Web-based Learning Solutions for Communities of Practice

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Visualising the Invisible in Science Centres and Science Museums Figure 11. Raven Test. An example of the standardised test item. Raven 2000; Series 3. monitored the usability by applying the so called HCI-evaluation method which provides a specific feed-back with regard to the subjective feelings related to the technical usability, psychological usability, and the learning experience. RESULTS AND DISCUSSION Usability A major character of any virtual and especially Augmented Reality technology lies in its’ overwhelming effect as visual experience . Especially for a first time, user mostly find the tool effective and exiting, but may also feel frightened or physically unpleasant. A usability evaluation by a questionnaire and interviews (n: 78 students) revealed the following details: The students experienced the Combination of Real & Augmented reality fascinating (mean 5,23; scale 1-7). However, the feed-back could have been even higher. The teenagers did not feel it “very cool”. The Technical usability did receive high scores (mean 8,44; scale 1-10). The best score (9,2) was by the item “dryness in eyes” and even the lowest “visual fatigue” was as high as 7,9. The Psychological usability (mean 6.92; scale 1-10) was not as advantaged as the technical solutions. The lowest score (6.6) was received by the item frustrating – satisfying. Meanwhile the best feed-back was given to the item terrible – wonderful (7.2). The overall results indicated that the students liked the experience and their situation motivation was positive to start the testing of the equipment. Especially the technological comfort was at least adequate. In all the tests above the younger students (aged 11-13 y) gave clearly higher scores about the AReffect than the older students (aged 14-15 y). The difference was in all aspect – Real & Augmented; Technical; Psychological - statistically significant (p< .05). No statistically significant gender differences were found. This is an important result because very often the high-tech or ICT-solutions are classified as male activities. 199
Knowledge Learning: Pre-test High achieving students (who where above the average with their school grades, i.e. A+) unsurprisingly performed better in the pre-knowledge test (see the figure below) compared to average and below-average peers. Therefore, strong correlations applied. The differences between the groups (A- ; Average; A +) were even clearer inside the test group as can be seen from the following figure: The same trend was visible also in the control group as shown in the results in the next figure: Knowledge Learning by ARtechnology: Post-Test Again, high achiever performed clearly best in the post-knowledge test, too (see figure below) However, low achievers were clearly catching up with the others. The difference to their higher achieving peers decreased substantially. The implementation of Augmented Reality in the context of the Hot Air Balloon exhibit unveiled similar results: While the high achiever again did best in the post-knowledge test, low achiever again 200 Visualising the Invisible in Science Centres and Science Museums were clearly catching up with the others. This was especially true for the girls who also managed well in the VRA-Visual Reasoning Ability test. It seems like that visualising very theoretical scientific phenomenon of molecule movement) increased the understanding substantially for pupils who otherwise had severe difficulties. Knowledge Learning: Control Group without AR-Technology The control group attended the science centre exhibition implementation with the same kind of pre- and post-lesson in the school. However, they studied the Hot Air Balloon content in the exhibition in the traditional way (with the text, label, and guide). The results were quite different from the AR-test group (see next figure) since low achievers were not catching up with the others. The following figure confirms that gap between the low-achievers and the students with the higher school grades remained: This is an essential result which needs further analysis. It seems evident that the use and application of the Augmented Reality might give certain advantaged for some of the less-than –average school-success students. Especially the girls were Figure 12. School success vs. Knowledge learning pre-test [scale from 0 to 13]
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www.dbebooks.com - Free Books & mag
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Director of Editorial Content: Kris
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Editorial Advisory Board Anil Aggar
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Table of Contents Preface .........
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Chapter 11 An Organizational Knowle
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Detailed Table of Contents Preface
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Chapter 6 Using Storytelling as the
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Chapter 11 An Organizational Knowle
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Chapter 17 A Process-Oriented and T
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xviii Preface For more than ten yea
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xx (Greece) - by focusing on the pa
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xxii Advances reported in this book
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This chapter discusses the prelimin
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which will ultimately influence the
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Table 2. Facilitator 2 feedback SOL
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“Focus on reading peers’ posts
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• Feedback must be useful and for
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Schunk, D. H., & Lilly, M. W. (1984
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able to others (Wenger, 1998). With
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equire structure transformation att
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are often manually encoded on a cas
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context within the target template.
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tives have been negotiated with CoP
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Brown, H., & Cole, F. C. (1992). Ed
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26 ABSTRACT Chapter 3 Tackling Acce
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Figure 1. Web-based GUI of eLogbook
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Figure 2. System flow for the email
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submission or validation of deadlin
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Figure 7. Body of the email of crea
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The email-based eLogbook interface
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38 Chapter 4 Supporting Communities
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and to the contextualization of thi
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such meetings the CM practitioner n
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non-virtual spaces, candidate tools
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Compendium allows CoP members to cu
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lowing synchronous update of both C
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around the shared goal to enhance t
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community of farmers which is used
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REFERENCES Brown, J. S., & Duguid,
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est attain the educational goal. Th
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And here is where new technologies
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tion of such paths delivers a longe
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Figure 2. A snapshot of an activity
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Figure 3. A view of the course mult
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Henry, G. (2004, September). Connex
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defines a CoP as follows: “Commun
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ested in learning from each other i
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nize clearly how to begin a story,
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Figure 2. Story Development Phases
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Figure 3. Story Designed to move Em
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2. Some differences in JavaScript i
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However, bringing in a new practice
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Backbase. (2008). AJAX in enterpris
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through continuous learning (Rosenb
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do with web-based collaboration sys
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Artificial Intelligence. More preci
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approaches concerning social networ
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REFERENCES Ackerman, M. S. (1998).
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the describing more than one cluste
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eing ‘online’ or ‘offline’
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communication tools, see Weinberger
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learn community booked 147 meetings
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102 Live Virtual Technologies to Su
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Annotating FM text chat transcripts
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community members were discussing t
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chats taking place at this time, on
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ing its course. During an extended
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Dourish, P. (2006). Re-space-ing pl
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INTRODUCTION 114 Individual Learnin
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116 Individual Learning and Emotion
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Emotional Processing 118 Individual
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The Paradigm of CSA 120 Individual
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128 Chapter 10 From ‘Collecting
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aforementioned gap. In particular,
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it into the discussion. This means
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high degree of support for emergenc
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When resources are used in a collab
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Figure 7. Instance of the collabora
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Transformation Rules During the tra
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Grudin, J. (1996). Evaluating oppor
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legitimacy provided by online educa
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have all of the modules implemented
Page 171 and 172: Figure 5. Process used to classify
Page 173 and 174: Table 1. Number and percentage of l
Page 175 and 176: 152 An Organizational Knowledge Cir
Page 177 and 178: CONCLUSION Our practical goal is to
Page 179 and 180: 156 Chapter 12 Using Web-Based Tech
Page 181 and 182: visual clues and the ability to eas
Page 183 and 184: should focus on developing engaging
Page 185 and 186: experience, particularly in an onli
Page 187 and 188: CONCLUSION Distance education repre
Page 189 and 190: Roblyer, M. D., Davis, L., Mills, S
Page 191 and 192: to further increase.” (Allen & Se
Page 193 and 194: Figure 1. in moving from a real-tim
Page 195 and 196: Catalonia, Spain. The institutions
Page 197 and 198: Discussion It is clear that adjustm
Page 199 and 200: Table 3. Adjustment to Teaching Pre
Page 201 and 202: Comparisons between face-to-face an
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Page 207 and 208: Swan, K., & Shih, L.-F. (2005). On
Page 209 and 210: INTRODUCTION Museums of the past so
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Page 213 and 214: Figure 4. The mobile AR system. ©
Page 215 and 216: untold potential, as the individual
Page 217 and 218: in extended episodes of playful lea
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Page 221: spectrum in order to specifically d
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Page 227 and 228: Figure 18. Figure 19. learning appr
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Page 231 and 232: Ilola, L., Lakkala, M., & Paavola,
Page 233 and 234: 210 Chapter 15 A Proposed Framework
Page 235 and 236: 212 A Proposed Framework for Design
Page 253 and 254: 230 Chapter 16 An Agent System to M
Page 255 and 256: common place (Hillery, 1955). The d
Page 257 and 258: the local area. Because of this, as
Page 259 and 260: Figure 3. General architecture cons
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Page 265 and 266: Figure 7. Showing and sorting resul
Page 267 and 268: EVALUATION OF THE PROTOTYPE Once th
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INTRODUCTION 250 A Process-Oriented
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252 A Process-Oriented and Technolo
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exploration and review the attempt
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Defining Features of the IntelCitie
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Figure 1. Integrated eGov services
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portals to merely provide links to
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experiential learning and, therefor
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274 decision-making and develop the
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towards the back-office functions,
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Table 4. Step-wise logic of the ser
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Table 6. Feedback responses to the
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tals, but as particular types of eG
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software consists of a set of enabl
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solve problems associated with the
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ecruitment was organized mainly aro
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The global structure of the activit
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ITPF (during the 2002 crisis) and f
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growth of tax revenue generated som
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and so forth. They confront the cha
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community of practice members. Faci
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It is my belief that these networks
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Tuomi, I. (1999). Corporate knowled
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to accomplish meaningful interchang
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306 Chapter 20 Conditions and Key S
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308 Conditions and Key Success Fact
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330 Compilation of References Abdul
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Balasubramanian, S., & Mahajan, V.
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Buckingham Shum, S. (2007). Hyperme
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Curwell, S., Deakin, M., Cooper, I.
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Dretske, F. (1991). Explaining beha
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Gebert, H., Geib, M., Kolbe, L., Br
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Han, J., & Kamber, M. (2001). Data
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Jain, A. K., & Dubes, R. C. (1988).
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Klijn, E., & Coppenhan, J. (2000).
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Loyarte, E., & Rivera, O. (2007). C
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O’Reilly, T. (2005). What is Web
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Roberts, J. (2006). Limits of commu
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Sharda, N. (2006). Applying movemen
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Tailby, R., Dean, R., Milnerm, B.,
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Wenger, E., White, N., Smith, J., &
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360 About the Contributors empirica
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362 About the Contributors is also
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364 About the Contributors Loïc Me
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366 About the Contributors 1984) he
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368 About the Contributors Christin
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CoPs, key success factors in the cu
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R Reactive Level 236 REGRET reputat
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