May 10, 2024, 4:46 a.m. | Yicheng Yang, Xinyu Wang, Haoming Yu, Zhiyuan Li

cs.CL updates on arXiv.org arxiv.org

arXiv:2405.05513v1 Announce Type: new
Abstract: The increase in academic dishonesty cases among college students has raised concern, particularly due to the shift towards online learning caused by the pandemic. We aim to develop and implement a method capable of generating tailored questions for each student. The use of Automatic Question Generation (AQG) is a possible solution. Previous studies have investigated AQG frameworks in education, which include validity, user-defined difficulty, and personalized problem generation. Our new AQG approach produces logical equivalence …

abstract academic aim arxiv cases college cs.cl cs.dm online learning pandemic question questions shift students type

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