Integrating AI and Sundanese Local Wisdom: A Framework for Culturally Responsive STEM Education

Abstract

This paper proposes a framework for integrating artificial intelligence (AI) with Sundanese local wisdom to create a culturally responsive approach to STEM education. Traditional STEM curricula often fail to engage students by detaching scientific concepts from their cultural context, creating a gap in learning and relevance. This research introduces a pedagogical model centered on a Project-Based Learning (PjBL) module that leverages AI to connect traditional Sundanese knowledge with modern scientific principles. The framework outlines the development of an AI-powered teaching tool designed to facilitate these PjBL modules. The tool uses AI, to analyze and digitize local knowledge like natural cleaning agent (lerak), agricultural practices (kolecer cai) and traditional crafts (ketapel). This data is used to generate culturally relevant project ideas. For instance, students could reverse-engineer the composition in `lerak` to develop a more natural and sustainable cleaning agent, investigating its chemical composition and effectiveness through a series of experiments. The goal is to not only preserve valuable local wisdom but also to foster a deeper understanding of STEM by demonstrating its presence and relevance within the students' own cultural background. Ultimately, this approach builds a more inclusive and effective educational system that respects and empowers indigenous knowledge through a hands-on, project-based learning experience.