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Advances in E-learning-Experiences and Methodologies

E-Mentoring Table 21. Coaching. Best practice in e-mentoring program IMPLEMENTATION (a literature review) RECOMMENDATIONS • Guide the e-mentoring pairs along the relationship, starting with initiation and moving through cultivation, separation, and redefinition (Kram, 1985) • Coach in a networked environment, using messages containing discussion suggestions, mentoring tips, and so forth. • Keep coaching messages short and frequent (weekly or every other week) • Conclude coaching messages by soliciting feedback from the participants • Consider techniques that address the development of the participant’s expectations and role acquisition: - Iterative cycles: give participants the chance to experience different mentors and mentees - Direct facilitation: interaction by a third party, who follows and participates in the mentoring dialogue, assisting, and suggesting - Open access to models: shared electronic workspace that allows mentors and mentees to observe and learn others’ e-mentoring relationships • Deal with lurkers: check all participants know how to post/reply to messages, provide test areas and arrivals areas, have a free-flowing social conferencing area, give participants time to get used to the online environment, provide areas for safe reflections and comments AUTHOR(S) Single & Muller (2005) O’Neill & Harris (2005) Salmon (2000) Table 22. Matching and re-matching. Best practice in e-mentoring program IMPLEMENTATION (a literature review) RECOMMENDATIONS AUTHOR(S) • Grounding in the program’s eligibility criteria MENTOR, 2001 • Choose a matching method: - Participant choice: works best when those available for listing are plentiful and when one group will be recruited before the other group; however, it may give place to inappropriate matching and to participants not having a match - Unidirectional matching: mentees identify preferences for a mentor, the coordinator matches mentees’ preferences with mentors’ characteristics - Bidirectional matching: both mentees and mentors identify preferences for e-mentoring partners, the coordinator takes into account all preferences • Let mentors and mentees know the process by which they will be matched • Allow the participants to review, accept, or reject their e-mentoring partnerships Single & Muller (2005) Table 23. Monitoring. Best practice in e-mentoring program IMPLEMENTATION (a literature review) RECOMMENDATIONS AUTHOR(S) • Consistent and regular communications with staff, mentors, and mentees • Tracking system for ongoing assessment • Written records MENTOR, 2001 • Guidelines for support and conflict resolution • Rationale for the selection of this particular monitoring strategy • Monitor e-mails systematically Ross, 2004

E-Mentoring Table 24. Support, recognition and retention. Best practice in e-mentoring program IMPLEMENTA- TION (a literature review) RECOMMENDATIONS • Formal kick-off • Process for managing grievances, rematching, interpersonal problem solving, handling crises, and bringing closure to the relationships that end prematurely • Ongoing peer support for volunteers • Social gatherings of different groups as appropriate • Ongoing recognition and appreciation • Newsletters of other communications to mentees, mentors, and support staff • Program Web site with a participant guideline posted on it • Keep a closed mentor list, so mentors can get feedback and advice from each other. A moderator prompts early introductions and periodically seeds the list with discussion topics AUTHOR(S) MENTOR, 2001 Single & Muller (2005) Table 25. Closure steps. Best practice in e-mentoring program IMPLEMENTATION (a literature review) RECOMMENDATIONS • Private and confidential exit interviews to debrief the mentoring relationship between mentees and staff, mentors, and staff and mentors and mentees • Clearly stated policy for future contacts between mentors and mentees • Assistance for mentees in defining next steps for achieving personal goals • Organize a formal end to the programs, which might include a celebration and certificates AUTHOR(S) MENTOR, 2001 Table 26. Types of data collected. Best practice in e-mentoring program EVALUATION (a literature review) RECOMMENDATIONS • Obtain benchmarking data after pilot program • During and after the program, collect three types of information: - Involvement data: frequency of interactions, continuation of mentoring relationships for the duration of the program - Formative data: participants’ satisfaction with the program, examinations of the matching protocol and content of the mentoring interactions, which will guide the future enhancement of the program - Summative data: assessment of program goals achieved, which serve as a standard for comparison with a control group (students that do not undergo mentoring), address sustainability and expansion with stakeholder and founders as main audience AUTHOR(S) Single & Muller (forthcoming)

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    Advances in E-Learning: Experiences

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    Table of Contents Preface .........

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    Chapter XIV Open Source LMS Customi

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    Chapter III Philosophical and Epist

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    of constructive and cooperative met

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    Chapter XIV Open Source LMS Customi

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    contents, learning contexts, proces

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    xv these organizations do not get a

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    xvii QuALIty In e-LeArnIng Before t

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    allow that the teachers in training

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    xxi ISO. (1986). Quality-Vocabulary

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    Chapter I RAPAD: A Reflective and P

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    RAPAD in fields such as law, engine

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    RAPAD mystery to the new student. B

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    RAPAD example, whereas Laurillard h

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    RAPAD Ontologically, systems philos

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    RAPAD information related processes

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    RAPAD methods and techniques accord

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    RAPAD 2. An introduction to learnin

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    RAPAD then asked to reflect on and

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    RAPAD Figure 4. A rich picture to h

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    RAPAD Again using techniques from t

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    E-Learning Value and Student Experi

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Integrating Technology and Research

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    Chapter IX AI Techniques for Monito

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    AI Techniques for Monitoring Studen

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    Chapter X Knowledge Discovery from

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Knowledge Discovery from E-Learning

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    Chapter XI Swarm-Based Techniques i

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Swarm-Based Techniques in E-Learnin

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    Chapter XII E-Learning 2.0: The Lea

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    E-Learning 2.0 Table 1. Different s

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    E-Learning 2.0 Figure 1. Difference

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    E-Learning 2.0 where the blog is al

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    E-Learning 2.0 process. Along this

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    E-Learning 2.0 forth, and, of cours

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    E-Learning 2.0 Finally, it is impor

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    E-Learning 2.0 never be a hotchpotc

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    E-Learning 2.0 McPherson, K. (2006)

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    E-Learning 2.0 Rosen, A. (2006). Te

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Telematic Environments and Competit

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    Open Source LMS Customization Intro

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    Open Source LMS Customization or ev

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    Open Source LMS Customization compa

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Figur

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    Open Source LMS Customization Haina

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    Evaluation and Effective Learning p

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    Evaluation and Effective Learning r

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    Evaluation and Effective Learning t

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    Evaluation and Effective Learning m

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    Evaluation and Effective Learning c

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    Evaluation and Effective Learning H

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    Chapter XVI Formative Online Assess

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    Formative Online Assessment in E-Le

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    0 Chapter XVII Designing an Online

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Designing an Online Assessment in E

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Quality Assessment of E-Facilitator

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    Chapter XIX E-QUAL: A Proposal to M

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    E-QUAL is proposed to evaluate the

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    E-QUAL provide competent, service-o

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    E-QUAL 2004; Scalan, 2003) and qual

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    E-QUAL benchmarks address technolog

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    E-QUAL E-learning added two differe

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    E-QUAL Table 6. Application of the

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    E-QUAL Future trends The future of

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    E-QUAL (EQO) co-located to the 4 th

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    E-QUAL SMEs: An analysis of e-learn

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    E-QUAL Meyer, K. A. (2002). Quality

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    Compilation of References Argyris,

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    Compilation of References Biggs, J.

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    Compilation of References Cabero, J

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    Compilation of References Comezaña

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    Compilation of References Downes, S

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    Compilation of References Fandos, M

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    Compilation of References national

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    Compilation of References Hudson, B

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    Compilation of References Harbour.

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    Compilation of References Little, J

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    Compilation of References Metros, S

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    Compilation of References ONeill, K

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    Compilation of References Preece, J

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    Compilation of References Sadler, D

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    Compilation of References Shin, N.,

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    Compilation of References tional Co

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    Compilation of References Vermetten

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    Compilation of References Yu, F. Y.

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    About the Contributors Juan Pablo d

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    About the Contributors part: “An

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    About the Contributors María D. R-

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    About the Contributors Applications

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    Index e-learning tools, automated p

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    Socrates 55 Sophists 55 student-foc

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