A personalized test paper generation model for English examination based on knowledge tracking

Ya Zhou; Xiuli Shao; Guimin Huang; Qingkai Guo; Nanxiao Deng; Jianxing Lin

doi:10.1117/12.3009521

16 October 2023 A personalized test paper generation model for English examination based on knowledge tracking

Ya Zhou, Xiuli Shao, Guimin Huang, Qingkai Guo, Nanxiao Deng, Jianxing Lin

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128030H (2023) https://doi.org/10.1117/12.3009521
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

In recent years, personalized paper grouping is a hot research topic in the field of intelligence education. In this paper, we propose an optimized deep knowledge tracking model Mul-MAKT combined with a genetic algorithm for personalized paper grouping with English practice as the target. Firstly, we use students’ records (exercise labels, response results, learning behaviors, exercise attributes) as input to the knowledge tracking model to predict students’ performance at the next moment and also to obtain students’ mastery level of knowledge points. Based on the students’ mastery levels, we adjust the students’ ability in each type of English exercise and calculate the students’ weaknesses in each type of question, so as to extract the questions from the test bank with the difficulty matching the students’ ability and containing the students’ weaknesses.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ya Zhou, Xiuli Shao, Guimin Huang, Qingkai Guo, Nanxiao Deng, and Jianxing Lin "A personalized test paper generation model for English examination based on knowledge tracking", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128030H (16 October 2023); https://doi.org/10.1117/12.3009521

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