Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests

Authors

  • Shumin Jing University of Iowa
  • Sheng Li Adobe Research

Keywords:

Collaborative Filtering, Student Response Prediction, Item Response Theory

Abstract

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). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/12187