Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests
DOI:
https://doi.org/10.1609/aaai.v32i1.12187Keywords:
Collaborative Filtering, Student Response Prediction, Item Response TheoryAbstract
The purpose of this study is to design a machine learning approach to predict the student response in mixed-format tests. Particularly, a novel contextual collaborative filtering model is proposed to extract latent factors for students and test items, by exploiting the item information. Empirical results from a simulation study validate the effectiveness of the proposed method.
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Published
2018-04-29
How to Cite
Jing, S., & Li, S. (2018). Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.12187
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Student Abstract Track