A Diagnostic Question Analysis Model based on a Modified Item Response Theory
- 10.2991/978-2-494069-31-2_371How to use a DOI?
- Item Response Theory; Missing Value Prediction; Education Study
Digital technologies are being more widely used in education, allowing students all around the world to access individualized, high-quality educational resources. This paper analyzes a massive amounts of data derived from students’ interactions with these diagnostic questions can help us more accurately understand the students’ learning status and thus allow us to automate learning curriculum recommendations, as evidenced by thousands of examples of students’ answers to mathematics questions provided by The NeurlIPS 2020 Education Challenge [1, 2]. In this paper, a new generated model based on Item Response Theory (IRT) is put forward. Additionally, with discrimination parameter added and classification by groups, the model on real-world dataset is verified.
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Cite this article
TY - CONF AU - Haonan Gao PY - 2022 DA - 2022/12/29 TI - A Diagnostic Question Analysis Model based on a Modified Item Response Theory BT - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) PB - Atlantis Press SP - 3164 EP - 3169 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-31-2_371 DO - 10.2991/978-2-494069-31-2_371 ID - Gao2022 ER -