Web-based Learning Solutions for Communities of Practice

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An Organizational Knowledge Circulation Management System For Universities Figure 1. Mission of the center for research and developing e-Learning Figure 2. Knowledge circulation management system DBs as shown in Fig.2. Instructional knowledge is constructed by extracting information from learning design repository and assessment knowledge is constructed by extracting information from content DB and learning log DB. This knowledge stored in relational DB and is used by instructors in daily e-learning activities. At the current stage, the learning activity integration system does not 145
have all of the modules implemented. However we have already developed several modules of knowledge circulation management system, in the next section we introduce these modules. Mentoring System It is difficult to sustain e-Learning activities. Thus regular mentoring for learners is important to keep their motivation to learn. However, to be able to give all learners advices on demand is costly in terms of time and effort required from lectures. Therefore automating mentoring activity is beneficial. Motivated by this we have developed auto-mentoring system. We define “auto-mentoring system for supporting lecturers” as a system in which it is possible to extract targets by learning from LMS log data and then sending mentoring messages automatically. Architecture The first version of our mentoring system supports learning activities in a course. In the next version Figure 3. Architecture of mentoring system 146 An Organizational Knowledge Circulation Management System For Universities we plan to support learners in their courses by also answering their questions or pointing out their weak points. The outline of the first version of mentoring system is shown in Fig.3. In the beginning, an instructor creates rules for learner classification and message construction. These rules are stored in a DB for further reuse (Fig. 3). Extracting target module matches leaning log data with production rules of learner classification module and extracts target learners who may need mentoring messages. Then sending message module creates appropriate messages for target learners and asks the instructor to verify them. In case instructor allows mentoring system to send messages to targets learners, sending message module then sends them to target learners. Learning activities of each learner are recorded in leaning log data base through LMS WebClass- RAPSODY. An example of how e-Karte learners go through this process is shown in Fig.4.
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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).
Page 117 and 118: the describing more than one cluste
Page 119 and 120: eing ‘online’ or ‘offline’
Page 121 and 122: communication tools, see Weinberger
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Page 125 and 126: 102 Live Virtual Technologies to Su
Page 127 and 128: Annotating FM text chat transcripts
Page 129 and 130: community members were discussing t
Page 131 and 132: chats taking place at this time, on
Page 133 and 134: ing its course. During an extended
Page 135 and 136: Dourish, P. (2006). Re-space-ing pl
Page 137 and 138: INTRODUCTION 114 Individual Learnin
Page 139 and 140: 116 Individual Learning and Emotion
Page 141 and 142: Emotional Processing 118 Individual
Page 143 and 144: The Paradigm of CSA 120 Individual
Page 151 and 152: 128 Chapter 10 From ‘Collecting
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Page 161 and 162: Figure 7. Instance of the collabora
Page 163 and 164: Transformation Rules During the tra
Page 165 and 166: Grudin, J. (1996). Evaluating oppor
Page 167: legitimacy provided by online educa
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 205 and 206: 11. Ensure that instructors and stu
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
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8 at the left shows a real experime
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spectrum in order to specifically d
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Knowledge Learning: Pre-test High a
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eceiving better learning results. T
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Figure 18. Figure 19. learning appr
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The teachers felt that the visit to
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Ilola, L., Lakkala, M., & Paavola,
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210 Chapter 15 A Proposed Framework
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212 A Proposed Framework for Design
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230 Chapter 16 An Agent System to M
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common place (Hillery, 1955). The d
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the local area. Because of this, as
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Figure 3. General architecture cons
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Deliberative-Social Level In this l
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- The person uses knowledge previou
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Figure 7. Showing and sorting resul
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EVALUATION OF THE PROTOTYPE Once th
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support knowledge management but it
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Malhotra, Y. (2000), «Knowledge Ma
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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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Curwell, S., Deakin, M., Cooper, I.
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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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