A Multilevel Causal Model of Factors Influencing Mathematical Thinking of Grade 9 Students under the Secondary Educational Service Area Office
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Abstract
The research article aimed at the following objectives: 1) to examine the factors influencing mathematical thinking among Grade 9 students under the Secondary Educational Service Area Office; and 2) to develop and validate a multilevel causal model of these factors using Multilevel Structural Equation Modeling (Multilevel SEM). The population consisted of 228 school administrators, 3,628 mathematics teachers, and 12,416 students. The sample included 120 administrators, 139 mathematics teachers, and 470 students, selected through stratified random sampling. Data were collected using a mathematical thinking assessment and questionnaires measuring the influencing factors. Statistical analyses included means, percentages, standard deviations, skewness, kurtosis, and Pearson correlation coefficients. The analysis was conducted using Mplus 8.3.
The results indicated that, at the school, classroom, and student levels, the variables had high mean scores, with low to moderate standard deviations, approximately normal distributions, and acceptable skewness and kurtosis, suggesting a general consensus among respondents. The developed multilevel SEM model integrated factors across the three levels to explain students’ mathematical thinking. Model fit indices (χ²/df, CFI, TLI, RMSEA, SRMR) indicated a good fit with empirical data. The model accounted for a high proportion of variance in mathematical thinking (R² = 71-88%), demonstrating that school management, teaching quality, and students’ affective factors collectively play a significant role in the development of students’ mathematical thinking skills.
The new knowledge regarding factors influencing students’ mathematical thinking at the multilevel dimension indicates that mathematical thinking is affected both directly and indirectly by school management quality and teaching quality. This influence occurs through classroom climate and learning approaches that promote deep thinking. The model accounts for a high proportion of variance in mathematical thinking, highlighting its significance for integrated educational quality development. Specifically, it emphasizes the importance of academic leadership of administrators, teacher instructional quality, and student motivation as key factors for sustainably enhancing mathematics teaching and learning.
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