Detection of Student Engagement in e-Learning Systems Based on Semantic Analysis and Machine Learning-Reference-Cited by-同舟云学术

Detection of Student Engagement in e-Learning Systems Based on Semantic Analysis and Machine Learning

Published:2020-10-09 Issue: Volume: Page:211-223
ISSN:2367-3370
Container-title:Advances on P2P, Parallel, Grid, Cloud and Internet Computing
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Author:

Toti Daniele,Capuano Nicola,Campos Fernanda,Dantas Mario,Neves Felipe,Caballé Santi

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-61105-7_21

Reference24 articles.

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3. Márquez-Vera, C., et al.: Early dropout prediction using data mining: a case study with high school students. Expert Syst. 33, 107–124 (2016)

4. Olaya, D., Vásquez, J., Maldonado, S., Miranda, J., Verbeke, W.: Uplift modeling for preventing student dropout in higher education. Decis. Support Syst. 134, 113320 (2020)

5. Siemens, G.: Massive open online courses: innovation in education. In: Open Educational Resources: Innovation, Research and Practice, pp. 5–15 (2013)

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