Abstract
Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile.
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Sun, G., Cui, T., Beydoun, G., Chen, S., Xu, D., Shen, J. (2017). Organizing Online Computation for Adaptive Micro Open Education Resource Recommendation. In: Xie, H., Popescu, E., Hancke, G., Fernández Manjón, B. (eds) Advances in Web-Based Learning – ICWL 2017. ICWL 2017. Lecture Notes in Computer Science(), vol 10473. Springer, Cham. https://doi.org/10.1007/978-3-319-66733-1_19
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DOI: https://doi.org/10.1007/978-3-319-66733-1_19
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