@inproceedings{090bced5ddfb4ff09d03fb5fb34ca843,
title = "Generating Contextualized Mathematics Multiple-Choice Questions Utilizing Large Language Models",
abstract = "Applying mathematics to solve authentic question play important roles in math-ematics education. How to generate high-quality multiple-choice questions that have authentic context is a great challenge. By combining multiple iterations of large language model dialogues with auxiliary external tools and the LangChain framework, this work presents a novel method for automatically generating contextualized multiple-choice mathematics questions. To check the quality of generated questions, 30 questions were randomly selected and 13 human experts were invited to rate these questions. The survey result indicates that the questions produced by the proposed method exhibit a significantly higher quality compared to those generated directly by GPT4, and are already quite comparable in performance to questions that are meticulously crafted by humans across multiple dimensions. The code is available on the project home page: https://github.com/youzizzz1028/MCQ-generation-Chain.",
keywords = "Automatic Question Generation, ChatGPT, Core Literacy, LangChain, Prompt Engineering",
author = "Ruijia Li and Yiting Wang and Chanjin Zheng and Jiang, \{Yuan Hao\} and Bo Jiang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 25th International Conference on Artificial Intelligence in Education, AIED 2024 - Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky ; Conference date: 08-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.1007/978-3-031-64315-6\_48",
language = "英语",
isbn = "9783031643149",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "494--501",
editor = "Olney, \{Andrew M.\} and Irene-Angelica Chounta and Zitao Liu and Santos, \{Olga C.\} and Bittencourt, \{Ig Ibert\}",
booktitle = "Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky - 25th International Conference, AIED 2024, Proceedings",
address = "德国",
}