Modelo predictivo de las metas de aproximación al dominio: un análisis con IA

Francisco Quiñonez Tapia; María de Lourdes Vargas Garduño

doi:10.24320/redie.2026.28.e10.6555

Authors

Francisco Quiñonez Tapia University of Guadalajara https://orcid.org/0000-0002-7371-0690
María de Lourdes Vargas Garduño Universidad Michoacana de San Nicolás de Hidalgo https://orcid.org/0000-0002-7384-3098

DOI:

https://doi.org/10.24320/redie.2026.28.e10.6555

Keywords:

educational goal, achievement motivation, intercultural communication, educational psychology, student educational

Abstract

The objective of this study was to use artificial intelligence (AI) to predict mastery-approach goals in secondary school students based on variables from the PISA 2018 database. The sample consisted of 339,560 participants from 60 countries. Machine learning was used with the Super Learner mega-algorithm with 14 candidate algorithms. In addition, deep learning was used with a neural network with 107 parameters. The analyses showed that students’ perceived parental emotional support, competitiveness, purpose in life, self-efficacy, and knowledge of intercultural communication were predictors of mastery-approach goals in secondary school students. This research contributes to the study of factors that influence mastery-approach goals in secondary school students, with analysis models that advance the development of the science of AI-based predictive education.

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