more input being required by this cohort. All
participants were undergraduates and all completed the Self-report survey. The Self-report Data
was gathered through a short questionnaire that ascertained the student perceptions of theirdegree of computer use. The top scoring students, those that self-reported as skilled computer
uses, were invited to participate in the study.
The Computer Activity Data: Eighteen students who self-reported as being skilled computer
users were selected for this part of the study. A software programme (ManicTime) was installedon their personal computers. This software captured usage information on applications used,websites visited, documents accessed and the associated times and durations involved. The data
was gathered over the duration of their first six studying weeks in semester one 2012. We wereconfident that this naturally-occurring activity data was going to yield rich information that was
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  going to be very different to the traditional perception data. It would allow us to review theapplications used, documents accessed, websites visited and periods of use. However, thenumerical nature of this data meant it couldn’t tell us much about the context in which these
digital activities were occurring. It was envisaged that the video capture that the students weregenerating of their home-based study practice would help situate the Computer Activity Data.
Cohort Behavioural Data: A second cohort consisted of four third year undergraduate students
who also rated themselves as being skilled computer users. Each student was asked to capture aseries of short video clips of their home study practices over a three month period. Over twelve
hours of video footage resulted. Our interest was on the context(s): to what extent did theparticipants integrate and interact with computer technology in their daily undergraduate study
habits.
These two datasets represented a mixture of students’ actual computer practices (Computer
Activity Data) and behaviours associated with study practice (Cohort Behavioural Data). While
Computer Activity Data captured what students used their computers for, Cohort Behavioural
Data was used to elicit data on how students used their computers within their study routines, andit gave us an insight into the context. Through these two datasets we hoped to gain some insight
into what students used their computers for.
Findings
Guided by our three core areas of interest, an analysis of the three data sets (Self-reported skill
level, Computer Activity Data, Cohort Behavioral Data) using the coding processes of groundedtheory resulted in three themes:-

Academic Use versus Non-academic Use-

Computer Orientated versus Paper Orientated-Self-Reports versus Actual Practice

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  Academic Use vs. Non-academic Use: From the Computer Activity Data (computer logs) weanalyzed the top three software applications, documents used and web sites accessed. The mostobvious classification was the academic or non-academic use. Academic refers to software,
documents or web services that were related to the participants’ academic study. Non-academic
includes all other uses, such as banking, entertainment sites, Facebook groups, etc. As shown intable 1 the computer logs revealed much higher non-academic use compared with academic use.
Table 1:
Computer log data: breakdown between academic vs. non-academic use.
Percentage (%)
No.

Academic

Non-Academic

10
20
90

90
80
10

of Students
15
2
1

For clarity values have been rounded to the nearest whole number

Paper Orientated vs. Computer Orientated: From the Cohort Behavioral Data, we analyzed thefour participants’ behaviors from their self-created 12 hours of filming. Coding the students
activity while they were studying revealed a clear distinction between behaviors that were paperorientated and behaviors that were computer orientated. By paper orientated we are referring torepetitive behaviors that did not include the use of their computer. By computer orientatedbehavior we are referring to repetitive behaviors that did include the use of their computer. As
shown in table 2 we found these students engaged in more paper-based activities during study
sessions than computer-based.

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  Table 2:
Percentages for comparison of paper orientated vs. computer orientated activities

Participants
12
34Percentage (%)
Paper
Computer
Orientated
Orientated
14
66
56
19
92
0
17
57

Note: The percentages do not distinguish between academic and nonacademic activities and for clarity values have been rounded to the nearest
whole number

Self-Reports of Practice vs. Actual Practice: We found a considerable difference between what
students thought they used their computers for from what they actually used them for. While theself-report questionnaire indicated students believed they used their computers mainly foracademic purposes the results from the computer logs suggested a very different story. As shownin Figure 1 the data shows students generally believed they used their computers more foracademic purposes rather than non-academic (red). However, the computer logs revealed that 17
out of 18 of the students used their computers significantly more for non-academic purposes thanfor academic.

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  This was reinforced from the Cohort Behavioral Data where students spent considerable time
during their home-based study sessions on a variety of applications not associated with academic
practice. As shown in Figure 2 below, this student often played around with music software (asin the illustration on the left) and regularly checked her emails (as in the illustration on the right),
while others had Facebook permanently on screen.

Figure 2: Non-academic work with technology8

The Cohort Behavioral Data also revealed that when these students did use their computers foracademic purposes they exhibited a more limited degree of proficiency than we were expecting.
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
8
Consent was granted by participants for the use of the film files for research purpose.
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Volume 2 - Issue 1 - Winter	  For example, we had footage of a student manually adding references for an assignment. The
footage also captured her saying, “I’m just doing my psychology assignment … first of all I’m
going to compile a list of references just using Microsoft Word …” She continued at this task forsome time, repeatedly deleting large section when an error was made. She also commented about
her expectations of the process before she started typing, “This is probably going to take meages”. In the process, she said, “This is really time consuming”; “This is boring”; “God that is soannoying”; and “I’ve done this so many times I’ve just memorized reference lists”. The footage
duration showed that she took more than one hour to add one page of references. Whenquestioned later about her knowledge of software programs that automate much of this process,she replied she had heard of these but hadn’t used them.
Findings
As mentioned earlier, the core findings contributed to the development of three main themes,
namely, Academic Use vs. Non-academic Use, Paper Orientated vs. Computer Orientated, andSelf-Reports vs. Actual Practice.
All participants stated in the self-report questionnaire that computers played an important role intheir undergraduate academic practice. This is not surprising given the rapid increase in theownership of personal computers over the past five years by students enrolled in higher education(Aspden and Thorpe, 2009, Guidry and BrckaLorenz, 2010, Smith and Caruso, 2010, Dahlstrom,2011). It seems reasonable then to assume that these students would be leveraging the benefits
that computer technologies afford. However, our results did not support this. In fact we found thedominant use of their personal computers was for socialising (social networks such as Facebook
and email), personal web services (auction sites and online banking) and entertainment (YouTube,music and movies). This was followed closely by web services such as retail, news, health,television, movies, information on pubs, air tickets, etc. Academic use on the other hand was

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  generally limited. This was a surprise given the growth of study resources such as PowerPoint
slides, academic articles, and assignment guidelines being distributed in digital formats.

An analysis of the Cohort Behavioral Data (video footage) revealed that the participants exhibited
only rudimentary awareness and skills concerning the capabilities of their computers to enhancetheir academic work (e.g., file management, bibliographies, planning, word-processing, databases,
and analytical packages). In fact, the students in this study were completely unaware of the many
academic-related software applications either on their computers or available throughapplications offered by the institution such as bibliography programmes (i.e., Endnote, Zotera,
Mendley), planning programmes (e.g., Outlook, Evernote, OneNote), analysis packages (i.e.,
SPSS, NVivo, and MATLAB), and more generally (e.g., spread sheets, graphics software,
programmes to support PDF annotation).

Given the wide-ranging conscience in the literature on student’s computer savviness, we weretaken aback by the degree to which these students were using paper-based approaches. It was
clearly the preferred means of engagement regarding study. While the common format for course
materials for these students was text based and digital (i.e., Microsoft Word, PowerPoint andportable document formats), all engaged in extensive indiscriminate printing of these materials.
We were puzzled by this behaviour. We had assumed these students would exhibit high levels ofdigital orientated behaviour, instead we found they preferred to print material and apply
traditional study techniques associated with paper-based form. We wondered if this was due to alack of awareness of annotation and mark-up facilities, and the storage and retrieval capabilities
that digital formats offer or did it signal something deeper about student’s preference to use
paper-based approaches.
It is interesting to speculate whether students’ preference for paper-based approaches is the lackof skill/knowledge with the technology or whether it could be due to a dependence on paper167	
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  based approaches inherent in higher education. It seems reasonable to assume that the way inwhich an institution embraces and implements technology is going to have a bearing on the way
in which students will engage with technology in their higher education learning. Althoughstudents are comfortable with technology and see it as integral to higher education (Dahlstrom,2011), they may expect that teaching staff will model the academic use of technology (Smith andCaruso, 2010).
Given the dominance of paper-based approaches it is not surprising that the Cohort Behavioural
Data (video footage) showed that students were very reliant on their printers. In fact you could
say that for academic use the computer was of little use without an attached printer. From thevideo footage it appeared that the computer was simply a device that was used to accessdocuments that the student then printed and stored in ring binders. Incidentally, all used ringbinders to store and categorise their printed resources.
Finally, it is worth noting that much of the literature we found on the role of computer technology
in supporting learning in higher education was based on perception data. Part of this study was toexplore the validity of this approach by examining whether there is a difference between students’
perceptions and actual practice in relation to their computer use and their computer literacy. The
results from Computer Activity Data suggest that there is considerable difference.

Studies employing perception data are typically optimistic regarding student dependency on
personal computers for supporting study. A vast array of studies claim that computer technology
now plays a significant role in supporting undergraduate education (Aspden and Thorpe, 2009,
Dahlstrom, 2011, Guidry and BrckaLorenz, 2010, Smith and Caruso, 2010) and that thisincreased use is resulting in learning efficiencies for students (Smith et al., 2009). There is adegree of acceptance from much of this material that presupposes students “use technology inacademia to give them access to resources and progress reports, make them more efficient as
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  students, facilitate connecting with others, and make learning more relevant and engaging”(Dahlstrom, 2011).
The naturally-occurring practice data captured in this study did not support these claims. Why
were our findings different? When we looked only at the perception data (self-reportquestionnaire) gathered from our participants we found the conventional pattern appearing. The
difference only occurs when we accessed the naturally occurring student activity. It gave us away of ‘seeing’ what students did (and did not do) rather than what they said they did or did not
do. As Starr and Fernandez (2007) noted, self-reported behaviours can be quite inaccurate fordescribing practice and thus we believe there are grounds to question the veracity of studies thatuse post-event capture to represent actual practice. Furthermore, participants’ “perspectives inaction” (records of behaviour) and/or “perspectives of action” (accounts of behaviour) (Belk andKozinets, 2005, p. 132) should be taken into consideration when studying practice.
In summary
The aim of this study was to explore third year undergraduate students’ practice of using theirpersonal computers in their independent study sessions. While the findings from this study are
specific to the cohort groups involved and are therefore not generalisable, the results do offer new
understandings and insights into the use of computers to support undergraduate study. From thisstudy, students were found to be active computer users and highly computer literate in nonacademic use. Their academic use, in terms of practice and literacy, however, was low andlimited. Students were also found to favour working in a paper-based manner rather than a digitalone. Finally we found a clear difference in outcomes from perception data to naturally occurringdata. We believe this finding brings into question the current dependence on perception data toreveal authentic, situated practice.

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Volume 2 - Issue 1 - Winter	  We are confident that this study will promote a deeper conversation about the role of technology
in higher education and the use students currently make of personal computers/devices to support
their study. Perhaps more research on larger and more diverse groups of students could beconsidered. Additionally, authentic and situated behavioural data should be employed inresearching technology use. The difference found between perception and practice data signals
the need for a substantial shift in the way we understand and gather data in this emerging field.
Acknowledgements
To Carla Thomson, University of Otago, for her contribution to the Cohort Behavioral Data.
The support and generosity of Dr Sarah Stein (Senior Lecturer at HEDC), without which thepresentation at The European Conference on Technology in the Classroom (ECTC) in Brighton,
UK on 11th-14th July 2013 could not have been undertaken.

References
Aspen, E. J., & Thorpe, L. (2009), "Where do you learn?": Tweeting to inform learning spacedevelopment. [Online]. Educause Quarterly Educause. Retrieved February 04, 2014, fromhttp://www.educause.edu/ero/article/where-do-you-learn-tweeting-inform-learning-spacedevelopment
Belk, R. W., & Kozinets, R. V. (2005), Videography in marketing and consumer research.
Qualitative Market Research, 8, 128-141.
Butson, R., & Thomson, C. (2011), Reflections on the use of autovideography in anundergraduate education context. Journal of Research Practice, 7, 1-10.
Charmaz, K. (2006), Constructing grounded theory: A practical guide through qualitative
analysis, Thousand Oaks, CA, Sage.
Dahlstrom, E. (2011), Connecting student data from ECAR and CDS. Educause, 1-7.
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  Guba, E. G., & Lincoln, Y. S. (1989), Fourth generation evaluation, Newbury Park, Ca, Sage.
Guidry, K., & Brckalorenz, A. (2010), A comparison of student and faculty academic technologyuseacrossdisciplines.

Retrieved

February

04,

2014,

from

http://www.educause.edu/ero/article/comparison-student-and-faculty-academictechnology-use-across-disciplines
Prensky, M. (2001), Digital Natives, Digital Immigrants. On the Horizon, 9, 1-6.
Sharpe, R., Benfield, G., Lessner, E., & Decicco, E. (2005), Final report: Scoping study for thepedagogy strand of the JISC learning programme.
Smith, S. D., & Caruso, J. B. (2010), The ECAR study of undergraduateutudents and information
technology, 2010 Educause. October 2010 ed.
Smith, S. D., Salaway, G., & Caruso, J. B. (2009), The ECAR study of undergraduate students
and information technology, 2009 Educause [Online], 6. Retrieved February 04, 2014,
from http://net.educause.edu/ir/library/pdf/ers0906/rs/ERS0906w.pdf
Starr, R. G., & Fernandez, K. V. (2007), The Mindcam methodology: Perceiving through thenative's eye. Qualitative Market Research: An International Journal, 10, 168-182.

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  Exploring Major Predictors of Student
Satisfaction: An Input towards a
Learning-Friendly School Environment.
Marilyn L. Balmeo, Allan B. Castro, Kristine Joy T. Caplis,
Kizzylenn N. Camba, Jahziel Gillian M. Cruz, Marion G. Orap,and Joroma Sol T. Cabutotan

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  Abstract

The study sought to determine the perceived level of importance and perceived level ofsatisfaction of college students on 16 areas of student service commonly provided in a tertiary
education setting within any university as prescribed and observed by local and international
standards of tertiary education.
Each area was tested to determine the existence of a significant relationship between themeasured response by respondents on their perceived level of importance and perceived level ofsatisfaction. The existence of a significant relationship between the two variables indicates thatthe given area of the learning environment is a major predictor towards student satisfaction. Item
analysis was also performed on each area of the learning environment to determine specificindicators of student satisfaction.
The results of this research serves as a benchmark to any university [with similar status as the
locale of the study] in identifying particular areas of the learning environment that are crucial indetermining student satisfaction and must be focus of university maintenance and development so
as to achieve a learner-friendly school environment.
The research was conducted with 399 students enrolled in Saint Louis University distributed inproportion to the population distribution of students in the different colleges within the said
University.

Keywords: Student satisfaction; Perceived level of importance; Student services.

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  Introduction
The 21st Century Educational Goals suggest a reconstruction on the different educational
principles which to a degree of urgency include citizenship preparation, inclusion, and thecreation of an optimum learning environment (Laguardia and Pearl, 2009).
The degree of citizenship preparation given by a learning institution to its students can bemeasured by the performance of a student outside the school setting. While inclusion and the typeof learning environment by educational institutions are measured in the attitude and services an
educational institution affords for its students inside the school.
Inclusion is defined as the approach whereby students with disabilities receive all instruction in a
general education classroom while support services, like specialists, are expected to come to thestudent (Hardman, Drew & Egan, 2006).
The Learning Environment, which serves as the subject of this research, pertains to any formal or
non-formal setting where students gain knowledge and skills to be used in their learning(UNESCO). Such may take form of schools, colleges, cultural centers, hobby centers and social
clubs. It also includes the buildings, infrastructures, machineries, the quality of service, and theefficiency of workforce inside an educational institution.
Assessing a learner-friendly school environment
The learning environment is typically composed of 4 elements: teacher-student relationship,
atmosphere of inclusion, school facilities and services, and school departments and bureaucracies(Coll and Draves, 2009; Laguardia and Pearl, 2009; Stebleton, Huesman and Kuzhabekova, 2010;
Roberts and Styron, 2009; Johnson, 1997; Umbach and Porter, 2002).
On the other hand, to qualify a learner-friendly school environment, there must be the existenceof an effective interplay of the 4 elements of the learning environment (Gulosino and Lubienski,
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Volume 2 - Issue 1 - Winter	  2011). This means that, aside from the existence of the prescribed student services, student
services must operate in high-efficiency.
In the Philippines, the normative practice by which the efficiency of the learning environment ofcolleges and universities is assessed through the quantity of national citations and accreditations
an institution garner, and the civil service examination passing rates by programs within a certain
educational institution (Corpus, 2003).
However, these traditional ways of assessing the learning environment are futile as they disregard
the way the learning environment operates in normal circumstances. The use of accrediting
agencies, civil service examinations and categorical citations allows for ample preparation by
universities to give a good impression and attain high scores in such events. This kind of scenario
is a common practice in Philippine Colleges and Universities.
Although efforts on measuring the efficiency of a learning environment are performed, such
efforts are either focused on measuring the areas of instruction and school facilities. This meansthat full-scale assessment of the quality of the learning environment is commonly absent.
To address such problem, it is always advocated that students should also be able to have a say on
the manner the learning environment operates on all areas to have an honest assessment of thequality of such. This is so since students have a full-knowledge on the learning environment
given their direct interaction with such. One of the most common standards used by students inevaluating the learning environment is their satisfaction towards it.

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  Theoretical and conceptual framework of satisfaction
The theory adopted in this research to explain how major predictors of satisfaction aredetermined is the Stimulus-Organism-Response theory. The S-O-R Theory states that for any
stimulus, an individual is expected to produce a certain response. The degree of the response isdetermined in accordance to the organism variables upheld by a person such as cognition,
emotion, knowledge etc. (Algharabat, 2007).
In parallelism to the act of assessing the learning environment, the areas of service, and its
specific indicators, is determined as the stimulus while the level of satisfaction to each area ofservice is seen as a [possible] response by students. The organism variable can be seen of asignificant role when one tries to make a sense out of the satisfaction response by students to theareas of the learning environment.
In this research, the attempt of determining major predictors of student satisfaction used theorganism/student variable of perceived level of importance for each area of the learning
environment. In concept, the existence of a direct relationship between the perceived level ofimportance and level of satisfaction by students on the areas of the learning environment isindicative to such area as a major predictor to student satisfaction.
By knowing the areas of the learning environment that serves as major indicators to student
satisfaction, the school will be able to know what areas of the learning environment can promotea learner-friendly environment.
Purpose Statement
This study aims to identify the major predictors affecting student satisfaction along the areas ofthe learning environment, particularly its locale that is Saint Louis University.

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  Knowledge on the specific indicators of learner-friendly environment allows for any university
administration or management to determine which area of the learning environment needs crucial
focus to sustain student satisfaction. It also lessens the non-strategic spending by schools bydetermining what areas really need improvement.
Over-all, this serves as a guide on how to create a learner-friendly environment by identifying
specific areas of the learning environment that highly affects student satisfaction. Needless to say,satisfaction of the students translates to the friendliness of the school.
Problem Statement
Since the research aims in determining major predictors of student satisfaction by using the levelof satisfaction and perceived level of importance on the student services by the students of aschool environment, the essential questions of this research are identified as:•What is the perceived level of importance of students along the sixteen identified areas of thelearning environment?
•What is the level of students’ level of satisfaction along the sixteen identified areas of thelearning environment?
•Is there a significant relationship in the students’ perceived level of importance and level ofsatisfaction along the sixteen identified areas of the learning environment?
Extension to these questions is the task of identifying specific indicators for each area of thelearning environment that serve as a major predictor to student satisfaction.

Method

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  Locale of the study
This research, centering on knowing the variables that determine a leaner-friendly school
environment involved the assessment of all the 9 colleges present at Saint Louis University as its
study locale.
Respondents included the population of Saint Louis University in the 3rd, 4th and 5th year levels.
Respondents were limited to such because of the assumption that students on these year levels
have a full knowledge and a maximum interaction with all the areas of the learning environment
given their years of stay in the university
Data gathering method
Population sampling was used to get the total number of respondents as the representative figureof the entire population. The calculated number of respondent totals to 399 students distributed inproportion to each college of the university.
The administration of questionnaires was held using random floating of questionnaires incooperation with the respective deans of each college.
Data collection tool
A questionnaire was used to gather data. The questionnaire is a three-column survey
questionnaire that required student respondents to rate their perceived level of importance andtheir level of satisfaction from a scale of 1 to 5.
There are 267 items containedin the questionnaire which were distributed among the 16

different services/facilities which were identified as Instruction (22 items), Admission (10 items),
Guidance Office (13 items), Accounting Office (13 items), Dean’s Office (20 items), Bookstore(14 items), Library (30 items), Food Services (15 items), Computer Laboratory (20 items),
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  Science Laboratory (26 items), Students Affairs Office (16 items), Campus Security (10 items),
Janitorial Services (10 items), Audio-Visual Rooms (8 items) and Over-all Facilities (30 items).
The areas of the learning environment, and their corresponding items/specific indicators, were
determined in accordance to the generally existing areas of the learning environment existing inmost tertiary education institutions nationally and internationally.
Statistical tools
Statistical formulae that were used include the Weighted Mean (WM) and Regression Analysis(r).
In answering problem number 1 and problem number 2, the general weighted mean (WM) of
items were used to which results were interpreted in the following manner: 1.00-1.74: Not
Important (NI)/ Dissatisfied (D), 1.75-2.49: Slightly Important (SI)/Slightly Satisfied (SS), 2.503.24 : Important (I)/ Satisfied (S) and 3.25-4.00: Very Important (VI)/Highly Satisfied (HS).
In treating question number 3, Regression Analysis (r) was used to derive the possibility of an
existing relationship between the items and the significance of the relationship was validated byusing a P-value of .05.
After deriving the existence of relationship between areas, item analysis was conducted using
Regression Analysis (r) to identify items that serve as major predictors of student satisfaction inline with student services.
Interviews
Also, since this research concerns students’ perspective of the learning environment, perceptions
by the respondents of this research were also incorporated in interpreting results.
Research limitations
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Volume 2 - Issue 1 - Winter	  The results, and even the suggestions, in this research may prove irrelevant to some schools that
may uphold a different learning environment as compared to the research’s locale.
This research only took into full account the areas of the learning environment present in the
research’s locale. Hence, the results of this research may be applicable to educational institutions
with a similar profile as Saint Louis University.
What is the perceived level of importance of students along the different services of the school?
In the given table, it can be seen that all of the areas of the learning environment were considered
as “very important” by respondents. Results suggest that all the given areas of the learning
environment play an important role the development of college students.
This is furthered by a student interview stating that the presence of such areas of the learning
environment allows for students to address their personal needs in the varying aspects of being a
student—psychological needs, health needs, academic assistance support needs etc.
In a nutshell, the importance of such areas of learning environment only prove that holistic
development of students can only be made possible by the existence of facilities, services,
program supports etc. that are directly present to cater to such needs of students.
What is the level of satisfaction of students along the different services of the school?
From the table below, it can be seen that respondents expressed varying satisfaction rating foreach area.

Results and discussions
Areas of the Learning
EnvironmentA) University InstructionB) University Admission

Level of Importance
OWM
DE
3.63
VI
3.50
VI
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Level of Satisfaction
OWM
DE
2.72
S
2.83
S

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Volume 2 - Issue 1 - Winter	  C) Guidance Office
3.57D) Accounting Office
3.59E) Dean’s Office
3.62F) Bookstore
3.53G) Library
3.59
H) Canteen Services
3.62I) Computer Laboratory
3.58
J) Science Laboratory
3.44K) Student Affairs Office
3.57L) Campus Security
3.64M) Clinic
3.57
N) Janitorial Services
3.59O) Audiovisual Services
3.63P) Overall Campus Facilities
3.58* r value is significant; P-value ≤..05

VI
VI
VI
VI
VI
VI
VI
VI
VI
VI
VI
VI
VI
VI

2.71
2.60
2.85
2.63
2.65
2.41
2.58
2.61
2.59
2.69
2.70
2.81
2.47
2.49

S
S
S
S
S
SS
S
S
S
S
S
S
SS
SS

.103*
.003
.074
.047
.091
.027
.122*
.380*
.062
.150*
.109*
.101*
.023
.013

Table: A table presenting the score results and corresponding interpretation on the respondents perceived
level of importance and level of satisfaction on the areas of the learning environment and the existence ofsignificant relationship between the two.

It can be seen that there are three areas which garnered a “Slightly Satisfied” response. It includes
the Canteen Services, Audiovisual Services and Overall Facilities of the University. Reasons
given by respondents for their rating for each area includes a) canteens in the university don’t
consider the suggestions of students in coming up with the daily menu, b) there are shortages ofunits and rooms for audiovisual services and c) miscellaneous services like elevators, online
enrollment and vending machines are not present within the university premises.

Also, students identified that areas that garnered a plain satisfied response are due commonly to a)
the absence of such areas of learning environment on all or some of the campuses, b) the use ofout-dated materials and c) some issues concerning the approachability of staffs for certain areas.

Clearly, all the areas of the learning environment require constant improvement, monitoring, andmaintenance to ensure the increase of student satisfaction response to such. Is there a significant
relationship in the respondent’s perceived level of satisfaction and their level of importance forthe areas of the learning environment?

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Volume 2 - Issue 1 - Winter	  The importance of knowing if a significant relationship exists between the level of satisfaction
and perceived level of importance by students is to determine the major predictors of student
satisfaction. By this, areas of the learning environment that highly contributes to student
satisfaction can be identified, thus, allowing educational institutions to determine the areas thatshould be a) maintained to sustain a learner-friendly school environment and b) that should be
improved to achieve a full learner-friendly school environment

In the given table, there are only 6 out of the 16 areas of the learning environment which wereidentified with an existing significant relationship between respondents’ perceived level ofimportance and level of satisfaction. Hence, these areas are seen as major predictors to student
satisfaction. These include the guidance office, the computer laboratory, the science laboratory,
the campus security, the clinic services and the janitorial services.

In an item analysis, it was found out that in each area with existing significant relationship,
specific indicators per area manage to qualify as specific predictors of student satisfaction.

Firstly, for the area of guidance services, the major predictors of satisfaction includes a) the
presence of extension services like scholarships, exchange student programs and student
organizational networking, b) the issuance of printed results of tests and c) the availability of staff
during working hours.

Secondly, for the computer laboratory area, respondents identified a) the adherence of computerlaboratory instructors to school policies regarding computer use and ethics in accessing
information, b) the giving of manuals on rules and policies regarding computer use andreservation and c) the presence of monitoring and inspection on laboratory facilities wereconsidered as the major indicators of satisfaction in the area of computer laboratory services.

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Volume 2 - Issue 1 - Winter	
  Thirdly, for science laboratory services, a) the conduct of experiments that are only authorized by
the school, b) the proper explanation of written laboratory directions to student before executionof any activity and c) the presence of enough water supplies and faucets in the laboratory were
determined as the major indicators of student satisfaction.

Fourthly, for the area of campus security, indicators that serve as major predictors to student
satisfaction include the assurance that security guards are a) equipped with protective skills, b)
well-groomed and c) well-disciplined.

Fifthly, major indicators of student satisfaction on the area of clinic services include a) thesterilization and cleaning of clinical equipments, b) the availability of doctors in the clinic at
anytime of the day and c) the approachability of staff.

Lastly, for the area of janitorial services, a) the friendliness, honesty and approachability ofjanitors, b) the presence of cleaning materials and tools inside the classroom and c) the presenceof janitors in all areas of the school were identified as major indicators to student satisfaction.

In a close analysis, areas and specific indicators that serve as major predictors of student
satisfaction includes those that are considered most crucial to promote student safety andclassroom order (like that of the computer and science laboratories), to promote a pleasing school
environment (like that of the security and janitorial services) and to cater to the student personalneeds like health and wellness (like that of the guidance and clinic services).

The simple interpretation to such result is this: among the 16 areas of the learning environment
presented, the most crucial areas that predict student satisfaction only include 6 areas of thelearning environment. Such result means that 6 offices are only seen as predictors to a learnerfriendly environment (of course, as per the indicators provided in the research questionnaire).
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Volume 2 - Issue 1 - Winter	
  This implies that the core focus of any learning institution for development and maintenance ofthe learning environment should be directed towards the identified six areas of the learning
environment. Such is so as to lessen the unstrategic use of resources in trying to improve all areasof the learning environment while achieving less in meeting student satisfaction.

In conclusion, to achieve maximum learner-friendly environment while using less resources,
educational institutions must focus on developing the areas, and the specific indicators per area,of the learning environment that serves as major predictors of student satisfaction.

Result limitations

The result of the hypothesis on determining the major predictors of satisfaction was dependent on
the values upheld by the respondents of the research. Therefore, areas of the learning
environment which are deemed as major predictors of student satisfaction can vary from one
school to another. Also, results cannot be automatically applied to any tertiary institution due tothe difference on functions observed for each area of the learning environment. The researchrecognizes that each institution upholds additional/specialized roles and transaction orders foreach area.

Suggestion and recommendations

What suggested programs should be implemented to further enhance the university’s student
services?

A) Creation of a manual on the areas of the learning environment

In any tertiary education institution, it would be student-friendly if the school issues a manual
identifying the various areas of the learning environment and the specific services provided in
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Volume 2 - Issue 1 - Winter	  each area of the learning environment. Such manual would help students to be informed more on
the existing programs and student support systems to intensify the awareness of students to suchand to maximize the use of such areas of the learning environment by students.

B) Survey on major predictors of the learning environment

This includes the simple act of constructing a data collection tool that would measure theperceived level of importance and level of satisfaction of students on the learning environment
they are situated. Following the same methods of this research, educational institutions will beable to pin point which areas of the learning environment are most important and are in need of adegree of maintenance and development by the institution’s management.

What are some recommendations by researchers related to the research?

The researchers recommend for future researchers of the same topic to make a cross-sectional
study along various institutions to determine whether there exists a significant difference in theareas of the learning environment that are seen as major predictors to student satisfaction.

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Volume 2 - Issue 1 - Winter	
  Conclusion

From the research, it can be concluded that not all areas of the learning environment areconsidered as major predictors of the student satisfaction.

Although, this doesn’t mean that no efforts or whatsoever should be afforded to improve thoseareas which are not considered as major predictors of student satisfaction.

Through identifying the major predictors of satisfaction, it allows university administration todetermine specific areas that require much focus for maintenance and development.

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Volume 2 - Issue 1 - Winter	
  References
Algharabat, R. (2007), The role of the stimulus-organism-response (s-o-r) model in explaining
effects of image interactivity technology (IIT) on consumer responses. Brunel University
Journal, PhD Doctoral Symposium 2007, Paper no. 28. Retrieved February 04, 2014 fromhttp://www.brunel.ac.uk/__data/assets/file/0004/90535/phdSimp2007RaedAlgharabat.pdf
Coll, J. E., & Draves, P. (2008), Traditional age students: worldviews and satisfaction withadvising a homogeneous study of student and advisors. College Student Affairs Journal,
27(2), 215-223.
Corpus, M. T. (2003), Philippine perspectives of the Philippine quality assurance system. Journalof Philippine Higher Education Quality Assurance, 1(1), 1-7.
Gulosino, C., & Lubienski, C. (2011), School's strategic responses to competition in segregatedurban areas: patterns in school locations in metropolitan detroit. Educational Policy
Analysis Archives 19(13).
Hardman, M. L., Drew, C. J., & Egan, M. W. (2006), Human exceptionality school, communityand family. (8th ed.). USA: Pearson Publishing House.
Johnson, R. (1997), Equal access to quality school facilities. Intercultural Development Research
Association.

Retrieved

February

04,

2014

from

http://www.idra.org/IDRA_Newsletter/March_1997_Coordination_of_Funds_and_Programs/Equal_Access_to_Quality_School_Facilities/
Laguardia, A., & Pearl, A. (2009), Necessary educational reform for the 21st century: The futureof public schools in our democracy. Urban Review: Issues ad Ideas in Public Education,
41(4), 352-368. Doi: 10.1007/s11256-008-0115-9

188	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Roberts, J., & Styron, R. Jr. (2009), Student satisfaction and persistence: factors to student
retention. Research in Higher Education Journal, 1-18. Retrieved February 04, 2014
http://www.aabri.com/manuscripts/09321.pdf
Stebleton, M. J., Huesman, R. L. Jr., & Kuzhabekova, A. (2010), Do I belong here? Exploring
immigrantcollegestudent

responses

on

the

SERU

surveysenseofbelongingness/satisfaction factor. CSHE Research and Occasional Paper Series 13.10.
Berkeley, CA: University of California-Berkeley, Center for Studies in Higher Education.
Retrieved

February

04,

2014,

from

http://www.oir.umn.edu/static/papers/NASPA_2010/2009_SERU_Symposium_immigrant_
study_presentation.pdf
Umbach, P. D., & Porter, S. R. (2001), How do academic departments impact student satisfaction?
Understanding the contextual effects of departments. Research on Higher Education, 43(2),209-231.
United Nations Educational, Scientific and Cultural Organization (2009), Embracing diversity:
Toolkit for creating inclusive, learning-friendly environment. Bangkok, Thailand: Author.
Retrieved

February04,

http://unesdoc.unesco.org/images/0018/001829/182975e.pdf

189	
  
	
  

2014,

from

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Additional biography
Archambault, L., Hartwell, L., Frisk, E. & Hale, A. (2012). Developing Sustainability Literacy
among Preservice Teachers Through Web-based Learning. In Proceedings of Society for
Information Technology & Teacher Education International Conference 2012 (pp. 83-87).
Chesapeake, Virginia: AACE Publishing, Inc.
Barth, M. E., & Schipper, K. (2008), Financial reporting transparency. Journal of Accounting,
Auditing and Finance Spring, 23(2). Rochester, New York: SSRN.
Bocala, C., Morgan, M., Mundry, S., & Mello, D. (2010), Do states have certification
requirements for preparing general education teachers to teach students withdisabilities? Experience in the northeast and islands region. Issues & answers. Rel 2010no. 090. Regional Educational Laboratory Northeast and Islands. Retrieved February 04,
2014 from http://www.eric.ed.gov/PDFS/ED526433.pdf
Brears, L., MacIntyre, B., & O’Sullivan, G. (2011), Preparing teachers for the 21st century using
PLB as an integrating strategy in science and technology education. Design andTechnology

Education,

16(1),

36-46.

Retrieved

February

04,

2014

from

http://www.eric.ed.gov/PDFS/EJ916495.pdf
Brooks, S. (2001), Integration of information resources and collection development strategy.
Journal of Academic Librarianship, 27(4), 316-319. Doi: http://dx.doi.org/10.1016/S00991333(01)00218-X
Carver, C. S., & Scheier M. F. (2008), Feedback processes in the simultaneous regulation ofaction and affect. Handbook of Motivation Science. New York, USA: The Guilford Press.
Centra, J. A. (1973). Effectiveness of student feedback in modifying college instruction. Journalof Educational Psychology, 65(3), 395-401. USA: American Psychological Association.
190	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Cornacchia, H. J., Olsen, L. K., & Ozias, J. M. (2001), Health in elementary schools. (9th ed.).
USA: Mosby-year Book Inc.
Coy, D. R., & Long, J. K. (2005), Maslow and miller: an exploration of gender and affiliation in
the journey competence. Journal of Counseling and Development, 83(2), 138.
Culp, M. M. (2005), Increasing the value of traditional support services. New Directions forCommunity Colleges, 131, 33-49.
deFur, S. H., & Korinek, L. (2008), The evolution toward lifelong learning as a critical transition
outcome

for

the

21st

century.

Exceptionality,

16(4),

178-191.

Doi:

10.1080/09362830802412158
De Grez, L., Valcke, M., & Roozen, I. (2009), The impact of goal orientation, self-reflection andpersonal characteristics on the acquisition of oral presentation skills. European Journal of
Psychology of Education, 24(3), 293-306.
Deikman, A. B., & Eagly, A. H. (2008), Of men, women, and motivation a role congruity
account. Handbook of Motivation Science. New York, USA: The Guilford Press
Department of Psychology, University of Michigan. Howard Gardner’s Multiple Intelligences.
Retrieved February 04, 2014 from http://sitemaker.umich.edu/356.martin/homeDrummond, K. E., & Brefere, L. M. (2007), Nutrition for food service and culinary professionals.
(7th ed.). Canada: John Wiley & Sons Inc.
Espina, P.D. (2009), Physical aspects of campus security. Security In and Out School. Retrieved
February 04, 2014 from http://securitymatters.com.ph/physical-aspects-of-campus-security379/

191	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Fiske, S. T. (2008), The core social motivations views from the couch, consciousness, classroom,computers, and collectives. Handbook of Motivation Science. New York, USA: The
Guilford Press.
Gawel, Joseph E. (1997), Herzberg's theory of motivation and maslow’s hierarchy ofneeds. Practical Assessment, Research & Evaluation, 5(11). Retrieved February 04, 2014
from http://pareonline.net/getvn.asp?v=5&n=11
Grant, H., & Dweck, C. S. (2008).,Self-theories, goals and meaning. Handbook of Motivation
Science. New York, USA: The Guilford Press.
Hu, S. (2011), Scholarship awards, student engagement, and leadership capacity of highachieving low-income students of color. Journal of Higher Education, 82(5), 511-534.
Hurliman, S. K., & PAston, K. (2011), Code labs: expediting laboratory test results during a code.
Critical Care Nurse, 31(5), 6-30.
Hwang, Y. S., & David, E. (2011), Attitudes towards inclusion: gaps between belief and practice.
International Journal of Special Education, 26(1), 136-146. Retrieved February 04, 2014
from http://www.eric.ed.gov/PDFS/EJ921198.pdf
Jones, V. F. & Jones, L. S. (2001), Comprehensive classroom management creating communities
of support and solving problems. USA: Allyn & Bacon.
Korkmaz, I. (2008), Elementary teachers' perceptions about implementation of inclusive
education. US-China Education Review, 8(2), 177-183.
Kose, B. W., & Lim, E. (2010), Transformative professional learning within schools: relationshipto teacher’s beliefs, expertise and teaching. International Journal of Leadership in
Education, 13(4), 393-419.
192	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Leary, M. R., & Cox, C. B. (2008), Belongingness motivation a mainspring of social action.
Handbook of Motivation Science. New York, USA: The Guilford Press.
Leather, D. J., & Marinho, R. D. (2009), Designing an academic building for 21st century
learning: a dean’s guide. Change: The Magazine of Higher Learning, 41(3), 42-49.
Lo, C. C. (2010), How student satisfaction factors affect perceived learning. Journal of the
Scholarship of Teaching and Learning, 10(1), 47-54.
Lucas, M. R. D., & Corpuz, B. B. (2007), Facilitating learning: a metacognitive process. Quezon
City: Lorimar Publishing Inc.
Mackey, T. P. (2010), Collaborative information literacy assessments: strategies for evaluatingteaching and learning. London: Facet Publishing.
McClellan, J. A., & Conti, G. J. (2008), Identifying the multiple intelligences of your students.
Journal of Adult Education, 37(1), 13-32. Retrieved February 04, 2014 fromhttp://www.eric.ed.gov/PDFS/EJ891071.pdf
Merrienboer, J. J. G., & Paas, F. (2003), Powerful learning and the many faces of instructional
design: Toward a framework for the design of powerful learning environments. In E. De
Corte, L.

Verschaffel, N. Entwistle & J. van Merrienboer (Eds.), Powerful learning

environments: Unravelling basic components and dimensions. Oxford, England: Elsevier
Science.
Moore, M. G. (2007), Handbook on distance education.(2nd ed.). United Kingdom: Routledge
Publishing Company.
Morling B., & Kitayama S. (2008), Culture and motivation. Handbook of Motivation Science.
New York, USA: The Guilford Press.
193	
  
	
  

The IAFOR Journal of Education
2014	
  

Volume 2 - Issue 1 - Winter	
  Murray, R. J. & Kane, K. S. (2010), In service of mission: assessing catholic school guidancecounselors. Catholic Education: A journal of Inquiry and Practice, 14(2), 173-194.
Needles, B. E., Anderson, H. R., & Caldwell, J. C. (1990). Principles of accounting. (4th ed.)
USA: Houghton Mifflin Company.
Neiman, S. (2011), Crime, violence, discipline and safety in U.S. public schools: finding from theschool survey on crime and safety 2009-10. National Center for Education Statistics, 85.
Onchwari, G., Onchwari, J. A., & Keengwe, J. (2008), Teaching the immigrant child: applicationof child development theories. Early Childhood Educational Journal, 36(3), 267-273.
Orange, C. (2002), The quick reference guide to educational innovations practices, programs,
policies and philosophies. California: Corwin Press, Inc.
Ormerod, N. (2010), Identity and mission in catholic organizations. Austrlasian Catholic Record,87(4), 430-439.
Parkay, F. W., & Haas, G. (2000), Curriculum Planning. (7th ed.). Needham Heights, MA: Allyn& Bacon.
Piazza, C. C., Fisher, W. W., Brown, K. A., Shore, B. A., Patel, M. R., Katz, R. M., Sevin, B. M.,
Gulotta, C. S., & Blakely-Smith, A. (2008), Functional analysis of inappropriate mealtime
behaviors. Journal of Applied Behavior Analysis, 36, 187–204. Retrieved February 04,
2014 from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1284432
Richardson, J. W. (2007), Building bridges between school-based health clinics and schools.
Journal of School Health, 77(7), 337–343. USA: American School Health Association.
Ruoling, Z. (2010), On the rationality of college entrance examination analysis of its foundations,functions and influences. Chinese Education and Society, 43(4), 11-21.
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  Sadker, D., Sadker, M., & Zittleman, K. R. (2009), Teachers, Schools, and Society. (8th ed.). New
York: McGraw-Hill.
Sampson, J. P. Jr., Dozier, C. V., & Colvin, G. P. (2011), Translating career theory to practice:
the risk of unintentional social injustice. Journal of Counseling and Development, 89(3),326-337.
Santos, M. J. (2008), Knowledge level of food handlers in portuguese school canteens and theirself-reported behavior towards food safety. International Journal of Environmental HealthResearch 18 (6), 387-401.
Ellyson, S. L., Coldren, J. T., Kestner, J., Fry, W. R., Ragozzine, F., & Haynes, V. (2008),
General psychology. (3rd ed.). USA: Kendall Hunt Publishing.
Stevens, L. P. et al. (2007), Reconceptualizing the possible narratives of adolescence. Australian
Educational Researcher, 34(2), 107-127.
Taylor, H. F., & Anderson, M. L. (2007), Sociology the essentials. (4th ed.). USA: Thomson
Learning, Inc.
Thomas, H. (2010), Learning spaces, learning environments and the displacement’ of learning.
British Journal of Educational Technology, 41(3), 502-511. Doi: 10.1111/j.14678535.2009.00974.x
Vermunt, J. D. (2003), The power of learning environments and the quality of student learning.
Powerful Learning Environments: Unravelling Basic Components and Dimensions, pp.
109-124. Amsterdam: Elsevier Science.

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  Vohs, K. D., & Baumeister R. F. (2008), Can satisfaction reinforce wanting? A new theory about
long-term changes in strength of motivation. Handbook of Motivation Science pp.373-389.
New York, USA: The Guilford Press.
Weimer, M. (2002), Learner-centered teaching: five key changes to practice. San Francisco,California: Jossey-Bass.
Weinstein, C. S., Romano, M., & Migano, A. J. Jr. (2011), Elementary classroom management
lessons from research and practice. (5th ed.). USA: Mc Graw Hill.
Wohlfarth, D. (2008), Student perceptions of learner-centered teaching. InSight: A Journal of
Scholarly Teaching, 3, 67-74.
Yesil,

R.,&

Korkmaz,O.

(2010),

Reliability

andvalidity

analysisofthe multiple intelligence perception scale. Education, 131, 8-32.
Zhang, L. (2010), Study on the satisfaction of the relationship between teachers and students
under the impact of double factors in universities - A case study of empirical survey among
the students of seven universities in china. International Journal of Psychological Studies,2(1), 116-121.

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  Key Educational Scholars

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  Mikhail Geraskov (1874-1957)
Methodological Concepts of Learning Physics.
Mariyana Ilieva* This article is made with the financial support of the European Social Fund, project № BG051PO0013.3.06/0026. Mariyana Ilieva has the sole responsibility for the content of the article and it cannot be
considered as an official statement of the European Union or of Sofia University "St. Kliment Ohridski",
Faculty of Education

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  Abstract

Mikhail Geraskov is a distinguished Bulgarian educator from the first half of the twentiethcentury, who developed the scientific foundations of didactics and methodology of training. His
work contributed a lot to the development of the Bulgarian pedagogy. The subject of scientificresearch is didactical conceptions and methodological conceptions of learning. The aim of theresearch paper is to presents his ideas about particular methods of teaching Physics for highschool. Geraskov assumes direct correlation between didactics and methodology. This paper
focuses on his ideas about design, technology and methodological requirements for lessons ofPhysics. He believes that the appropriate methods are determined by the curriculum, set of
educational goals and age characteristics, and capabilities of adolescents. In his methodical
recommendations he focuses on teaching methods and forms that provoke students’ activity.
Comparative analysis with publications on the issues set for development of the Bulgarianpedagogic science and the actuality in the modern education system.

Keywords: Education; Design lesson; Methods of teaching; Classroom practice; Historicalpedagogy.

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  Introduction
Mikhail Geraskov is a distinguished Bulgarian teacher from the first half of the twentieth century,
who developed the scientific foundations of didactics and methodology of training. In the period
1923 – 1940 he was a lecturer at Sofia University. The period was characterized by thedevelopment and influence of the Herbartianism and the Alternative education. During thisperiod at the University taught some of the distinguished Bulgarian educators - professors
Dimitar Katzarov (1881-1960), Petko Tzonev (1875-1950), Hristo Negentzov (1881-1956). In the
1920s at the University were formed two major departments the Department of Pedagogy, (1924)
it was led by professor Katzarov and the Department of Didactics and methodology, in 1924
headed by Professor Tsonev who attracts Geraskov of academic activity. The period 1921-1950
was characterized by the launch of the development of university courses in methods of teachingvarious subjects. Geraskov is one of the erudite Bulgarian teachers.

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Mikhail Geraskov (1874-1957)

Mikhail Geraskov with colleagues and students at the
University, Sofia 1939

The scientific production of Mikhail Geraskov is voluminous and of a varied content. The
scientific areas contain Pedagogy, Theory of education, Philosophy of education, Didactics,
Methodology of training, Educational psychology, School law, History of international andBulgarian education.
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  Despite all these facts in contemporary Bulgarian historiography scientific publications include
separate studies of his ideas. The reason for this is the change of political ideology in Bulgaria. In
September 1944 a communist regime was imposed in Bulgaria and the country’s political, socialand cultural structures were radically changed by the ideology of this regime. Thinking people
are a barrier before any dictatorship, therefore the first task of usurpers is terror and genocide ona mass scale against the intellectual class. Some of the books by Geraskov have been on the listof books banned by the government. The Bulgarian cultural life was dominated by the communist
ideas for 45 years.
The research paper is part of a scientific study, which explores and analyzes the scientificproduction of Mikhail Geraskov in the field of didactics and methodology of training. The
scientific study investigates and presents the didactical and methodological conceptions
developed by Mikhail Geraskov. In the context of this research paper contribution is related tothe development of this issue in its entirety. The aim of the research paper is to present his ideas
on methods of teaching Physics. The following tasks are:•to present his views on the scientific status of the teaching methodology•

to analyze Geraskov’s basic methodological views for teaching Physics•

to define and show their importance and relevance in modern methods in the Bulgarian
education

The research is built on the scientific production of Geraskov’s work on methods of teachingparticular subjects and interpretation of key publications on the topic.
Literature review
The Bulgarian educational history includes separate studies of his pedagogical conceptions.
While many studies have been done since then, few of them includes Geraskov’s philosophy of
methods of teaching particular subjects in school.
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  Radev (1988, 1999, 2002) developed the theme of pedagogical thought in Bulgaria in the firsthalf of the twentieth century. He presented basic facts about ideas of Geraskov. Radev described
his contribution to the development of the Bulgarian pedagogy, especially of the didactics andmethodology of training.
In the some research about the history of the methodology of teaching the authors very briefly
wrote for Geraskov. Radeva (2009) presented information about his methodological concept oflearning History. Antonova (1983) wrote about his methodological concept of learning Chemistry.
Each of the authors briefly presented his contribution to the development of the methodology of
training.
Yordanova (2005) examined the methodological views of Geraskov for learning Pronunciation in
the elementary school. In conclusion the author expressed position that he is one of the mostimportant educators of scientific thought and his methodological concept of learning Bulgarian
language has actual dimensions and value.
Petrova (2005) presented in detail information about his methodological concept of learning
Bulgarian language. In summary the author wrote that the methodological heritage of Geraskov isvaluable. She defined him as a progressive scholar who put rational requirements about thedesign and the technology for lessons of Bulgarian language. Gulabova had such task of her
article (2005). She briefly described the ideas of Geraskov about the methodological concept oflearning Particular subject.
Ilieva (2012) described in detail Geraskov’s basic methodological views for teaching Bulgarian
language and Mathematics. In summary the author indicated that he has important contributions
to the development of methods of teaching Bulgarian language and mathematics. In conclusion
she maintained that in the middle of the twentieth century his ideas are highly appreciated andinfluenced to the other scholars in this area.
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  In conclusion, each of the authors strongly pointed his contributed to the development of theteaching methodology and the relevance of his ideas. But the studies are not enough to bring out
the Geraskov's fundamental ideas about design, technology and methodological requirements forlessons of particular subjects. The aim of the research paper is to presents his ideas about
particular methods of teaching Physics. The research should show another aspect of hispedagogical heritage and should enrich the Bulgarian historiography. Comparative analysis withpublications on the issues set for development of the Bulgarian pedagogic science and theactuality in the modern education system.
Scientific status of the teaching methodology by Mikhail Geraskov
Geraskov distinguishes didactics and methodology. He believes that didactics contains theory andprinciples of teaching methods. Teaching methodology contains theory and technique of teachingparticular subjects. He assumes that between didactics and methodology there is a direct
correlation. Teaching methodology has a specific task - to examine and specify the use of
didactic and pedagogical training rules in order to achieve the best educational outcomes. He
defines methodology as a special didactics (Geraskov, 1922, p. 3). His view is different from themodern educational theory (Radev, 2005). However his idea about the correlation theory –practice is important. This shows that his idea is still relevant today.
In his view, didactics modify the content according to the development of students. He argues
that it is impossible training to be tailored to the individuality of each student. However, it isnecessary to develop problems, according to the characteristics of the age groups. He makes thedivision according to the development of students and determines - Didactics of primary school,
Didactics of secondary school and Didactics of high school. Each of them has special task-driven
objectives. Compliance with the psychophysiological opportunities for students of different age
groups is important and necessary for the education. The author claims that pointing out that in
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  developing the science standards should specify the individuality of students (Geraskov, 1921, pp.
17-20).
This division can certainly be extrapolated as a correlation between didactics and methodology.
The following table (Table 1) represents the correlation theory – practice and the didactics
modify the content. Didactics of primary, secondary and high school in content are actually
modern subject theory. Although Geraskov puts them only according to age groups, he does notgive a prescription on curriculum. He recommends specific tasks to involve the organization,compliance with laws and application of specific methods. Such view is close to the modern
understanding of the relationship of the individual school didactics and methodologies. In firsthalf of the twentieth century the school levels of Bulgarian education were primary school,secondary school and high school. In his scientific concept Geraskov covers the entire education
system. In the modern concept of school didactics there is no such division, but similardifferentiation will contribute to improving the quality of education. His idea is modern. The
sciences principles should be according to the characteristics of the age groups. Dividing asystem into its separate parts is considered support to the proper organization of training and theuse of appropriate methods. In practice, each of the steps in education should be to promote thedevelopment of students. The educational goal is possible when educational system is consistent
with psychology of students. These conditions influence the quality of education.

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  Table 1. The correlation between didactics and methodology

Characteristic of the scientific publication of Mikhail Geraskov in teaching methodology
In 1922 the first edition of the book of Mikhail Geraskov Methodology for primary andsecondary education which is a guide for students in Teachers' institutes, schools, teachers andself-improvement was released. It is dedicated to the methodology of the particular subjects. The
book was reprinted four times consecutively, the second edition was in 1924, the third in 1928
and the fourth - in 1942. This shows the best estimate, which is given to the work of Geraskov.
Each edition is tailored to the school curriculum of the Bulgarian educational system and changes
in it. In 1946 the book was published under the title Methods of subjects in school.
The period was characterized by the development and influence of Herbartianism and European
reforming education. In the first half of the twentieth century in the pedagogical literature wasusing the methodologies of Stephan Basarichek (1848-1918) and Todor Benev (1861 -?).
Basarichek was a Croatian educator, lecturer in a teaching school in Zagreb, where he trained
many Bulgarians, who would later work in the field of education. He was a follower of
Herbartianism. His views had a strong influence on the Bulgarian educational thought andpractice to the spread of Herbartianism immediately after the Liberation. His scientific
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  publication was translated into Bulgarian. During this period, many pedagogical literature andbooks of Basarichek were used for pedagogical disciplines teaching future teachers. In period
1903-1906 were published three volumes of the book by Todor Benev, Sava Velev (1869-1913)
and Vasil Nikolchov (1873 -?). They are dedicated to pedagogy, didactics, teaching methodology
and history of education. The second volume is Methodology. Benev is entirely in the spirit of
Herbartianism specific instructions and followed the instructional models of education. During
this period, only individual articles existed in Bulgaria, many of which were devoted to themethodology in the primary school. This is inherently Geraskov’s great contribution to thedevelopment not only of the methodology, but also of the didactics and pedagogy in general. He
presents his personal position depending on the Bulgarian reality and educational system.
In the preface to the first edition, Geraskov (1922, pp. 1-2) points out the reasons which prompted
him to write this paper. The Bulgarian educational print often considered questions ofmethodology in different subjects, but they were isolated and represented separate and distinct
concepts. The purpose of his work is to give a global and contemporary view, which serves toprepare future teachers and those who seek to enhance their pedagogical training - for selfeducation of teachers.
In considering methodological issues in individual subjects Geraskov adopts an idea about the
subject of the special methodology. In characteristic style Geraskov presents the development ofideas and confirmation of each subject in historical aspect. He points out specific objectives andtasks of the subjects, starting from general educational purposes, the place they occupy in the
curriculum and requirements for the selection and order of the material. To achieve his intention
Geraskov presents views on the conduct of individual units’ methodological subjects andrecommends concrete implementation of teaching methods and forms. He emphasizes therelationship with psychology, while examining the methodology and presentation of various
subjects puts particular emphasis on the psychophysiological basis of the student. To achieve
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  educational goals and the examination of theory and Geraskov shows that a good methodology
and application of each method is in direct correlation with the knowledge of the field of
psychology. He focuses on the educational and practical importance of each subject. He presents
in detail the particular methodological design of a learning unit.
The historical context of the relationship between didactics and methodology is amended in theprocess of building a system of pedagogical sciences. This is indicated by modern scholars of
Bulgarian pedagogy for example Petar Petrov. In the first half of the twentieth century and before
that, methodology is accepted as a normative part of the pedagogical theory and its content
presents primarily the specific guidance for teaching (Petrov, 1998, pp. 16-17). This aspect shows
the idea about the subject and tasks of the special methodology. The structure is consistent of thepresentation and the importance of the subject key concepts associated with it and its
development as a science.
Geraskov briefly presents the evolution of ideas and presentation of each subject in historicalaspect which is a characteristic of his style of writing. He points out specific objectives and tasksof subjects determined by the total educational purposes. He presents his position about the
curriculum and requirements for the selection and order of the knowledge. Geraskov expresses
views on the conduct of teaching particular subjects and recommends specific application ofteaching methods. This is determined by the compliance and implementation of the principles of
education. He emphasizes the relationship with psychology and methodology in addressing thevarious subjects and puts particular emphasis on the psychophysiological progress of students. He
thinks that the best methodology and application of each method is in a direct correlation with theknowledge of psychology. It is important for the educational purpose. He also focuses on the
educational and practical significance of each school subject (Geraskov, 1946).

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Volume 2 - Issue 1 - Winter	  The meaningful analysis of his scientific publication focuses to this problem, in conclusion to thatthe author consistently adopts his instructional model of education with the four steps in teaching.
They are:•definition of the aim of the lesson•

preparation for teaching the new curriculum material•

teaching new knowledge•

practice knowledge

He adopts a direct relationship between school levels. This is clearly expressed in the setting ofindividual goals and objectives of training in each subject. He focuses on the methodology ofprimary school, as it laid the foundations of the education of young people, particularly in reading,writing and arithmetic, which are not only skills necessary for personal and social development ofadolescents, but also a prerequisite for higher knowledge scientific fields. Geraskov puts tocorrelation emphasizes theory – practice (Geraskov, 1921, p. 177).
His instructional model of education should not be directly related to the model of Herbartianism(see Table 2). He takes only a few aspects of this model. The direct correlation between schoollevels is pronounced by placing individual goals and objectives in teaching various subjects. The
three school levels of Bulgarian education, in this period, are primary school, secondary schooland high school. Each of them has specificity determined by the psychophysiological progress ofthe students. This determines differences in recommended methods. Also each subject area
requires the use of certain methods. This is especially true for the Natural Sciences of subjects inwhich Geraskov considered the most appropriate the use of the inductive method. In themethodological views of Geraskov thoroughly is presented the idea of the need to implement avariety of methods. For each school grade in different subjects, he indicates which methods andforms of training are best suited for use (Geraskov, 1944).
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Volume 2 - Issue 1 - Winter	  THE INSTRUCTIONAL MODEL OFMIKHAIL GERASKOVTHE INSTRUCTIONAL MODEL OF
HERBARTIANISM

1. Definition of the aim of the lesson

1. Preparation

2. Preparation for teaching the new
curriculum material

2. Presentation

3. Teaching new knowledge

3. Association

4. Practice knowledge

4. Generalization
5. Application

Table 2. Similarities and differences between the two instructional models of education

Teaching methodology of Physics
Geraskov’s ideas support the development of Bulgarian pedagogical thought; more specifically,
he develops methods of teaching particular subjects for high school. It is because in the first halfof the twentieth century different scientific publications focus on the methodology for primaryschool. Contrary to Geraskov in their issues on the methods of teaching particular subjects
including the three school levels which are primary school, secondary school and high school. In
his methodical recommendations on particular subjects, briefly, specifying certain teaching
methods and forms suitable for use in the high school. He believes that the appropriate methods
are determined by the curriculum, set of educational goals and age characteristics, andcapabilities of adolescents. In his methodical recommendations he focuses on teaching methods
and forms that provoke students’ activity. This implies to a greater degree the use of heuristic
learning and development. Along with the induction for this school degree he recommends more
frequent use of deductive method. He emphasizes the need for the exercise of inductive reasoning.
Educational content and underlying educational purpose suggested enriching student’s awarenessthrough presenting a clear realistic picture and knowledge in various scientific fields in asystematic form. The knowledge must be practical and focused. Geraskov (1946, p. 84) stated
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  that, “Methods of teaching must influence the feelings of the students and their critical attitude
towards things in public life”.
The educational aim of Physics in high schools is to acquire knowledge of science, scientificmethods of observation and study. Physics is an inductive science. This science is the result of
inductive reasoning. Thus, according to Geraskov teaching Physics must be based on theexperiment. The main method of teaching Physics is induction and parallel with it is theanalytical method. Geraskov determines the methods of teaching. They are direct instructional
method, induction and deduction. In that process, experience is not mere observation, susceptible
to the tricks of our perception, but is based on systematic observation, comparison andverification. The experiments should be conducted exclusively for the purpose of observation andinformation gathering, followed by the formalization of knowledge (Geraskov, 1928, p. 173).
Geraskov believes in the importance of achieving greater connection between educational
purpose, theories and practices on Physics education. He focuses on laboratory activities. The
teacher’s guidance and instruction have ranged from highly structured to open inquiry.
Laboratory activities’ goal is to promote central science education goals including: understandingof scientific consepts, development of scientific practical skills and problem – solving abilities,
and interest and motivation. Scholarly efforts have identified serious mismatches between goals
for science education and learning outcomes visible in school graduates (Geraskov, 1928, pp.
175-177).
The way people learn and process new information that they are taught is one of the many factorsthat makes each individual person unique. While some people learn quickly by actually
performing a task for themselves, others learn better by watching someone doing the task or bysimply hearing the task explained. The methods that each prefers for learning is known as theirown unique learning style. Geraskov believes for teachers’ understanding of their student’s
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  learning style can be the key to unlocking their full potential and making difficult concepts seemas easy as they can be. This methodological assumptions of Geraskov is determined by his ideasof significance of psychophysiological progress of students. The teacher must know their students(Geraskov, 1923).
In Physics education Geraskov stresses the value of laboratory experiment and activities,
demonstration and models. Therefore, graphic organizers are visual representations of knowledge
that can support theoretical knowledge. They provide a frame for teachers and students tovisually identify important facts, organize information, and record relationships between facts
and ideas. These tools help students to practice higher level thinking skills and apply these skills
to real world situations. Different demonstrations, models and experiments help students toremember information, understand how pieces of information are related, better understand thelearning material and engagement of multiple intelligences. They are especially effective in
explaining and illustrating abstract concepts (Geraskov, 1928, pp. 178-179). Geraskov creates thelesson plan for forming knowledge of Physics with the four steps in teaching. They are:•introduction•

engagement in physical experience•

performance characteristics make the phenomenon•

defined as the Physical law•

exercises

In his ideas about structure, technology and methodological requirements of lesson Geraskov
firstly sets teachers’ preparation and design of Physics lessons. It includes theoretical, practicaland methodological aspects. He pays particular attention to the methodology of the teacher about
the students’ understanding of physical truths and the causal relationships between them. The
second condition are teaching aids which are very important. Equipment is needed to produce
natural experiments. The experiments in the classrooms must be under school time. He
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  recommends selecting those that require less time and which are most accessible. In the statementof the new knowlegde the teacher makes first physical experience. The experiments are mademost often by the teacher, but where possible and appropriate to engage students. This isimportant for the active participation of the students in training. After performance the teacher
points characteristics the phenomenon and the comparison with other similar events. He specifies
the relationship and defines the physical law. In drawing a few truths in attempts to observe thesequence. Geraskov writes that the lessons of Physics cannot give an overall scheme, but thestatement should follow the main points. The practice knowledge is best if you allow students toperform exercises alone. This can be carried out through experiments with a total exposure to thematerial or items with practical significance. In this part of lesson, the teacher and the students
can make various experimentals. Thus Geraskov puts the emphasis on students' activity. He
recommends that outside school hours are appropriate for students to visit places in which to see
the practical application of Physics. Practical exercises in physics are important for education.
Unfortunately, Geraskov says, most schools do not have the necessary facilities. It is importantthat these exercises allow students to make at least the most important attempts. Empiricalknowledge is very important in learning of Physics (Geraskov, 1928, p. 177). These ideas areclose to modern methodology. This highlights the principle of transparency, which is expressedby Geraskov. His ideas are interesting and contemporary. They may support improving thequality of education.
The hygienic working conditions that adversely affect the physiological status of students arevery important (Geraskov, 1928, p. 188). In education these subjects presented the idea ofenvironmental and health education, which requires pupils to form a conscious and caring
attitude towards their own health and the environment with all its components - physical,
chemical, biological, cultural, historical and others. It puts the other cross-curricular education,
which as mentioned is expressed as an idea by Geraskov. The idea that physics is an inductive
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  science and focus on the physical experiment in education is in modern pedagogical science(Raykova, 2008). This implies respect for visual principle. M. Geraskov requirements onteacher’s education for the learning process have now become outdated. However, the planningand execution of specific physical experiments for achieve clear and thorough knowledge of thestudents are important points. The idea of Geraskov for activity in the training of students is still
current today. Their participation in the conduct of specific experiments, either alone or with theteacher is important.
Methodological concepts and requirements that are present in modern methods show that theideas of Mikhail Geraskov in this aspect are still relevant. Today it is recognized that the practicalexperience requirement is related to the logical structure of the curriculum and meets the purposeof the experiment. Proper organization of supervision during the event is important to direct
properly the attention of the students. Emphasis is placed and the optimum number ofexperiments and preliminary preparation of teachers for the experimental part of a lesson. It helps
to perform successful and safe experiments. This is connected with the right technique. Clearly
expressed is the idea of teaching students to independence of thought and action, giving them theopportunity to perform experiments under the instructions of the teacher. The training
presentation of the material should be presented according to age groups - in a narrative or alecture form, which is preferred in the high school, in parallel with the discussions it is important
to combine demonstration of experiments and other visual aids.
In general, these requirements are expressed today in the methods of teaching Physics; they are
similar to those posed for the Bulgarian teachers from the first half of the twentieth century when
the importance of educational resources was also stressed. Although Geraskov defines them ashigh school requirements. The model of learning in modern education is different in degree fromthat of Geraskov’s. However his idea of the place of experiment in the exhibition of new teaching

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Volume 2 - Issue 1 - Winter	  material is preserved today. The methodology of training as the most effective approach isconsidered a removal of physical laws and rules of the experiment.	
  

	
  	
  	
  	
  

	
  

The Physics classroom in the 1930s

Scientific production of Mikhail Geraskov

www.lostbulgaria.com

Photo by: M. Ilieva

Conclusion
The contribution of Mikhail Geraskov in the methods of teaching particular subjects can be seen
in several aspects. In the time in which he lived and worked, the Bulgarian pedagogical thought
experienced a deficit in its methodological developments. Geraskov fills this gap and it worked
very well. His Methodology was reprinted several times and is one of the main guidelines forschools to prepare teaching staff. His ideas were highly appreciated and influenced otherresearchers in this field. He makes a significant contribution to the development of teaching
methodology of the high school. He believes in basic principle which emphasize that the schoolorganization must be determined by the specifics of the students’ specifics. He presents his
personal position. He does not fully accept the ideas of Herbartianism. He wishes themethodological recommendations are guiding thought for teachers in organizing and
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  implementing their practical work, as well as an objective criterion for discussion of issues in thisarea. One of the major achievements of Mikhail Geraskov is improvement of methodology for
Bulgarian school. He made valuable contributions to science. Before 1950's he was the mentor
for scholars who worked on this topic.
The educational politics in Bulgaria for the past 20 years has been focused on improving thequality of education, in particular through increasing the capacity for teaching. One of thestrategies to improve the quality of Bulgarian education is to establish teaching practices thatallow a greater interaction between the teacher and the student, so as to assure a constantmonitoring of the teaching and learning process in order to quickly identify problems and tosupport students that may face difficulties. The others strategies are to focus on the learning
process of each and every student and to establish mechanisms for the participation of thestudents in the education. The History can teach us. Geraskov’s views of methodology in the highschool are actuality in the modern educational system. There is a significant similarity with theideas in modern education. In conclusion his ideas are relevant to contemporary educational
practice. The model of learning in modern education is different in a degree from that ofGeraskov’s. However his idea of the place of experiment in the exhibition of new teachingmaterial is preserved (today). His methodological recommendations are relevant for thecontemporary Bulgarian education.
	
  
	
  

References
Antonova, L. (1983), The methodological heritage of Geraskov about learning Chemistry. In:
Biology and Chemistry. Vol. 6. Sofia: Press Ministry of education [in Bulgarian].

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  Geraskov, M. (1921), The Didatics or the theory of training. Vratza: St. Tzekov Press [inBulgarian].
Geraskov, M. (1922), Methodology for primary and secondary education. Vratza: St. Tzekov
Press [in Bulgarian].
Geraskov, M. (1923), Learning of students in high schools from didactic perspective. Vratza: St.
Tzekov Press [in Bulgarian].
Geraskov, M. (1928), Methodology for primary and secondary education. 3rd ed. Vratza: St.
Tzekov Press [in Bulgarian].
Geraskov, M. (1944), The basics of Didactics. 2nd ed. Plovdiv: H.G.Danov Press [in Bulgarian].
Geraskov, M. (1946), Methods of subjects in school. Sofia: Hemus Press [in Bulgarian].
Gulabova, М. (2005), Learning of Particular subject in Methodology by Mikhail Geraskov. In:
National Scientific Session “Pedagogical Contributions”. Veliko Tarnovo: Univ. Press St.
Cyril and St. Methodius, pp. 147-150 [in Bulgarian].
Ilieva, M. (2012), Mikhail Geraskov (1874-1957) methodological concept of learning Bulgarian
language and mathematics. In: Year-book of Sofia University “St. Kliment Ohridski”,
Faculty of Pedagogy, Book – Pedagogy. Vol. 104. Sofia: Univ. Press St. Kliment Ohridski[in Bulgarian].
Yordanova, D. (2005), Look at the methodological views of Mikhail Geraskov about learning
Pronounce in elementary school during the first half of the twentieth century. In: National
Scientific Session “Pedagogical Contributions”. Veliko Tarnovo: Univ. Press St. Cyril andSt. Methodius, pp. 82-86 [in Bulgarian].
Petrov, P. (1998), Didactics. Sofia: Veda Slovena – JG Press [in Bulgarian].
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  Petrova, Z. (2005), The fundamental aspects to language learning in the methodological work ofProfessor Mikhail Geraskov. In: National Scientific Session “Pedagogical Contributions”.
Veliko Tarnovo: Univ. Press St. Cyril and St. Methodius, pp. 115-122 [in Bulgarian].
Radev, P. (1988), Development of ideas about structure of educational process. Plovdiv: Univ.
Press Paisii Hilendarski [in Bulgarian].
Radev, P. (1999), Temathical indexes and paradigmas in Bulgarian workbooks and handbooks of
didactics. Plovdiv: Univ. Press Paisii Hilendarski [in Bulgarian].
Radev, P. (2002), History of Bulgarian education. Plovdiv: Univ. Press Paisii Hilendarski [inBulgarian].
Radev, P. (2005), General school didactics. Plovdiv: Univ. Press Paisii Hilendarski [inBulgarian].
Radeva, M. (2008), School history education in Bulgaria 1878-1944. Sofia: Gutenberg Press [inBulgarian].
Raykova, Z. (2008), Development procedural skills in science education – constructivist
approach. Plovdiv: Univ. Press Paisii Hilendarski [in Bulgarian].
Sofia University “St. Kliment Ohridski” (1940), Almanac of Sofia University St. Kliment
Ohridski, 1888 – 1939. Sofia: Univ. Press. St. Kliment Ohridski [in Bulgarian].
	
  

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  Guide for Authors
Article structure
Abstract
A concise and factual abstract is required (maximum length of 250 words). The abstract should
state briefly the purpose of the research, the principal results and major conclusions. An abstract
is often presented separately from the article, so it must be able to stand alone. For this reason,
References should be avoided, but if essential, then cite the author(s) and year(s). Also, nonstandard or uncommon abbreviations should be avoided, but if essential they must be defined attheir first mention in the abstract itself.
Keywords
Immediately after the abstract, provide a maximum of 6 keywords.
Introduction
Present purposes of the study and provide background for your work.
Literature Review
Include a pertinent literature review with explicit international connections for relevant ideas.
Discuss the findings of published papers in the related field and highlight your contribution.
Methodology and methods
Provide sufficient detail to allow the context of the work to be thoroughly understood and/or for
the work to be reproduced. Provide sufficient detail for readers to understand how you engaged inyour inquiry. Clear descriptions of your context and participants along with strategies used tocollect and analyze data should be described.
Discussion
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  This section should explore the significance of the results of the work, not repeat them.
Combining your results and discussion into a single section may be suitable. Returning torelevant literature from the introduction should show how your work connects with or interrupts
already published literature.
Conclusions
The main conclusions of the study may be presented in a Conclusions section, which can include
the main findings, the implications, and limitations.
Appendices
If there is more than one appendix, they should be identified as A, B, etc.
Acknowledgements
Collate acknowledgements in a separate section at the end of the article before the references anddo not, therefore, include them on the title page, as a footnote to the title or otherwise. List here
those individuals who provided help during the research (e.g., providing language help, writing
assistance or proof reading the article, etc.).
Footnotes
Footnotes should be used sparingly. Number them consecutively throughout the article, using
superscript Arabic numbers.
References
Citation in text
Please ensure that every reference cited in the text is also present in the reference list (and viceversa).
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  Reference style
Text: Citations in the text should follow the referencing style used by the American
Psychological Association (APA). Publication Manual of the American Psychological
Association, Sixth Edition, ISBN 978-1-4338-0561-5.
List: references should be arranged first alphabetically and then further sorted chronologically ifnecessary.
Reference to a journal publication:
Van der Geer, J., Hanraads, J. A. J., & Lupton, R. A. (2010). The art of writing a scientific article.
Journal of Scientific Communications, 163, 51–59.
Reference to a book:
Strunk, W., Jr., & White, E. B. (2000). The elements of style. (4th ed.). New York: Longman,(Chapter 4).
Reference to a chapter in an edited book:
Mettam, G. R., & Adams, L. B. (2009). How to prepare an electronic version of your article. In B.
S. Jones, & R. Z. Smith (Eds.), Introduction to the electronic age (pp. 281–304). New York: EPublishing Inc.
Please follow the checklist:* Times New Roman font (size 12)* Double-spacing throughout the document; paragraphs, justify.
* Double space (instead of indent) to designate a new paragraph or section* Page numbers at the bottom center of each page
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Volume 2 - Issue 1 - Winter	  * Top, bottom, and side margins 0.87" or 2.2 cm* Page that includes title, authors, their affiliations, their contact information, and the topic of thesubmission* Authors and affiliations repeated at the beginning of the body of the paper* There is no limit of words or pages, but manuscript too short or incomplete will be rejected.
IAFOR Journal of Education is following the guidelines and advice proposed by top SSCI
academic journal Teaching and teacher Education on their website.

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