Using Similarity Learning with SBERT to Optimize Teacher Report Embeddings for Academic Performance Prediction-Reference-Cited by-同舟云学术

Using Similarity Learning with SBERT to Optimize Teacher Report Embeddings for Academic Performance Prediction

Published:2023 Issue: Volume: Page:720-726
ISSN:1865-0929
Container-title:Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky
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Author:

Fateen Menna^ORCID,Mine Tsunenori^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-36336-8_111

Reference7 articles.

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2. Fateen, M., Mine, T.: Predicting student performance using teacher observation reports. In: International Educational Data Mining Society (2021)

3. Fateen, M., Mine, T.: Extraction of useful observational features from teacher reports for student performance prediction. In: International Conference on Artificial Intelligence in Education, pp. 620–625. Springer, Heidelberg (2022). https://doi.org/10.1007/978-3-031-11644-5_58

4. Fateen, M., Ueno, K., Mine, T.: An improved model to predict student performance using teacher observation reports. In: Proceedings of the 29th International Conference on Computers in Education Conference, ICCE (2021)

5. Murphy, L., Thomas, L.: Dangers of a fixed mindset: implications of self-theories research for computer science education. In: Proceedings of the 13th Annual Conference on Innovation and Technology in Computer Science Education, pp. 271–275 (2008)