<![CDATA[Purpose: Set Theory is a fundamental yet abstract topic in Discrete Mathematics that often challenges students in connecting mathematical concepts with real-world applications. This study proposes an AI-Assisted Case-to-Project Learning approach that transforms Set Theory learning into marketplace application development while fostering interdisciplinary and digital competencies. Design/methodology/approach: A convergent mixed-methods design was employed involving 50 undergraduate vocational students organised into ten project teams. Students first analysed Set Theory through the Shopee marketplace, then investigated different domestic and international marketplaces before developing simplified marketplace applications using HTML, CSS, JavaScript, and Generative AI. The project integrated Programming, Database Systems, Computer Architecture, and Marketing, with Set Theory serving as the conceptual foundation. Data were collected through competency-based assessment rubrics, project documentation, and application analysis. Findings: All project teams successfully developed functional marketplace applications featuring product catalogues, seller and buyer interactions, digital payment options, and delivery services. The findings demonstrate that students effectively translated abstract Set Theory concepts into authentic digital solutions while Generative AI supported mathematical modelling, programming, debugging, and iterative problem solving. Research limitations/implications: The study was conducted in a single vocational higher education institution, limiting the generalisability of the findings. Practical implications: The proposed approach provides an authentic instructional framework that connects mathematical reasoning with interdisciplinary software development and computational thinking. Originality/value: This study introduces an AI-Assisted Case-to-Project Learning approach that positions Set Theory as the conceptual backbone of marketplace application development, enabling students to integrate mathematical reasoning, Generative AI, and interdisciplinary knowledge in solving authentic problems. Paper type: Research paper]]>
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