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

AAAI 2018 pp. 8095-8096

doi:10.1609/AAAI.V32I1.12187 /aaai/2018/jing2018aaai-contextual/

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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Cite

Text

Jing and Li. "Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12187

Markdown

[Jing and Li. "Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/jing2018aaai-contextual/) doi:10.1609/AAAI.V32I1.12187

BibTeX

@inproceedings{jing2018aaai-contextual,
  title     = {{Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests}},
  author    = {Jing, Shumin and Li, Sheng},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8095-8096},
  doi       = {10.1609/AAAI.V32I1.12187},
  url       = {https://mlanthology.org/aaai/2018/jing2018aaai-contextual/}
}