Learning Path Recommendation System for Programming Education Based on Neural Networks
Top Cited Papers
- 1 January 2020
- journal article
- research article
- Published by IGI Global in International Journal of Distance Education Technologies
- Vol. 18 (1), 36-64
- https://doi.org/10.4018/ijdet.2020010103
Abstract
Programming education has recently received increased attention due to growing demand for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting this demand. One way to compensate for a shortage of trained teachers is to use machine learning techniques to assist learners. This article proposes a learning path recommendation system that applies a recurrent neural network to a learner's ability chart, which displays the learner's scores. In brief, a learning path is constructed from a learner's submission history using a trial-and-error process, and the learner's ability chart is used as an indicator of their current knowledge. An approach for constructing a learning path recommendation system using ability charts and its implementation based on a sequential prediction model and a recurrent neural network, are presented. Experimental evaluation is conducted with data from an e-learning system.Keywords
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