Abstract
Several researchers study recommendation systems to assist users in the retrieval of relevant goods and services, mostly used in e-commerce. However, there is limited information of the impact of recommender systems in other domains like education. Thus, the objective of this study is to summarize the current knowledge that is available as regards recommendation systems that have been employed within the education domain to support educational practices. By performing a systematic mapping study, a total of 44 research papers have been selected, reviewed and analyzed from an initial set of 1181 papers. Our results provide some findings regarding how recommendation systems can be used to support main areas in education, what approaches techniques or algorithms recommender systems use and how they address different issues in the academic world. Moreover, this work has also been useful to detect some research gaps and key areas where further investigation should be performed, like the introduction of data mining and artificial intelligence in recommender system algorithms to improve personalization of academic choices.
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Rivera, A.C., Tapia-Leon, M., Lujan-Mora, S. (2018). Recommendation Systems in Education: A Systematic Mapping Study. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_89
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DOI: https://doi.org/10.1007/978-3-319-73450-7_89
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