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Revista Lasallista de Investigación

versión impresa ISSN 1794-4449

Resumen

DIAZ-MARTINEZ, Marco Antonio; AHUMADA-CERVANTES, María de los Angeles  y  MELO-MORIN, Julia Patricia. Decision Trees as a Methodology to Determine Academic Performance in Higher Education. Rev. Lasallista Investig. [online]. 2021, vol.18, n.2, pp.94-104.  Epub 14-Mar-2022. ISSN 1794-4449.  https://doi.org/10.22507/rli.v18n2a8.

Introduction.

This article presents the results of the Decision Trees research as a methodology to determine academic performance in higher education.

Objective.

Explain the academic performance of students taking subjects related to programming at a higher-level institution located in the urban area of Pánuco, Veracruz, Mexico. Academic performance presents a situation that not only concerns educational institutions, but also students, parents, teachers, and principals. It can be mentioned that this also presents a world situation and that it is investigated in different areas of knowledge.

Materials and methods.

A questionnaire was applied to 341 students distributed in the second, fourth and sixth semester. Two statistical modeling techniques were used: decision tree and multiple linear regression, to define which independent variables are associated with academic performance.

Results.

It is located that the learning variables in the classroom and the external tutorials are related to the academic performance variable and that 48.1 % of the students need some academic support or external training to reinforce the programming.

Conclusions.

It is recommended to implement improvement strategies to reduce the work overload of the students. Also make an awareness before applying the survey and that the questionnaires are applied on test dates since the students are at high levels of stress. Future research could evaluate the effect on academic, economic and cultural performance.

Palabras clave : Academic performance; statistical modeling; academic stress; decision tree and linear regression.

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