Volume Two - Academic Conferences

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Fatemeh Orooji et al. lower and upper levels that should be assigned below the label of "Assign numbers to dimensions" in 0. It also shows that different colors have been proposed for different margins to make them more visually understandable. Second, each modeler may either represent its dimensions independently or organize them as some opposite dimensions. Some questionnaires like Felder-Silverman LS have dimensions that are two by two against each other and must be placed faced by. In this situations, opposite dimensions will be represented as two ends of one axis, shown in 0as "Opposite Dimensions". Figure 6: Phase 4: determine representation of modeler report 4.2 System management tools Proposed unified LS modeling system provides some valuable feasibilities enabling administrators and designers to introduce a new questionnaire as well as altering and removing available modelers. It is possible to define a new questionnaire via the predesigned phases explained before or edit desired features of an available modeler easily. In addition, administrator receives some management specific reports consist of the last version of all activities and the number of users participated, their LSs reports, group LS reports and the average scores of each group. 4.3 System reports Perhaps the most important outcome of this study is that it provides an opportunity for a unified information representation despite the differences between modelers. When learner completes a questionnaire, system analyzes his answers and makes a graphical report representing achieved results in an understandable manner. Our integrated environment reports the name of user’s LSs and his/her scores in a similar manner. In addition, system provides some recommendations based on some given instructional rules due to learner recognized model. To motivate students, we consider each learner situation among the others and compare their learning styles to the average of their community. There are also some other possibilities to compare learners recognized styles against 616
Fatemeh Orooji et al. their popular instructors’ ones which may make them more enthusiastic about their instructors and related course. 5. Results The proposed system has been utilized in the university of Tehran, department of electrical and computer engineering, ECE. At the first step, students of one course have been demanded to fill FLSI and MBTI questionnaires. Almost 40 students have been participated in this study; most of them are at the second year of computer engineering. After processing the results, 25% of students, who had not filled the questionnaire completely, were detected as outliers and put aside. 5.1 Statistical reports Our unified LS modeling system make it available to see the results in a comparable manner. Table 2 shows the average and variances of each questionnaire dimensions. All dimensions have averages about 5-6 except FLSI Visual and MBTI Judgment dimensions which have a greater average. In addition, the variances of all dimensions have values between 4.5 and 5.5 except MBTI Sensing dimension, which has a smaller one, and MBTI Extroversion dimension, which has a greater one. It shows that this group of students are either highly or lowly extrovert while they are less variant in their sensing aspect of their characteristics. Table 2: Statistical Reports of FLSI and MBTI Dimensions FLSI Dimension Active Sensing Visual Sequential Average 5.71 5.54 6.82 5.14 Variance 5.47 5.29 5.19 4.42 MBTI Dimension Extroversion Sensing Thinking Judgment Average 5.11 5.78 5.63 7.15 Variance 8.56 3.79 4.63 4.59 5.2 Correlation analysis Trying to check the consistency and validation of different modelers, we have designed and implemented our unified LS modelers. We wanted to check whether there is any relationship between modelers' dimensions. Table 3 shows the results of the experiments. Table 3: Correlation between FLSI and MBTI dimensions Pearson coefficients between FLSI dimensions Active & Sensing Active & Visual Active & Sequential Sensing & Visual Sensing & Sequential Visual & sequential 0.16 0.14 0.08 -0.12 0.65 -0.06 Extroversion & Sensing Extroversion & Thinking Pearson coefficients between MBTI dimensions Extroversion & Judgment Sensing & Thinking Sensing & Judgment Thinking & Judgment 0.41 -0.49 0.1 -0.30 0.26 0 Sensing & Sensing Pearson coefficients between FLSI & MBTI dimensions Active & Extroversion Active & Judgment Visual & Sensing Sensing & Extroversion Sequential & Thinking 0.3 0.55 -0.04 -0.57 0.17 -0.36 We expected that there would be no correlation between a modeler dimensions since each dimension has a special psychological objective, and as a result, it is naturally expected to be independent from 617
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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
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Freeing Education Within and Beyond
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Chrissi Nerantzi The aim was to exp
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Chrissi Nerantzi agreeing with Nova
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Chrissi Nerantzi familiarisation wi
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Page 86 and 87: Paul Newbury et al. the slides or w
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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
Page 112 and 113: Maruff Akinwale Oladejo and Adelua
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 126 and 127: Adelua Olajide Olawole and Maruff 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
Page 140 and 141: Andy Pulman et al. A key feature of
Page 142 and 143: Andy Pulman et al. in this case “
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
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Page 170 and 171: Figure 5: Screen shot of a user’s
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Page 176 and 177: Kansei Design Model for eLearning:
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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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