Predictor Variables Of Academic Success In Mathematics Under A Binary Logistic Regression Model

Abstract

In recent years, many investigations have been carried out to identify the different factors that influence academic achievement in mathematics. Although the list is extensive and diverse, this paper focuses on determining whether the affective domain, mathematical processes and pedagogical practices influence academic achievement in mathematics. The research considers a quantitative approach at a cross-sectional descriptive level. The sample consisted of 2,450 students from a Colombian department from fourth to eleventh grade (ages 8 to 20 years). The instrument was composed of 90 items that evaluated the affective domain, mathematical processes, pedagogical practices and academic performance, with responses on a five-level Likert scale. The independent variables considered were affective domain, mathematical processes and pedagogical practices, and the dependent variable was academic performance. The adjustment obtained resulted in a binary logistic model, where the categories considered were pass or fail, which allowed 95% of those who passed to be correctly classified, although, at a global level, its effectiveness was close to l 87%. It should be noted that none of the aspects associated with teachers’ pedagogical competencies in their classroom work was significant in constructing the model.