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Advances in E-learning-Experiences and Methodologies

RAPAD university

RAPAD university preparation course. Each iteration played an important role in the overall development of the methodology and its emergence as a tool which could be used with a broad range of general students as in the university preparation course, Learning at University. With the more general type of course exemplified by the Learning at University course, an initial concern was the apparently large potential difference in the likely skills available to each group in terms of developing the e-learning environment as Web site. There was an emphasis throughout the process that this was not a technical or technology-based process, but one of reflection and design. The form and content of the environment is given far greater emphasis that the technical “bells and whistles” that can be added using technology, no matter how valuable its contribution may be. To this end, the current generation of Web development tools such as FrontPage (and even, at a stretch, Word) and their associated tutorials provide an initial set of pages which can be developed with relative ease. The experience for the student continues to vary enormously in terms of success and frustration, but increasing familiarity with personalizing mobile phone interfaces adds to the confidence of many students. The sense of achievement in having developed a personal e-learning environment and the associated skills is often mentioned as one of the tangible benefits by the students in the feedback survey. The combination of RAPAD and the cognitive profile instruments afford a framework and a set of processes for enabling students to engage with their own and other profile elements and apply them in a reflexive manner to a practical design exercise. It is a complex scenario, but the repeated failure of many quasi experimental attempts to uncover significant relationships between learning measures and learning material presentation (or interface design) suggested a need for a more sophisticated approach to e-learning systems design. Several major studies have concluded that there is a need to consider the process as well as the outcomes and that the qualitative data provided by student comments are the most useful sources of explanatory data. Systems theory and a systems approach enabled this and helped the concept of flexible student alignment to emerge with the production of adaptive personalized e- learning environments. Flexible student alignment focuses on the learner and considers alignment from the student perspective. As suggested above, a close fit and tight-coupling between the student and the PELE as e-learning support system plus the facility for loose coupling and flexibility between the PELE and the university as e-learning environment enables students to better align themselves with the different teaching-learning environments encountered. In this way, using RAPAD to enable flexible student alignment allows the student to exercise individual flexible alignment. This is an important characteristic when considering the many and varied teaching-learning environments and other university e-learning support systems likely to be encountered by each student. The concept of process reengineering in the information systems field draws on the idea that developments in new information and communications technologies allow us to do many things in fundamentally different ways than previously. Instead of using the technology just to further improve how something is done, reengineering suggests we look for ways of reconceptualising how things are done. The use of an iterative, participatory process for effective technology design is part of this reconceptualisation. The student becomes a central part of the technology design process, whether as specialist (e.g., HCI) student or, with more help, pre- or first year university student. In doing so, each individual actively engages with fundamental aspects of his or her learning in ways that produce a valuable e-learning environment plus improved metacognitive and self-regulatory characteristics. The use of RAPAD produces a PELE as an effective

RAPAD e-learning support system and the student and e-learning environment combine to form an efficient learning support system for e-learning and lifelong learning. This chapter has presented the background, content, and empirical use of the RAPAD methodology. Definitions and key terms were provided and followed by a section which discussed the need for new and personalised approaches for supporting e-learning. The changing conceptions of learning and the complexity of learning were considered. In order to provide a coherent overview of the work, a systems perspective of the student, methodology, and PELE as a learning system was presented. The concept of Flexible Student Alignment was then introduced before the need for human-centred e-learning systems design and participatory design was outlined. The development of RAPAD as a participatory methodology was then summarized. This was followed by a broad description of the research phases and empirical work which comprised the development of RAPAD as an e-learning methodology. Future trends were then suggested before concluding points were made. Future reseArch dIrectIons In terms of future research directions developments, several prospects exist to develop RAPAD and take the personalized e-learning environment forward. These include developing advanced adaptive virtual environments. The enormous success and developments in alternative digital environments such as Second Life (http://secondlife.com) suggest that this is possible and likely. Developing the skills of learning and gaming and integrating them with mobile virtual environments means that e-learning environments can become more personalised, powerful, and accessible. Other developments include matching its form and content to the additional cognitive preferences of individual students. Developments in auditory and visual digital data offer exciting opportunities to personalize the environments in more effective ways. Software agents, part of an earlier iteration of the work, have developed and become more mainstream. Their potential for the gathering, filtering, and selection of relevant learning information and materials has been enhanced by their increased use for these purposes in the business arena. The use of XML (eXtensible Markup Language) will enable software agents to better match the content of documents to the cognitive preferences of the individual student. All of these examples represent the potential for research and development in fertile areas. Cognitive, Virtual, and organisational Interfaces Subsequent work has suggested that students can use personal cognitive profile knowledge to develop a series of different but individually related e-learning interfaces. Each interface serves a separate but important function in helping the student to develop a series of strategies for interfacing with the university at different levels—the personal, the virtual, and the organisational. The first interface would operate at the level of self-awareness. Here the knowledge and understanding of an individual’s cognitive profile would provide a framework in which that individual can better formulate a series of learning strategies (based on, for example, subject, course, year, semester, unit, etc.). These learning strategies would then become part of the learning resources on which the student can draw. The second interface operates at a more functional level and consists of a Web-based interface for information management purposes. The development of the first interface will help inform the design and development of the second interface. In addition, besides being structured around the individual student’s cognitive profile, the awareness of preferences in terms of the format and content of educational materials helps each student to interact more effectively with learning materials.

  • Page 2 and 3: Advances in E-Learning: Experiences
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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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    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 Haina

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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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    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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    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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