Passwords of Student Mathematics Achievement: Investigating Student and Teacher Characteristics with Hierarchical Linear Modeling

This study examined the effects of student- and teacher-level characteristics on students’ mathematics achievement using Hierarchical Linear Modeling (HLM). The primary aim was to identify the influence of variables at both levels on mathematics performance. The two-level HLM analysis included 12 mathematics teachers and their 413 students. Students’ end-of-semester mathematics grades were used as the measure of achievement. The findings revealed that the most significant predictors of mathematics achievement were student-level variables, with parental education, mathematics self-efficacy, and gender emerging as key factors. At the teacher level, mathematics anxiety and marital status were found to have significant effects on student achievement. The results demonstrated that a substantial proportion of the variance in mathematics achievement was explained by student-level variables, while the remaining variance was attributable to teacher-level factors. These findings highlight that mathematics achievement is shaped not only by individual differences but also by classroom and teacher-level influences.