Student-Level, Classroom-Level and School-Level Factors as Predictors of Undergraduate Mathematics Students’ Achievement in Vector Analysis

This study investigates student-level, classroom-level, and school-level factors that predict students’ achievement scores in vector analysis, and determines the achievement score of students using the regression equation. A total of 243 third-year undergraduate mathematics students from a university in Ghana, participated in the study. The study adopted a correlational design with a multiple regression model, to identify significant predictors. For model 1, the student-level factors explained 56.0% of the variance (R²=.56, F (36,206) =133.06, p < .05), with fourteen significant predictors.  For model 2, the student-level and classroom-level factors explained 61.0% of the variance (R²=.61, F (39,203) =124.92, p <.05), with fifteen significant predictors. For model 3, the student-level, classroom-level and school-level factors explained 62.0% of the variance (R²=.62, F (41,201) =120.86, p <.05), with sixteen significant predictors. The study concludes that students whose parents’ educational level and socio-economic status are high, have a greater chance of improving their mathematics achievement scores.

Citation: Charles K. Assuah (2021) Student-Level, Classroom-Level and School-Level Factors as Predictors of Undergraduate Mathematics Students’ Achievement in Vector Analysis, International Journal of Education, Learning and Development, Vol. 9, No.7, pp.16-37

Keywords: Achievement, correlational design, predictors, variance