Educational data mining: A survey and a data mining-based analysis of recent works

Author:

Peña-Ayala Alejandro

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference274 articles.

1. Akcapinar, G., Cosgun, E., & Altun, A. (2011). Prediction of perceived disorientation in online learning environment with random forest regression. In Proceedings of the 4th international conference on educational data mining (pp. 259–263).

2. Aleahmad, T., Aleven, V., & Kraut, R. (2010). Automatic rating of user-generated math solutions. In: Proceedings of the 3rd international conference on educational data mining (pp. 267–268).

3. Content-free collaborative learning modeling using data mining;Anaya;User Modeling and User-Adapted Interaction,2011

4. Anaya, A. R., & Boticario, J. G. (2011b). Towards improvements on domain-independent measurements for collaborative assessment. In Proceedings of the 4th international conference on educational data mining (pp. 317–318).

5. Anjewierden, A., Gijlers, H., Saab, N., & De-Hoog, R. (2011). Brick: mining pedagogically interesting sequential patterns. In Proceedings of the 4th international conference on educational data mining (pp. 341–342).

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