A Systematic Literature Review on the Implications of Educational Recommender System in Teaching Learning Environment
A Systematic Literature Review on the Implications of Educational Recommender System in Teaching Learning Environment |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-4 |
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| Year of Publication : 2023 | ||
| Author : Neeti Pal, Omdev Dahiya |
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| DOI : 10.14445/22315381/IJETT-V71I4P218 | ||
How to Cite?
Neeti Pal, Omdev Dahiya, "A Systematic Literature Review on the Implications of Educational Recommender System in Teaching Learning Environment, " International Journal of Engineering Trends and Technology, vol. 71, no. 4, pp. 203-212, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I4P218
Abstract
The education sector has drastically changed from offline to online mode in the past few years. Educational data mining, learning analytics, and machine learning are the fields that continuously process, monitor, analyse, predict performances, and display learning outcomes. Selecting an appropriate course still is the biggest challenge for learners. Recommendations can improve the learning process of learners and enhance their performance by providing appropriate learning objects. Informal learning requires special attention to the applications of recommender systems, which can guide learners through learning paths to achieve specific knowledge. This paper is a systematic review of the study of recommendation systems. The purpose of this study is to find out all the existing recommender systems that support the teaching/learning environment, its various techniques/approaches for implementation, and evaluation measures for measuring the quality and accuracy of the recommendation framework. This SLR methodology gives an opportunity to develop novel recommender system techniques in order to enhance the learning process of learners by giving them relevant learning objects.
Keywords
Educational data mining, Learning analytics, Recommender systems, Course recommendations, Deep learning.
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