AI-Driven Assessment of Students: Current Uses and Research Trends

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Abstract

During the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teaching-learning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students. This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies. As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129. The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.

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Sánchez-Prieto, J. C., Gamazo, A., Cruz-Benito, J., Therón, R., & García-Peñalvo, F. J. (2020). AI-Driven Assessment of Students: Current Uses and Research Trends. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12205 LNCS, pp. 292–302). Springer. https://doi.org/10.1007/978-3-030-50513-4_22

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