Recommender systems as a tool in teaching work: a systematic review

Keywords: Educational improvement, Technological tools, Machine Learning, Semi-automatic meta-analysis

Abstract

This systematic review examines the current state of recommender systems applied in educational work. The research focuses on trends in recommender system development, relevance and areas of opportunity, as well as the importance of delving deeper into these issues in future research. The results show a growing interest in the field, specifically in countries such as the United States, China and Spain, where their educational systems are of high quality, but not in Latin America. It is identified that there is a great interest, in general, in the development and use of novel tools that allow improving education systems, but most of them are not through the use of new technologies, such as recommender systems. In addition, many of the tools reported in the manuscripts reviewed are focused on supporting students and only some of them on supporting teaching, which shows that there is an area of opportunity for the development of tools that support teachers through the use of new technologies. The methodology used was PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), with which 121 manuscripts related to the topic were obtained and which were analyzed semi-automatically using Python.

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Published
2024-01-05
How to Cite
Torres-Herrera, M., Cuaya-Simbro, G., & Canales-Castillo, C. (2024). Recommender systems as a tool in teaching work: a systematic review. Pädi Boletín Científico De Ciencias Básicas E Ingenierías Del ICBI, 11(22), 34-42. https://doi.org/10.29057/icbi.v11i22.11032