Student performance analysis and prediction in classroom learning: A review of educational data mining studies-Reference-Cited by-同舟云学术

Student performance analysis and prediction in classroom learning: A review of educational data mining studies

Published:2020-07-01 Issue:1 Volume:26 Page:205-240
ISSN:1360-2357
Container-title:Education and Information Technologies
language:en
Short-container-title:Educ Inf Technol

Author:

Khan Anupam^ORCID,Ghosh Soumya K.

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Education

Link

http://link.springer.com/content/pdf/10.1007/s10639-020-10230-3.pdf

Reference207 articles.

1. Abrami, P.C., D’Apollonia, S., & Rosenfield, S. (2007). The dimensionality of student ratings of instruction: what we know and what we do not. In The scholarship of teaching and learning in higher education: an evidence-based perspective (pp. 385–456): Springer.

2. Adjei, S.A., Botelho, A.F., & Heffernan, N.T. (2016). Predicting student performance on post-requisite skills using prerequisite skill data: an alternative method for refining prerequisite skill structures. In Proceedings of the sixth international conference on learning analytics & knowledge (pp. 469–473): ACM.

3. Aghabozorgi, S., Mahroeian, H., Dutt, A., Wah, T.Y., & Herawan, T. (2014). An approachable analytical study on big educational data mining. In International conference on computational science and its applications (pp. 721–737): Springer.

4. Agrawal, R., Imieliṅski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. ACM SIGMOD Record, 22(2), 207–216.

5. Ahmed, N.S., & Sadiq, M.H. (2018). Clarify of the random forest algorithm in an educational field. In 2018 international conference on advanced science and engineering (ICOASE) (pp. 179–184): IEEE.

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