Extraction of Useful Observational Features from Teacher Reports for Student Performance Prediction-Reference-Cited by-同舟云学术

Extraction of Useful Observational Features from Teacher Reports for Student Performance Prediction

Published:2022 Issue: Volume: Page:620-625
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Fateen Menna^ORCID,Mine Tsunenori^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-11644-5_58

Reference8 articles.

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2. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 (2018)

3. Fateen, M., Mine, T.: Predicting student performance using teacher observation reports. In: The Fourteenth International Conference on Educational Data Mining, pp. 481–486 (2021)

4. Fateen, M., Ueno, K., Mine, T.: An improved model to predict student performance using teacher observation reports. In: ICCE 2021, pp. 31–40 (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)

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