OPTIMIZING THE ALLOCATION OF INSTRUCTIONAL TECHNOLOGY RESOURCES TO MAXIMIZE PRIMARY SCHOOL STUDENTS' MATHEMATICAL LEARNING OUTCOMES USING LINEAR PROGRAMMING

This study investigates the optimization of instructional technology resource allocation in primary schools to enhance students' mathematical learning outcomes using Linear Programming (LP). With a focus on both urban and rural schools, the research aims to formulate an LP model to maximize the effective use of available resources such as digital devices, software licenses, and instructional time. A mixed-methods approach was employed, including surveys, interviews, classroom observations, and secondary data analysis to assess current resource allocation practices. The LP model was designed to allocate resources efficiently within constraints such as budget limits, time, and available technology. Results indicate a significant improvement in student performance, with urban schools showing a 28.57% increase and rural schools showing a 25% increase in math achievement after the implementation of the optimized resource allocation. The study highlights disparities in resource availability between urban and rural schools and demonstrates the potential of the LP model to address these disparities, even in resource-constrained settings. The findings suggest that effective resource optimization can lead to improved educational outcomes, especially in schools with limited budgets. This research also emphasizes the importance of teacher training in technology integration and the need for continuous monitoring and evaluation of resource allocation practices. The study’s implications extend to educational policy, suggesting that LP-based models could inform more equitable and efficient distribution of educational resources.

This study investigates the optimization of instructional technology resource allocation in primary schools to enhance students' mathematical learning outcomes using Linear Programming (LP). With a focus on both urban and rural schools, the research aims to formulate an LP model to maximize the effective use of available resources such as digital devices, software licenses, and instructional time. A mixed-methods approach was employed, including surveys, interviews, classroom observations, and secondary data analysis to assess current resource allocation practices. The LP model was designed to allocate resources efficiently within constraints such as budget limits, time, and available technology. Results indicate a significant improvement in student performance, with urban schools showing a 28.57% increase and rural schools showing a 25% increase in math achievement after the implementation of the optimized resource allocation. The study highlights disparities in resource availability between urban and rural schools and demonstrates the potential of the LP model to address these disparities, even in resource-constrained settings. The findings suggest that effective resource optimization can lead to improved educational outcomes, especially in schools with limited budgets. This research also emphasizes the importance of teacher training in technology integration and the need for continuous monitoring and evaluation of resource allocation practices. The study’s implications extend to educational policy, suggesting that LP-based models could inform more equitable and efficient distribution of educational resources.