A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning

Author:

Wang Hei-Chia,Chiang Yu-HungORCID,Chen I-Fan

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Education

Reference49 articles.

1. Agarwal M. and Mannem P. (2011). Automatic Gap-Fill Question Generation from Text Books. In Proceedings for the 6th Workshop on Innovative Use of NLP for Building Educational Applications, Portland, Oregon, pp. 56-64.

2. Akben, N. (2020). Effects of the problem-posing approach on students’ problem solving skills and metacognitive awareness in science education. Research in Science Education, 50(3), 1143–1165.

3. Albalawi, R., Yeap, T. H., & Benyoucef, M. (2020). Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis. Frontiers in Artificial Intelligence, 3(42), 1–14.

4. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of machine Learning research, 3, 993–1022.

5. Caspari-Sadeghi, S. (2023). Learning assessment in the age of big data: Learning analytics in higher education. Cogent Education, 10(1), 2162697.

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