Análisis Genético en Objetos de Aprendizaje: La enseñanza personalizada del álgebra.

Resumen

This article presents a specific overview of algebra learning among students at the National Technological Institute of Mexico, Apizaco Technological Institute, analyzing the main difficulties in achieving accreditation in different algebra-related subjects. It also presents a detailed analysis of the software used in classroom sessions to strengthen student learning. Finally, it presents a genetic analysis of performance on monomial exercises solved using a learning object called "Components of Mixed Monomials," employing a focused genetic algorithm to identify error patterns and propose personalized recommendations to students. The responses to 200 exercises were analyzed, identifying that fractional coefficients accounted for 49.5% of the total errors. The genetic algorithm achieved an accuracy of 85.62% in predicting success, selecting 8 out of 12 characteristics as critical. The research findings demonstrate that time management and the handling of fractional coefficients are the most determining factors in the performance of this learning object.