The purpose of this study was to examine the relationship high schools’ instructional capacities and students’ achievement gains. Designed as a relational screening model descriptive research methods, the data draws upon the statistical data on students’ high school and UPE success scores obtained from Ministry of National Education and Center for Evaluation, Selection and Placement as well as teachers’ responses to the data collection tool in this study. Instructional Capacity Scale (ICS) was the data collection instrument developed by the researchers. ICS has six subscales including instructional management practices, teacher quality, the quality and quantity of curriculum and materials, instructional climate, students’ readiness to learn, and financial resources. The data were analyzed using Multilevel structural equation modeling (ML-SEM) to determine the direct or indirect relationships between dependent variables and independent variables. The findings show that teacher quality and students’ readiness to learn affect the students' achievement directly, while there is an indirect relationship between instructional climate and instructional management practices. There is also evidence to suggest that the previous achievement level of students is the most effective variable to predict academic achievement. The findings have confirmed the model presenting that instructional capacity components affect the academic achievement of the students either directly or indirectly. In this sense, the most effective variance on the students’ academic achievement was the previous academic achievement level (SBS base scores). Several limitations and recommendations for future research are provided.



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