Aprimorando a experiência de aprendizado em ambientes online massivos: o papel dos sistemas de recomendação

• Wilson M. Sanches FURG
• Fabiana Z. Ferreira FURG
• Paulo J. D. O. Evald UFPel
• André P. Vargas FURG
• Jean L. Bez URI
• Silvia S. da C. Botelho FURG

DOI: https://doi.org/10.5753/sbie.2023.234741

Abstract

Massive environments have been used in education because they provide a large collection of exercises for students. In this paper, a recommendation system is proposed for use as an online judge in massive learning environments. The proposed method recommends problems considering the user’s skills and motivation; that is, it recommends exercises solved by other users with similar skills and motivation. For this purpose, the traditional collaborative filtering method with a similarity measure adapted to the current domain was adopted. The effects of matrix settings using accuracy and recall metrics are analyzed.

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