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

Shumin Jing, Sheng Li

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.