USING NEURAL COLLABORATIVE FILTERING TO PERSONALIZE ONLINE LEARNING CONTENT

Authors

  • Novianty Djafri Universitas Negeri Gorontalo, Indonesia
  • Kasmudin Mustapa Universitas Tadulako, Indonesia
  • Arnes Yuli Vandika Universitas Bandar Lampung, Indonesia

Keywords:

Neural Collaborative Filtering, online learning content

Abstract

Personalization of learning is a strategy used to determine the characteristics of learners so they can learn effectively. There are many approaches that can be taken to personalize learning. This system for personalizing learning content in the form of recommendations for online learning content was built using the Neural Collaborative Filtering method and utilizes a collection of implicit feedback data taken from student activity records when interacting with online learning content as reference data to produce recommendations. The design of a learning content personalization system in the form of recommendations on online learning content for students using the Neural Collaborative Filtering method has been successfully built and can run well in online learning content. The literature study approach was used to conduct the research. Data and relevant information were gathered through a review of the literature using Neural Collaborative Filtering to personalize online learning content. This research discusses traditional methods in personalizing online learning content, Neural Collaborative Filtering, relevant previous research, and the implementation of Neural Collaborative Filtering in online learning content.

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Published

2024-03-23

How to Cite

Novianty Djafri, Kasmudin Mustapa, & Arnes Yuli Vandika. (2024). USING NEURAL COLLABORATIVE FILTERING TO PERSONALIZE ONLINE LEARNING CONTENT. Indonesian Journal of Education (INJOE), 4(1), 170–183. Retrieved from https://www.injoe.org/index.php/INJOE/article/view/110

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