Inteligencia artificial para analizar el rendimiento académico en instituciones de educación superior. Una revisión sistemática de la literatura

• Autores: Patricia Jimbo Santana, Laura Cristina Lanzarini, Mónica Jimbo Santana, Mario Raúl Morales Morales
• Localización: Revista Cátedra, ISSN-e 2631-2875, Vol. 6, Nº. 2, 2023 (Ejemplar dedicado a: Revista Cátedra), págs. 30-50
• Idioma: español
• DOI: 10.29166/catedra.v6i2.4408
• Títulos paralelos:
  • Artificial Intelligence for analyzing academic performance in higher education institutions. A systematic literature review
• Enlaces
  • Texto completo
• Resumen
  • español

    La inteligencia artificial se encuentra en constante evolución y se está aplicando en varias áreas, dentro de esta se encuentra la educación.  El análisis del rendimiento académico de los estudiantes en instituciones de educación superior es un tema crítico para la toma de decisiones y el mejoramiento de la calidad de la educación.  El objetivo de este artículo es realizar una revisión sistemática de la literatura, considerando las investigaciones que se han desarrollado utilizando técnicas de inteligencia artificial para analizar el rendimiento académico en instituciones de educación superior.  Se han considerado las bases de datos científicas Web of Science, Scopus, e IEEE Xplore.  Se consideró palabras clave relacionadas con la inteligencia artificial y el rendimiento académico.  Se tomó en cuenta artículos publicados desde enero 2017 hasta diciembre 2022, se obtuvieron 1427 manuscritos, de los cuales se seleccionaron y analizaron 74, según los criterios de inclusión y exclusión predefinidos.  Entre los resultados obtenidos se puede indicar que las técnicas más utilizadas para la predicción del rendimiento académico son: las redes neuronales y los árboles de decisión.  En conclusión, se puede indicar que la aplicación de la inteligencia artificial puede mejorar la eficiencia y precisión de la evaluación, y proporcionar información valiosa para la toma de decisiones y la mejora de la calidad de la educación.  Adicionalmente, se discuten las implicaciones y limitaciones de estos estudios y se proponen áreas para futuras investigaciones.

  • English

    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.

• Referencias bibliográficas
  • Alghamdi, R. A. (2020). Predicting the academic performance of university students using an ensemble classification approach. International...
  • Almaraz Menéndez, F., Maz Machado Carmen López Esteban, A., Almaraz Menéndez, F., Maz Machado, A., y López Esteban, C. (2017). Análisis de...
  • Al-Radaideh, Q., Alsmadi, I., y Al-Ayyoub, M. (2021). Predicting student's academic performance using deep learning techniques: A comparative...
  • Baldino G, Lanzarini L, Charnelli M. (2016). Análisis del avance académico de alumnos universitarios. Un estudio comparativo entre la UTN-FRLP...
  • Barrios-Tao, H., Díaz, V., y Guerra, Y. M. (2021). Propósitos de la educación frente a desarrollos de inteligencia artificial. Cadernos de...
  • Brereton, P., Kitchenham, B. A., Budgen, D., Turner, M., y Khalil, M. (2007). Lessons from applying the systematic literature review process...
  • Castro Benavides, L. M., Tamayo Arias, J. A., Arango Serna, M. D., Branch Bedoya, J. W., y Burgos, D. (2020). Digital Transformation in Higher...
  • Cui, Y., Zhang, Y., y Li, X. (2022). A student performance prediction method based on machine learning algorithms. Wireless Communications...
  • Chiu, T., Xia, Q., Zhou, X., Chai, C., y Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research...
  • Guo, J., Liu, X., y Huang, Z. (2022). A decision tree-based model for predicting academic performance of university students. Journal of educational...
  • Khademi, M., Akbari, M. E., Alizadehsani, R., y Jafari Navimipour, N. (2019). Predicting academic failure of students using decision tree...
  • Kitchenham, B. (2014). Procedures for Performing Systematic Reviews. Keele University Technical Report, 33(2004), 1-26.
  • Liang, X., Wang, S., Sun, L., y Li, J. (2022). An intelligent analysis method for academic performance of students based on deep learning....
  • Liu, Y., Zhang, Z., y Gao, L. (2022). Prediction of students’ academic performance based on support vector machine optimized by artificial...
  • Meng, Q., Hao, J., y Zhang, J. (2021). Applications of artificial intelligence in higher education: a systematic review. Education and Information...
  • Ocaña-Fernández, Y., Valenzuela-Fernández, L. A., y Garro-Aburto, L. L. (2019). Inteligencia artificial y sus implicaciones en la educación...
  • Ouyang, F., y Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence,...
  • Ouyang, F., Zheng, L., y Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from...
  • Olaf Zawacki-Richter*, Victoria I. Marín, Melissa Bond and Franziska Gouverneur, (2019), Systematic review of research on artificial intelligence...
  • Salas-Pilco, S. Z., y Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic review. International...
  • Tien, Y.-C., Lee, Y.-H., y Tsai, C.-C. (2018). Prediction of student performance using an integrated artificial neural network model. Expert...
  • Wang, L., Wang, S., y Zhou, W. (2019). A deep learning model for predicting college student academic performance. IEEE Access, 7, 77499-77510....
  • Wang, R., Liu, M., y Zhu, X. (2022). A Machine Learning-Based Early Warning System for Identifying Students At-Risk of Dropping Out of Engineering...
  • Wang, Y., Zhang, M., y Chen, M. (2022). A decision tree-based method for predicting academic performance of undergraduate students. International...
  • Xiao, J., Zhang, Y., y Wang, H. (2022). An intelligent prediction model for college students' academic performance based on Bayesian network....
  • Xu, W., y Ouyang, A. (2022). The application of AI technologies in STEM education: a systematic review from 2011 to 2021. International Journal...
  • Zhang, H., Ding, Y., y Liu, X. (2019). Predicting the Performance of College Students Based on Machine Learning Algorithms: Evidence from...
  • Zhang, H., Li, L., Li, X., Li, Z., y Liu, B. (2020). The impact of academic performance and learning attitudes on employment of Chinese university...
  • Zhang, J., Liu, Z., y Chen, X. (2022). Research on the prediction of college students' academic performance based on improved decision...
  • Zhang, M., Hu, Y., y Yu, J. (2022). Study on the correlation between college students' academic performance and mental health based on...