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| Research on the Application of AI-Empowered Test Difficulty Assessment: An Empirical Study of the First Law of Thermodynamics |
| Li Peng1，Xin Bingjing2*
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| 1、College of Science, Beihua University, Jilin Jilin 132013；2、School of Resources and Environmental
Engineering, Jilin Institute of Chemical Technology, Jilin Jilin 132022 |
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Abstract In the teaching process, exercise practice constitutes the most critical component. However, the difficulty of exercises varies significantly. To enable teachers to assign homework of appropriate difficulty levels, establishing a scientific difficulty evaluation system is particularly essential. We employs an AI-based difficulty evaluation equation specifically designed for exercises on the First Law of Thermodynamics to classify their difficulty levels. Through testing on the Superstar Learning Platform with two cohorts of students, the difficulty coefficient is calibrated by integrating a correction term ε and student test results, ultimately establishing a scientific and efficient exercise difficulty evaluation system.
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Published: 30 April 2026
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| [1] |
CHEN Li, ZHANG Yu, HAN Yunhua, ZHANG Shuang. Discussion on the Course Reform of Chemical Technology based on the Education and Training of Excellent Engineers in Applied Universities[J]. Journal of Jilin Institute of Chemical Technology, 2025, 42(8): 16-19. |
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LIU Ke-xin, HAO De-cheng, WANG Li, XING Jian, ZHAO Xue. Construction and Practice of a Blended Teaching Model for Engineering Training in a MOOC Environment[J]. Journal of Jilin Institute of Chemical Technology, 2025, 42(8): 6-11. |
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