Abstract
We propose ideas for the development of TEL systems which allow for an automatic, dynamic and self-adapting recommendation of curricula from a wide set of available content for an individual user and with regard to a specific purpose. We argue that recommender systems in the prevalent occurrence cannot be used directly in TEL systems, but must be extended by process-related techniques for continuous optimization and adaptation of the generated curriculum.
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References
Albert, D., Hockemeyer, C., Kickmeier-Rust, M.D., Nussbaumer, A., Steiner, C.M.: E-learning based on metadata, ontologies and competence-based knowledge space theory. In: Lukose, D., Ahmad, A.R., Suliman, A. (eds.) KTW 2011. CCIS, vol. 295, pp. 24–36. Springer, Heidelberg (2012)
Ley, T., Kump, B., Gerdenitsch, C.: Scaffolding self-directed learning with personalized learning goal recommendations. In: De Bra, P., Kobsa, A., Chin, D. (eds.) UMAP 2010. LNCS, vol. 6075, pp. 75–86. Springer, Heidelberg (2010)
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Bab, S., Kranich, L. (2013). On Self-adapting Recommendations of Curricula for an Individual Learning Experience. In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds) Scaling up Learning for Sustained Impact. EC-TEL 2013. Lecture Notes in Computer Science, vol 8095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40814-4_65
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DOI: https://doi.org/10.1007/978-3-642-40814-4_65
Publisher Name: Springer, Berlin, Heidelberg
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