RAPAD Figure 4. A rich pi

RAPAD Figure 4. A rich picture to help clarify learning support needs and PELE design The Rich Picture has been described as a “tool for reasoning about work context” (Monk & Howard, 1998) and both the technique and the methodology have been applied to educational scenarios by several authors and practitioners in addition to Checkland, its originator (Briggs, 2003; Kassabova & Trounson, 2000; Patel, 1995). In the systems development unit, the students were asked to reflect and comment on the perceived learning support needs of different types of student (undergraduate, pos-graduate, part-time, fulltime, etc.). After various exercises and discussion in the context of systems development they were asked to produce a Rich Picture of their own situation with respect to learning support resources and systems. Again, the concept of the Learning Resource Centre was used to illustrate and aid this exercise. The examples produced illustrated a variety of individual perspectives of how different students see themselves acting and interacting within the context of the university as e-learning environment––very much a personalized viewpoint. The students then used their Rich Pictures to define the PELE as a system in systems development terms (see below). Phase Four: the “Learning at University” Unit For the fourth phase of RAPAD’s development saw the methodology developed and restructured for less technologically experienced students. The reflective and participatory model developed in the previous three phases—including the cognitive profile, Rich Pictures, and personalised e-learning environment—was introduced as a pre-university unit that formed the central unit of a university preparation course for more than 400 pre-university students. This development represented an attempt to change the unit or course from one format—study skills based, nonelectronically supported—to a format which is supported by Blackboard Learner Management System. The course syllabus (see Table 1) adapted and used the model presented above to develop the metacognitive and self-regulatory skills of the students about to enter university life and to help enable e-learning and lifelong learning. The differences between 64 predominantly third year students doing a Level 3 unit in “Human Computer Interaction” and more than 400 pre-university

RAPAD students completing a “Learning at University” unit are significant. However, the exercise proved very successful and by the second iteration of the course the methodology as unit was successfully integrated with Blackboard and the unit assessment practices. This phase also provided additional data and material for consideration in the development of the RAPAD as a methodology to enable students to reconceptualize their learning within e-learning environments. “Learning at University”: Participatory methodology and unit as a Learning system The research has a practical focus. It was always intended that the research and methodology would provide the basis of several short courses and also longer units if possible. The main target group were first year students and it was hoped that short courses could be provided in the first semester, although it was recognised that the best time could be before commencing university study. A variety of courses, including one half-day, one day, and one week courses were designed for students (and staff in one case), but there were difficulties with fitting into the current diet of study skills courses. However, an opportunity did arise with the redevelopment of a series of university preparation units to integrate the material into a keystone unit for a university preparation course. This unit, Learning at University, was aimed at helping students to understand their own learning more full and thus to help provide the individual metacognitive skills and strategies necessary for each student to more fully benefit from the other units comprising the course. The methodology and the unit can also be seen as parts of a learning system designed and developed to help the student to develop as an autonomous learner. This is within the context of the different systemic demands of mass higher education (educational and social). In Banathy’s (1999) terms of key entity, key function, and organising the education for learning outcomes (i.e., of the learning system), we have the following: • The key entity is the student • The key function is to enable autonomous e-learning • How to “organize the education for attaining the best possible learning outcomes?" is achieved via the current and proposed implementation of the “Learning at University” unit Figure 5. Conceptual model of “Learning at University” as a learning system 0

Page 2 and 3: Advances in E-Learning: Experiences
Page 4 and 5: Table of Contents Preface .........
Page 6 and 7: Chapter XIV Open Source LMS Customi
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Page 16 and 17: xv these organizations do not get a
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Page 20 and 21: allow that the teachers in training
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Page 32 and 33: RAPAD Ontologically, systems philos
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Page 46 and 47: RAPAD university preparation course
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Page 52 and 53: RAPAD AddItIonAL reAdIngs Goodyear,
Page 54 and 55: A Heideggerian View on E-Learning t
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E-Mentoring Table 10. Ethical impli
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E-Mentoring Table 15. Technology st
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E-Mentoring Table 21. Coaching. Bes
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E-Mentoring Table 27. Moment. Best
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E-Mentoring Moreover, existing rese
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E-Mentoring Kasprisin, C. A., Singl
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E-Mentoring Ensher, E. A., Heun, C.
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Chapter V Training Teachers for E-L
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Training Teachers for E-Learning FL
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Training Teachers for E-Learning ne
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Training Teachers for E-Learning A
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Training Teachers for E-Learning yo
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Training Teachers for E-Learning Di
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Training Teachers for E-Learning ht
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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The Role of Institutional Factors i
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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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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 p
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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 national
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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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