Abstract
More than a decade has passed since the start of the MIT OCW initiative, which, along with other similar projects, has been expected to change dramatically the educational paradigms worldwide. However, better findability is still expected for open educational resources and open courseware, so online guidance and services that support users to locate the appropriate such resources are most welcome. Recommender systems have a very valuable role in this direction. We propose here a hybrid architecture that combines enhanced case-based recommending (driven by a quality model tenet) with (collaborative) feedback from users to recommend open courseware and educational resources.
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Vladoiu, M., Constantinescu, Z., Moise, G. (2013). QORECT – A Case-Based Framework for Quality-Based Recommending Open Courseware and Open Educational Resources. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_68
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DOI: https://doi.org/10.1007/978-3-642-40495-5_68
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