Lecomps5: A Framework for the Automatic Building of Personalized Learning Sequences
In the context of distance learning, Adaptive Web-based Educational System focus on personalizationand adaptation, that is on “learner’s satisfaction”. In this paper we address the other side of the coin, that is the "teacher’s satisfaction" problem, which is quite seldom taken into account in educational systems. We present a new version of the Lecomps5 Web-based Educational System, a system capable of providing personalization and adaptation on the basis of learner’s knowledge, learning styles and learning progresses. In this new version, a framework provides the teacher with an easy and flexible tool for managing learning material, expressing different didactic strategies and sequencing personalized courses by means of an embedded planner. Such functionalities are supported by the system basing on evaluations of learner’s knowledge, learning styles, and learning progresses. We report on a first controlled experiment, we made to evaluate the “teacher’s satisfaction”.
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- 1.Bloom, B.S.: Taxonomy of Educational Objectives. David McKay Company Inc. (1964)Google Scholar
- 3.Brusilowsky, P., Vassileva, J.: Course sequencing techniques for large-scale webbased education. International Journal of Continuing Engineering Education and Life-long Learning 13, 75–94 (2003)Google Scholar
- 4.Capuano, N., Gaeta, M., Micarelli, A., Sangineto, E.: Automatic student personalization in preferred learning categories. In: 3rd International Conference on Universal Access in Human-Computer Interaction (2005)Google Scholar
- 7.Felder, R.M., Silverman, L.K.: Learning and teaching styles in engineering education. Engineering Education 78(7) (1988)Google Scholar
- 9.Limongelli, C., Sciarrone, F., Temperini, M., Vaste, G.: LECOMPS5: A Web-Based Learning System for Course Personalization and Adaptation. In: IADIS International Conference e-Learning 2008, Amsterdam, The Netherlands, July 22 - 25 (accepted, 2008)Google Scholar
- 10.Russel, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall, Englewood Cliffs (2003)Google Scholar
- 11.Weber, G., Brusilovsky, P.: Elm-art: An adaptive versatile system for web-based instruction. International Journal of AI in Education 12(4), 351–384 (2001)Google Scholar