OPTIMIZING LINEAR PROGRAMMING LEARNING WITH VBA EXCEL AND SOLVER COLLABORATION (CASE STUDY: DESIGNING A HEALTHY FOOD MENU WITH 4 VARIABLES)

Abstract

Learning Linear Programming (LP) forms a crucial foundation across various disciplines such as optimization, operations research, and computational science. However, its mathematical complexity and implementation challenges often hinder student comprehension. This study proposes and evaluates an innovative approach to enhance LP learning through collaboration between Visual Basic for Applications (VBA) in Excel and the Solver add-in, using a case study focused on designing a healthy food menu involving four variables with minimal cost. VBA is used to dynamically model the LP problem structure, automate data input, and display results, while Solver is employed to find optimal solutions. The research methodology includes the development of interactive learning modules, the implementation of a quasi-experimental study with control and experimental groups, and analysis of students' conceptual understanding and problem-solving skills. The results indicate that this collaborative approach significantly increases student engagement, deepens intuitive understanding of LP concepts, and enhances their ability to formulate and solve real-world optimization problems—particularly in the given case study of composing a healthy menu at minimal cost. The integration of familiar technology such as Excel, combined with VBA's automation capabilities and Solver's computational power, proves to be an effective pedagogical tool for bridging the gap between theory and practice in LP education.