Análisis de estrategias innovadoras para retención estudiantil con inteligencia artificial: una perspectiva multidisciplinaria

Ester Martín-Caro Alamo

doi:10.31637/epsir-2024-440

Authors

Ester Martín-Caro Alamo Corporación Universitaria de Asturias https://orcid.org/0000-0002-7674-3068

DOI:

https://doi.org/10.31637/epsir-2024-440

Keywords:

higher education, artificial intelligence, machine learning, neural networks, big data, learning analytics, student retention, systematic review

Abstract

Introduction: Higher education is transforming with the adoption of virtual modalities and the integration of technologies such as artificial intelligence (AI), machine learning (ML), neural networks (NN), and big data (BD). These technologies are redefining access and student retention, offering personalized solutions to enhance the educational experience in virtual environments. Methodology: This systematic review, based on the PRISMA method, examines how the interaction of AI, ML, NN, and BD influences the prediction and management of student dropout, highlighting the applications of learning analytics (LA) to improve educational interventions. Results: The results show that AI, ML, and BD are effective in predicting and managing school dropout, allowing for more personalized interventions. Analyzing large volumes of data helps identify crucial patterns for designing retention strategies. Discussion: Despite the significant improvements in personalized learning and resource optimization offered by these technologies, they face ethical and operational challenges that must be considered. Conclusions: The integration of AI, ML, NN, and BD in higher education is a promising approach to enriching the student experience and outcomes, emphasizing the importance of strategic investments and a robust ethical framework for effective implementation.

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Author Biography

Ester Martín-Caro Alamo, Corporación Universitaria de Asturias

Ph.D. in Economic and Business Sciences with a doctoral thesis titled “The Process of Integration of Stock Markets: A Method for Valuing Trading Costs.” She holds an MBA from IESE Business School, University of Navarra. Since joining the Academic Vice-Rectorate of the University Corporation of Asturias, she has published several articles on Online Higher Education.

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