Volume Two - Academic Conferences

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Adelua Olajide Olawole and Maruff Akinwale Oladejo Fichten, C. S., Asuncion, J., Barile, M., Fossey, M., and De Simone, C. (2000) “ Access to Educational and Instructional Computer Technologies for Post-Secondary Students with Disabilities: Lessons from Three Empirical Studies”, Journal of Educational Media, Vol. 25, No.3, pp 179-201. Foucher, R., and Prince, I. (2003) “Motivation et Apprentissage dans des Dispositifs Ouverts de Formation, Dans" N. Delobbe, G. Karnas et C. Vandenberghe (dir.) Évaluation et développement des Compétencesau Travail, Vol.1. Psychologie du Travail et des Organisations, (p.517-526). Presse de l’Université de Louvain. Georgiev, T., and Gobachev, A. (2004) M-Learning – The Modern Stage of ELearning. International Conference on Computer Systems and Technologies . [online] Retrieved January 04,2005 from http://edet.ecs.ru.acad.bg/cst05/ Docs/sIV/426.pdf. Hall, B., and Snider, A. (2000) Glossary: The Hottest Buzz Word in the Industry, Learning, Vol. 44, No. 4, pp 85- 104. Homan, G., and Macpherson, A. (2005) “ELearning in the Corporate University” Journal of European Industrial Training, Vol. 29, No. 1,pp 75-99. Jackson, R.H. (2001) Defining ELearning - Different Shades of Online Web-Based Learning Resources. [online] Retrieved on June 25, 2005 from http://www.outreach.utk.edu/weblearning/. Newton, R. (2003) “Staff Attitudes to the Development and Delivery of ELearning” New Library World. Vol. 104,No.1193, pp 412-425. Odabasi, H.F.; Kuzu, A.; Girgin, C.; Cuhadar, C.; Kiyici, M. and Tanyeri, T. (2009) “Reflections of the Hearing Impaired Students on Daily and Instructional PDA Use”, International Journal of Special Education, Vol. 24, No. 1, pp8-19. Saade, R., and Kira, D. (2007)”Mediating the Impact of Technology Usage on Perceived Ease of Use by Anxiety” Computers and Education, Vol. 49, No.4,pp 1189-1204. Smith, Q. P., and Bendev, P. (2003)”The Use of Personal Digital Assistants for Learning: A Review of Literature”, Learning and Skills Development Agency, Vol.. 4, No. 3, pp 95-105. Stephens, P. and Shotick, J. (2001) “Computer Literacy and Incoming Business Students: Assessment, Design and Definition of a Skill Set,” Issues in Information Systems, Vol. 2, No. 2, pp. 460 – 466. Vrana, V.; Fragidis, G.; Zafiropoulos, C.; and Paschaloudis, D. (2010) “Analysing <strong>Academic</strong> Staff and Students’ Attitudes towards the Adoption of ELearning”, Paper Delivered at the International Forum of Educational Technology & Society (IFETS), July. 608
An Integrated Environment for Providing Learning Style Information in a Unified Manner Fatemeh Orooji, Fattaneh Taghiyareh and Zahra Rahimi Department of Electrical and Computer Engineering, Tehran University, Tehran, Iran f.orooji@ut.ac.ir ftaghiyar@ut.ac.ir z.rahimi@ut.ac.ir Abstract: Learning styles inventories provide insights into student perceptions about how they prefer to learn. Since learning styles have notoriously some inconsistencies and invalidities, it is unreliable to base instructional decisions on just one learning style preferences. This paper introduces a new approach to integrate various learning style modelers in a unified system. The unified system contains some predefined phases in modeling each style’s dimensions and some representing suggestions in order to visualize modeler results. Four popular learning styles along with their specific dimensions and report representations have been studied to demonstrate how to synthesize various inventories into a single representation of learners’ learning styles. Utilizing integrated environment in the University of Tehran, department of electrical and computer engineering, has revealed some dependencies between a modeler dimensions as well as some correlation between two modelers' dimensions. The implication of this effort is to provide advice about how web-based instructions can be modified to accommodate learners’ differences. Keywords: user model, learning style, learning style questionnaire, web-based educational system, eLearning 1. Introduction In the past decades, the rapid growth of the internet has brought a great deal of changes in our educational environment, demanding continuous access to education. These web-based educational systems need to consider different characteristics of a large number of students, constructing their user models. User model represents essential information about each user in two dimensions: first, viewing him as an individual considering the user’s knowledge, interests, goals, background, and individual traits; second, modeling his/her context of work which consists of location, time of day and platform. Individual traits are stable and usually determined using psychological tests, consist of personality traits, cognitive styles, cognitive factors and learning styles (Brusilovsky and Millán, 2007). Learning style (LS) shows how people learn and how they prefer to organize and represent information. People have different strategies in managing information and different ways of implementing these strategies. Considering the LS of each learner individually, provides facilities to adapt the content (form, structure, presentation order of learning activities and choices of these activities) to improve the learning results, which is impossible for a teacher in a traditional educating system with a group of learners (Reed et al., 2000). There are several studies on some pedagogically personalized learning contents based on learners’ LSs, indicating differences in performance between matched and non-matched learners (Siadaty and Taghiyareh, 2007). However, there are still some questions about the consistency of visual, auditory and kinaesthetic preferences and the value of matching teaching and LSs (Coffield et al., 2004). A considerable amount of research has been carried out to clear what is the best method to capture learners’ LS. LSs can be detected through learner’s profile as well as his behaviors, for example his navigation behaviour in web-based educational system (Bousbia et al., 2010). In addition, using a questionnaire is another acceptable approach to detect user LS. Naturally almost all of known models have proposed their own questionnaire independently (Felder and Silverman, 1988) (Grasha and Riechmann, 1975) (Briggs Myers, 1962). It is noticeable that there are more than 70 definitions of the LS concept and many researchers have tried to evaluate them showing the relationships between the LS identified by the instrument and students' actual learning. It has been claimed that since “a reliable and valid measure of learning styles has not yet been developed, it will be more useful to focus on learners’ previous experiences and motivation” (Coffield et al., 2004). This research aimed to be beyond any individual LS by gathering different LS models together and unifying their information via a proposed approach. This unified modeling system provides a complete report of learners’ LSs in adoption to integrated modelers, which may bring about better self- 609
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Proceedings of the 10 th European C
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. A Qu
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The Project Mobile Game Based Learn
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Extreme Scaffolding in the Teaching
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Malaysia); Tuomo Kakkonen (Universi
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Preface These Proceedings represent
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Mini Track Chairs Dr Antonios Andre
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Cornélia Castro is a PhD student i
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Manuel Frutos-Perez is the Leader o
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David Mathew works at the Centre fo
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Research interests include the inve
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Novita Yulianti is a PhD student at
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Peter Mozelius et al. searching and
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Peter Mozelius et al. Error Handli
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Peter Mozelius et al. were no chanc
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Peter Mozelius et al. single login
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Antoinette Muntjewerff for every st
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Antoinette Muntjewerff All of this
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Figure 1: Metadata editor Antoinett
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Antoinette Muntjewerff The structur
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A Framework for Decision Support fo
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Phelim Murnion and Markus Helfert i
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Phelim Murnion and Markus Helfert 4
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Phelim Murnion and Markus Helfert s
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Phelim Murnion and Markus Helfert P
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Shekhar Murthy and Devi Murthy wisd
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Shekhar Murthy and Devi Murthy educ
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Shekhar Murthy and Devi Murthy Figu
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Shekhar Murthy and Devi Murthy corr
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Shekhar Murthy and Devi Murthy Figu
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Shekhar Murthy and Devi Murthy Stag
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7. Conclusions Shekhar Murthy and D
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Student's Characteristics for Note
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Minoru Nakayama et al. Learning exp
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Minoru Nakayama et al. 3.3 Effectiv
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Minoru Nakayama et al. Table 2: Cor
Page 76 and 77: Freeing Education Within and Beyond
Page 78 and 79: Chrissi Nerantzi The aim was to exp
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Page 82 and 83: Chrissi Nerantzi familiarisation wi
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Page 86 and 87: Paul Newbury et al. the slides or w
Page 88 and 89: Paul Newbury et al. multimedia faci
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Page 92 and 93: Paul Newbury et al. Download figur
Page 94 and 95: Paul Newbury et al. “Has the fact
Page 96 and 97: eSubmission - UK Policies, Practice
Page 98 and 99: Barbara Newland et al. managing stu
Page 100 and 101: Figure 3: Technical infrastructure
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Page 104 and 105: Harnessing the Internet for Authent
Page 106 and 107: Abel Nyamapfene As stated on the co
Page 108 and 109: Abel Nyamapfene 8. There were suffi
Page 110 and 111: Abel Nyamapfene Mulnix, J. W. (2011
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Page 114 and 115: 2.3 Instrumentation Maruff Akinwale
Page 116 and 117: Maruff Akinwale Oladejo and Adelua
Page 118 and 119: References Maruff Akinwale Oladejo
Page 120 and 121: Adelua Olajide Olawole and Maruff A
Page 122 and 123: 2.2 Sample and sampling techniques
Page 124 and 125: 3.1 Result Adelua Olajide Olawole a
Page 128 and 129: Fatemeh Orooji et al. awareness and
Page 130 and 131: Fatemeh Orooji et al. Figure 1: The
Page 132 and 133: Fatemeh Orooji et al. Sensing/intu
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Page 138 and 139: Using Lifeworld-led Multimedia to E
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Page 144 and 145: Andy Pulman et al. The Research Evi
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Page 148 and 149: Thomas Putz A hybrid game, consisti
Page 150 and 151: 3.3 The different ‘events’ supp
Page 152 and 153: 4. Pedagogical impacts Thomas Putz
Page 154 and 155: Thomas Putz Fabricatore, C. (2000).
Page 156 and 157: Ricardo Queirós and José Paulo Le
Page 160 and 161: 3.6 Discussion Topics Ricardo Queir
Page 164 and 165: The Design and Development of an eL
Page 166 and 167: Andrik Rampun and Trevor Barker as
Page 168 and 169: Andrik Rampun and Trevor Barker add
Page 170 and 171: Figure 5: Screen shot of a user’s
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Kansei Design Model for eLearning:
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Fauziah Redzuan et al. presentation
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Fauziah Redzuan et al. A second sur
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Fauziah Redzuan et al. understand t
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Fauziah Redzuan et al. to explain t
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Fauziah Redzuan et al. Websites", P
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Changing Teacher Beliefs Through IC
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Bart Rienties et al. substantial di
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Bart Rienties et al. videoed for re
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5. Discussion Bart Rienties et al.
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Moodle and Affective Computing: Kno
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Manuel Rodrigues et al. Moodle does
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Manuel Rodrigues et al. Other sever
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Manuel Rodrigues et al. Doing this
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Using Google Applications to Facili
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Eleni Rossiou and Erasmia Papadopou
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Andrée Roy determines if eLearning
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Andrée Roy Table 3: Profiles of eL
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Andrée Roy the cost of production
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Andrée Roy Lawless, N., Allan, J.
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Zuzana Šaffková comment metacogni
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Zuzana Šaffková Moodle applicatio
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Zuzana Šaffková the other propert
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Zuzana Šaffková In the last phase
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Zuzana Šaffková prior knowledge,
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A Mobile aid Tool for Crafting Acti
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Ahmed Salem Question difficulty in
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Ahmed Salem Figure 2: The Simple le
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Ahmed Salem Table 1: The two groups
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King-Sized eLearning - how Effectiv
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Marie Sams et al. MOB was set up in
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Marie Sams et al. attaching the new
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Marie Sams et al. include time cons
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Rowena Santiago et al. However, whe
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Rowena Santiago et al. 6.1.2 Assign
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Rowena Santiago et al. the original
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Rowena Santiago et al. Together, th
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Vitor Santos and Luis Amaral To bui
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Vitor Santos and Luis Amaral Althou
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Figure 4: Technical architecture Vi
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Implementing and Evaluating Problem
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Maggi Savin-Baden et al. different
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Maggi Savin-Baden et al. and second
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Maggi Savin-Baden et al. important
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The Evolution of eLearning Platform
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Adriana Schiopoiu Burlea et al. Hyp
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Adriana Schiopoiu Burlea et al. Tab
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Adriana Schiopoiu Burlea et al. Eve
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Teachers’ Skills set for Personal
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Zaffar Ahmed Shaikh and Shakeel Ahm
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Zaffar Ahmed Shaikh and Shakeel Ahm
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6. Conclusion and recommendations Z
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Bridging the Feedback Divide Utilis
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Angela Shapiro and Aidan Johnston f
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Angela Shapiro and Aidan Johnston F
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Post-Academic Masters Course in Man
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4. Discussion and conclusion Cees T
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Engagement With Students in ‘Midd
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Anne Smith and Sonya Campbell x y c
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4.3 Student led connectivity Anne S
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Figure 2: Conceptualising ‘middle
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The Learning Management System as a
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Dina Soeiro et al. He was older, ol
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Dina Soeiro et al. specially about
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Can the Medium Extend the Message?
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Mekala Soosay elements under study,
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Mekala Soosay to self and peer-asse
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Mekala Soosay flexible web-based ap
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Implementation and Analysis of an O
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Iain Stewart et al. No-one was con
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Iain Stewart et al. The content sh
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Iain Stewart et al. entry per stude
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Iain Stewart et al. Dolnicar, S, Sh
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2. The research Caroline Stockman a
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Caroline Stockman and Fred Truyen S
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Caroline Stockman and Fred Truyen n
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Caroline Stockman and Fred Truyen s
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PeerWise - The Marmite of Veterinar
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Amanda Sykes et al. recently outlin
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Amanda Sykes et al. activity became
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Amanda Sykes et al. students either
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Category Amanda Sykes et al. Q9 : W
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Amanda Sykes et al. Chang, S-B., Hu
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Nicolet Theunissen and Hester Stubb
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Figure 1: Overall structure Nicolet
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References Nicolet Theunissen and H
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Tone Vold This idea phase was under
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Tone Vold process. A synchronous di
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The Effects of Self-Directed Learni
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Chien-hwa Wang and Cheng-ping Chen
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Usage Cases: A Useful way to Improv
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Cristina Wanzeller and Orlando Belo
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The Virtual Path to Academic Transi
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Julie Watson course overall, with s
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Julie Watson practical and economic
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6. First phase Julie Watson Followi
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Identifying and Locating Frames of
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Ethical approval Katherine Wimpenny
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Katherine Wimpenny et al. SL was a
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Katherine Wimpenny et al. This in t
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Reaction Lecture: Text Messaging to
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Koos Winnips et al. order to make a
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Table 2: Overview of student reacti
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Koos Winnips et al. Students liked
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A Holistic Approach to Instructiona
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Li Zhong Zhang There is a wealth of
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Figure 1: An integrated design fram
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6.1 Design implications Li Zhong Zh
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894
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896
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Nahla Aljojo et al. Adaptive hyperm
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Nahla Aljojo et al. Email: The emai
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Nahla Aljojo et al. Table 3: 16 typ
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Table 7: The results of pairwise co
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Nahla Aljojo et al. fact misleading
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Nahla Aljojo et al. Aljojo, N. & Ad
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Andy Coverdale media and related on
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Andy Coverdale A former interdisci
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Andy Coverdale Whilst new initiativ
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Andy Coverdale the participant inte
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Michael Flavin In a subsequent work
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Michael Flavin labour” nodes) in
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Michael Flavin The lecturer also sp
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Michael Flavin Quality Assurance Ag
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Fortunate Gunzo and Lorenzo Dalvit
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4. Possible scenarios 4.1 Computer
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Fortunate Gunzo and Lorenzo Dalvit
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Collaborative eLearning in a Develo
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Evelyn Kigozi Kahiigi et al. implem
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Evelyn Kigozi Kahiigi et al. includ
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Evelyn Kigozi Kahiigi et al. had ve
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Evelyn Kigozi Kahiigi et al. consid
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Evelyn Kigozi Kahiigi et al. So, H.
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Fabio Serenelli et al. is to identi
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Figure 3: Screenshots of LO3 - Lear
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Managing Essential Processing Foste
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6. Results and analysis Fabio Seren
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Fabio Serenelli et al. Mangiatordi,
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1.2 VLE (Virtual Learning Environme
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Nazime Tuncay and Hüseyin Uzunboyl
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Figure 4 Response Screen Nazime Tun
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Figure 12 An Example of Recorded Vi
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Figure 15 VirtualNeu General Menus
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972
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Liz Falconer and Manuel Frutos-Pere
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Liz Falconer and Manuel Frutos-Pere
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Extreme Scaffolding in the Teaching
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Dan-Adrian German first exposure to
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Benefits and Barriers: Applying eLe
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Simon McGinnes view on demand. OSD
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986
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988
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Olivia Billingham 2010); gains in c
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Olivia Billingham Deneen, L., (2010
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Karin Levinsen et al. conference or
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Karin Levinsen et al. in order to s
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Peps Mccrea professional engagement
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A Framework for Understanding Onlin
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Sónia Sousa et al. little sense re
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Sónia Sousa et al. Figure 4: The e
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Trust in Distributed Personal Learn
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2.2 LePress Sónia Sousa et al. Per
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Sónia Sousa et al. 3. Elicitation
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Breaking Down Barriers: Development
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Karen Strickland et al. qualitative
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Novita Yulianti et al. Research con
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