Artificial Intelligence for analyzing academic performance in higher education institutions. A systematic literature review
DOI:
https://doi.org/10.29166/catedra.v6i2.4408Keywords:
higher education, artificial intelligence, academic performance, systematic reviewAbstract
Artificial intelligence is constantly evolving and is being applied in several areas, including education. The analysis of the academic performance of students in higher education institutions is a critical issue for decision making and improving the quality of education. The objective of this article is to perform a systematic review of the literature, considering the research that has been developed using artificial intelligence techniques to analyze academic performance in higher education institutions. The scientific databases Web of Science, Scopus, and IEEE Xplore were considered. Keywords related to artificial intelligence and academic performance were considered. Articles published from January 2017 to December 2022 were taken into account, 1427 manuscripts were obtained, from which 74 were selected and analyzed, according to the predefined inclusion and exclusion criteria. Among the results obtained, it can be indicated that the most used techniques for the prediction of academic performance are: neural networks and decision trees. In conclusion, it can be indicated that the application of artificial intelligence can improve the efficiency and accuracy of the evaluation, and provide valuable information for decision making and improvement of the quality of education. In addition, the implications and limitations of these studies are discussed and areas for future research are proposed.
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