Neural Network-Based Collaborative Filtering for Question Sequencing

Lior Sidi; Hadar Klein

Neural Network-Based Collaborative Filtering for Question Sequencing

Machine Learning 2020-04-28 v1 Artificial Intelligence Information Retrieval

Authors: Lior Sidi , Hadar Klein

Abstract

E-Learning systems (ELS) and Intelligent Tutoring Systems (ITS) play a significant part in today's education programs. Sequencing questions is the art of generating a personalized quiz for a target learner. A personalized test will enrich the learner's experience and will contribute to a more effective and efficient learning process. In this paper, we used the Neural Collaborative Filtering (NCF) model to generate question sequencing and compare it to a pair-wise memory-based question sequencing algorithm - EduRank. The NCF model showed significantly better ranking results than the EduRank model with an Average precision correlation score of 0.85 compared to 0.8.

Keywords

information retrieval recommendation system nonnegative matrix factorization

Cite

@article{arxiv.2004.12212,
  title  = {Neural Network-Based Collaborative Filtering for Question Sequencing},
  author = {Lior Sidi and Hadar Klein},
  journal= {arXiv preprint arXiv:2004.12212},
  year   = {2020}
}

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