Enhancing mathematics teachers’ contextualization of mathematics content in welding and fabrication trade Area Using ChatGPT AI and Meta AI

Abstract Mathematics is the foundation of all TVET trade areas, particularly welding and fabrication. However, linking mathematics concepts to the welding and fabrication trades remains a challenge in the literature. To address this gap, this study investigated the potential use of ChatGPT AI to assist mathematics teachers in contextualising mathematics examples and tasks in the welding and fabrication trades. An exploratory case study research design was used to investigate the feasibility and effectiveness of using ChatGPT and Meta AI to contextualise mathematics examples and tasks in the welding and fabrication trade area. All welding and fabrication-related mathematics concepts were chosen based on the American Welding Society's fabrication mathematics I and II, as well as the Mathematics Curriculum for Welders (Northeast Wisconsin Technical Colleges). Two mathematics teachers searched ChatGPT AI and Meta AI for specific examples and questions about the various concepts in welding and fabrication at a TVET second cycle institution. Experts in the welding and fabrication trades assessed the output. The data was analysed using both content and thematic analyses. The findings revealed that both ChatGPT and Meta AI generated mathematics tasks and examples demonstrating the contextualisation of mathematics content in the WF trade area. Furthermore, the findings revealed that contextualise problems are consistent with specific mathematical competencies required in the WF trade area and meet the cognitive demand level for students in the WF trade area. This novel approach can thus improve students' understanding and application of mathematical concepts in the context of their trade, eventually bridging the gap between theory and practice in vocational education.