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Regae: Revista de Gestão e Avaliação Educacional
versión On-line ISSN 2318-1338
Resumen
BENEVENTO, Maurilio y MEIRELLES, Fernando de Souza. PREDICTING AND IMPROVING STUDENT PERFORMANCE WITH THE COMBINED USE OF MACHINE LEARNING AND GPT. Regae: Rev. Gest. Aval. Educ. [online]. 2023, vol.12, n.21, e74348. Epub 14-Dic-2023. ISSN 2318-1338. https://doi.org/10.5902/2318133874348.
This research used Machine Learning algorithms combined with GPT to predict and improve students' performance. This approach can have an innovative impact on education and the learning experience. The study adopted a quantitative approach based on experimental research and various techniques. 900 students were processed in 21 algorithms. The results indicated a powerful tool for predicting and improving students' performance, combined with GPT, surpassing other methods. Knowing students' knowledge gaps and providing personalized feedback enables more effective training. This combination can be a valuable tool for enhancing education.
Palabras clave : algorithm; machine learning; GPT; student performance prediction.