16 SES 05.5 PS, General Poster Exhibition
General Poster Session during Lunch
Introduction and theoretical framework
Higher education institutions should provide e-learning courses in order to promote high-level learner’s performance. For the facilitation of innovative e-learning courses, we should emphasize on the features of personalization and adaptivity (Tsolis et al., 2010). On this basis, we suggest Adaptive Hypermedia e-Learning Environments (AHeLE) which support personalized learning based on learner’s features (needs, goals, knowledge, preferences, learning styles) (Brusilovsky, 1996, 2001). In addition to these characteristics students’ psychological traits are important factors affecting their performance (Lo, Chan & Yeh, 2011). Moreover, the high dropout rate of e-learning is linked with low rates of self-motivation and self-direction in e-learning (Martinez, 2003). Furthermore, designers should develop e-learning courses which support the learner to avoid the problems of information overload, disorientation, cognitive overload, discontinuous flow, content unreadiness, lack of comprehension (Chen & Ford, 1997; Murray et al., 2000) and to deliver information to users more efficiently and effectively (Lo, Chan & Yeh, 2011). Acknowledging these needs we propose a conceptual framework for aligning Learning Styles (LS) with Self-Regulated Learning (SRL) in order to enhance learner’s performance. In addition, it is difficult to find evidence for the impact of e-learning environments on SRL (Steffens, 2008), we emphasize on self-regulation as an epistemic approach whereby learners set goals for their learning and then attempt to monitor, regulate, and control their behavior (motivations, self-beliefs, cognitive and meta-cognitive strategies, self-management) (Zimmerman, 2000). The proposed conceptual framework provides specific guidelines for exploiting the basic strategies of self-regulation theory for every LS and modeling appropriate learning activities.
Research question: This study is guided by the following research question: How can we align the students’ characteristics of different learning styles with self-regulated strategies in order to design tailored e-learning courses using AHeLE?
Brusilovsky, P. (1996), Methods and Techniques of Adaptive Hypermedia. Journal of User Modeling and User-Adaptive Interaction 1996, n 2-3 Brusilovsky, P. (2001). Adaptive Hypermedia, User Modeling and User-Adapted Interaction, 11, 87-110. Chen, S.Y. and Ford, N.J. (1997). Towards adaptive information systems: Individual differences and hypermedia. Information Research, 3(2). Retrieved June 16, 2006, from http://informationr.net/ir/3-2/paper37.html Dettori G., Persico D., (2007) Indicators of self-regulation in computer supported collaborative learning, In: Uzunboylu H., Cavus N. (eds), Proc. 7th Int. Educational Technology Conference, Near East Univ., Nicosia, North Cyprus, vol.II, pp.148-153. Honey, P. & Mumford, A. (1992). Manual of Learning Styles. Maidenhead, UK, Peter Honey Publications. Lo J., Chan Y., and Yeh S. (2011). Designing an adaptive web-based learning system based on cognitive styles identified online. Computers and Education. 58, 209-222. Martinez, M. (2003). "High Attrition Rates in E-learning: Challenges, Predictors and Solutions", The E-Learning Developers Journal [online], July. Murray, T. Shen, T., Piemonte, J., Condit, C., Thibedeau, J. (2000), “Adaptivity for Conceptual and Narrative Flow in Hyperbooks: the MetaLinks System”, Proceedings of Adaptive Hypermedia (AH 2000), Trento Italy. Pintrich, P.R., Smith, D.A.F., Garcia, T., & McKeachie, W.J. (1991). A Manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning, University of Michigan. Steffens, K. 2008. Technology enhanced learning environments for self-regulated learning: a framework for research. Technology, Pedagogy and Education 17(3), 221–232. Tsolis D., Stamou S., Christia P., Kampana S., Papaloulia T., Skouta M., Tsakalidis A. (2010). “An Adaptive and Personalized Open Source e-Learning Platform”. In the Elsevier Journal Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). San Diego: Academic Press.
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