Every computer system requires a software engineering process, however, educational recommender systems have a different engineering process since being a computer system requires a software design and structure phase in which the structure of a database is established, This motivated the development of the present research work with the purpose of updating knowledge and determining in which stages of the development process of a recommender system the recommendation approaches, the artificial intelligence algorithms, as well as the evaluation metrics used to validate the performance of these systems are used. The comprehensive review methodology, which combines qualitative and quantitative research results to provide a more complete understanding of the research topic, allowed us to evaluate more than 80 research studies related to educational recommender systems and to identify the joint use of software development and data mining methodologies in the implementation of recommender systems, as well as artificial intelligence algorithms such as classification and optimization algorithms to improve the results of the evaluation of the recommendations obtained in the system.

Authors:
Margarita Aucancela, Universidad de Salamanca, Spain
Alfonso González, Universidad de Salamanca, Spain
Pablo Chamoso, Universidad de Salamanca, Spain

About the Presenter(s)
Professor Margarita Aucancela is a University Postgraduate Student at Universidad de Salamanca in Spain

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