DEMYTHOLOGIZING DISTANCE LEARNING PLATFORMS

Distance learning software platforms represent a technology opportunity whose potential pedagogical impact still needs to he researched. This paper will refer to our experience using distributed learning environments in different departments (law, computer science, social, political and humanistic s...

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Bibliographic Details
Published inThe International Scientific Conference eLearning and Software for Education Vol. 2; p. 177
Main Authors Fierbinteanu, Cristina, Morariu, Ioan
Format Conference Proceeding
LanguageEnglish
Published Bucharest "Carol I" National Defence University 01.04.2014
Subjects
Distance learning
Educational Media
Educational Quality
Educational Resources
Educational Technology
Online instruction
Pedagogy
Teaching
World Wide Web
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Summary:Distance learning software platforms represent a technology opportunity whose potential pedagogical impact still needs to he researched. This paper will refer to our experience using distributed learning environments in different departments (law, computer science, social, political and humanistic sciences) at Titu Maiorescu University. We are arguing that eLearning platforms can strengthen academia if they are perceived as a supplement for classroom teaching rather than a replacement for it and offer counterexamples to some "eLearning platform myths" that we noticed in our discussions with faculty members. Some of these myths are: distance learning software platforms will fail because face-to-face discussions with professors and fellow students do not work in this format; distance learning software platforms distract faculty who should be focusing on improving their on-campus pedagogy; automatically graded quizzes are not useful in law and humanistic sciences courses; computer supported learning will replace faculty and teaching assistants, thus lowering educational quality. We compare different approaches (Moodle, AeL, social networks), showing their advantages and disadvantages from the perspective of our university's needs and vision. From the same point of view we propose further developments of the platforms considered. Our future work includes the use of inferential statistics techniques to extract information from test results (e.g. which questions are more difficult, which ones test comparable concepts, which ones have better effects on learning outcomes, etc.). This information could then be used by faculty to enhance classroom teaching. We also envisage undertaking multidisciplinary research in order to devise methods to determine the approaches that have better effects on learning outcomes, similarly to the way in which ecommerce sites evaluate user experiences.