The big data revolution is an exciting opportunity for universities, which typically have rich and complex digital data on their learners. It has motivated many universities around the world to invest in the development and implementation of learning analytics dashboards (LADs).
It recently came to my attention that I was waging a war across multiple fronts and fatigue had struck — they were winning. For months I had battled, fighting their persistence with my propensity to click x.
Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction.
M. Tavakoli, A. Faraji, M. Molavi, S. Mol, and G. Kismihók. (2021)cite arxiv:2112.12100Comment: This paper has been accepted to be published in the 12th International Learning Analytics and Knowledge (LAK'2022), March 21--25, 2022. ACM.
L. Mai, A. Köchling, and M. Wehner. Proceedings of the 13th International Conference on Computer Supported Education, SCITEPRESS - Science and Technology Publications, (2021)
M. Molavi, M. Tavakoli, and G. Kismihók. (2020)cite arxiv:2006.11109Comment: Editted version of this paper has been accepted to be published in the proceedings of The European Conference on Technology-Enhanced Learning (EC-TEL) 2020 by Springer (Lecture Notes in Computer Science (LNCS) Series).
M. Tavakoli, S. Mol, and G. Kismihók. (2020)cite arxiv:2005.07465Comment: This paper has been accepted to be published in the proceedings of CSEDU 2020 by SciTePress.