Prediction of Students’ Performance in E-learning Environments Based on Link Prediction in a Knowledge Graph-Reference-Cited by-同舟云学术

Prediction of Students’ Performance in E-learning Environments Based on Link Prediction in a Knowledge Graph

Published:2022 Issue: Volume: Page:432-435
ISSN:0302-9743
Container-title:Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium
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Author:

Ettorre Antonia^ORCID,Michel Franck^ORCID,Faron Catherine^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-11647-6_86

Reference5 articles.

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3. Corbett, A.T., Anderson, J.R.: Knowledge tracing: modeling the acquisition of procedural knowledge. User Model. User-Adap. Inter. 4(4), 253–278 (1994)

4. Feng, M., Heffernan, N., Koedinger, K.: Addressing the assessment challenge with an online system that tutors as it assesses. User Model. User-Adap. Inter. 19(3), 243–266 (2009)

5. Piech, C., et al.: Deep knowledge tracing. In: Advances in Neural Information Processing Systems, vol. 28, pp. 505–513 (2015)

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