Predicting academic performance of university students from multi-sources data in blended learning
Author:
Affiliation:
1. Pontifical Catholic University of Ecuador
2. University of Oviedo-Spain
3. University of Córdoba - Spain
Funder
European Union
Principality of Asturias
Department of Science and Innovation (Spain)
Publisher
ACM Press
Reference10 articles.
1. M. Tayebinik and M. Puteh. 2012. Blended Learning or E-learning?, Imacst, 3(1), 103--110.
2. P. Blikstein. 2013. Multimodal learning analytics. In Proceedings of the third international conference on learning analytics and knowledge, 102--106.
3. X. Ochoa. 2017. Multimodal learning analytics. The Handbook of Learning Analytics. Handb. Learn. Anal. 129--141.
4. Khaleghi, B., Khamis, A., Karray, F. O., & Razavi, S. N. (2013). Multisensor data fusion: A review of the state-of-the-art. Information fusion, 14(1), 28--44.
5. C. Romero, S. Ventura. 2013. Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3(1): 12--27.
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