Generating Contextualized Mathematics Multiple-Choice Questions Utilizing Large Language Models
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64315-6_48
Reference11 articles.
1. Chen, W.: Program of thoughts prompting: disentangling computation from reasoning for numerical reasoning tasks. arXiv preprint arXiv:2211.12588 (2022)
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3. Grévisse, C.: Comparative quality analysis of GPT-based multiple choice question generation. Int. Conf. Appl. Inform., 435–447. Springer Nature Switzerland (2023). https://doi.org/10.1007/978-3-031-46813-1_29
4. Kurdi, G.: A systematic review of automatic question generation for educational purposes. Int. J. Artif. Intell. Educ. 30, 121–204 (2020)
5. Lee, U.: Few-shot is enough: exploring ChatGPT prompt engineering method for automatic question generation in English education. Educ. Inf. Technol., 1–33 (2023). https://doi.org/10.1007/s10639-023-12249-8
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