Integrating AI literacy in solving linear programming problems: A study with prospective teachers using Madura Batik contexts

Abstract

Linear programming is a crucial aspect of optimization mathematics. Prospective mathematics teachers are required to be proficient in solving linear programming problems using graphical methods, the simplex method, and computational technology. However, challenges such as modeling real-world problems, computational complexity, and difficulty understanding graphical visualizations often hinder understanding the material. This study aims to describe the solution of linear programming problems based on the local wisdom of Madurese batik, incorporating AI literacy tools such as ChatGPT, DeepSeek, Grok, Wolfram Alpha, and GeoGebra AI. This study employed a qualitative, descriptive approach. The subjects consisted of 23 prospective teachers, and three representative subjects were selected. The instruments used were a contextual problem of Madurese batik and an interview questionnaire. The results were analyzed and compared with the interview results. The results show that AI helps facilitate prospective teachers in solving linear programming problems. The research findings suggest that AI has transformative potential in mathematics learning for prospective teachers. AI improves efficiency, visual comprehension, flexibility, and confidence. However, challenges such as technological barriers and potential decreases in learning intensity need to be addressed through thoughtful pedagogical design. Prospective teachers must remain meticulous in problem-solving because AI can make mistakes. Prospective teachers may feel the need for intensive learning because problems can be easily solved by AI. AI should be viewed as a tool that supports exploration and understanding, not as a complete substitute for the learning process. Mathematics learning needs to integrate AI as an aid, not a replacement for manual skills.