Estimating the Academic Performance of Secondary Education Mathematics Students: A Gain Lift Predictive Model

Juan-Manuel Trujillo-Torres, Hassan Hossein-Mohand, Melchor Gómez-García, Hossein Hossein-Mohand and Francisco-Javier Hinojo-Lucena
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Juan-Manuel Trujillo-Torres: Department of Didactics and School Organization, Faculty of Educational Sciences, Universidad de Granada (UGR), 18071 Granada, Spain
Hassan Hossein-Mohand: Department of Pedagogy, Faculty of Teacher Training and Education, Universidad Autónoma de Madrid (UAM), 28049 Madrid, Spain
Melchor Gómez-García: Department of Pedagogy, Faculty of Teacher Training and Education, Universidad Autónoma de Madrid (UAM), 28049 Madrid, Spain
Hossein Hossein-Mohand: Department of Pedagogy, Faculty of Teacher Training and Education, Universidad Autónoma de Madrid (UAM), 28049 Madrid, Spain
Francisco-Javier Hinojo-Lucena: Department of Didactics and School Organization, Faculty of Educational Sciences, Universidad de Granada (UGR), 18071 Granada, Spain

Mathematics, 2020, vol. 8, issue 12, 1-21

Abstract: Several socioeconomic, environmental, ethnic, family, and educational factors influence an individual’s academic performance and can determine their school performance in mathematics. Mathematical competence is one of the skills that allow students to build visions of the future from performance in the present. However, the perception that students have of mathematics, in addition to the teacher–student relationship, the classroom, gender, teaching–learning, and motivation are crucial factors for achieving an optimal academic performance and preventing school failure. The aim of the present study was: (1) to examine which variables of the dimensions “Learning Mathematics” and “School Environment” significantly contribute to the marks in the second quarter and quantify their relative importance; (2) to determine the optimal algorithm model for predicting the maximum gain in students’ marks in the second quarter and quantifying it; and (3) to analyze the maximum gain in terms of gender. A total of 2018 high school students in Melilla were included in this cross-sectional study. Mathematical learning and the school environment were assessed using a validated 14-item questionnaire. Gain lift was employed to quantify the improvement in students’ performance. The role of the classroom and teacher–student relationship had a greater influence on mathematics scores than affinity indicators, teaching, study time, teaching resources used, study aids, and motivation.

Keywords: mathematical education; educational innovation; school environment; high school; academic performance; school failure (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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