TAX-EdX 2.0: reimagining tax education through TPACK-driven AI-automated SmartTax Auto-Case Builder

Traditional classroom-based tax education in higher learning institutions is commonly delivered through lecture-based and theory-oriented approaches, which limit students’ opportunities to apply taxation knowledge in authentic professional contexts. Consequently, graduates often demonstrate conceptual understanding but lack advisory and analytical competencies required in modern tax environments. Simultaneously, Malaysia’s transition toward mandatory e-Invoicing presents considerable challenges for Micro, Small, and Medium Enterprises (MSMEs), particularly due to limited digital readiness, low tax literacy, and the complexity of compliance requirements. To address these interconnected issues, this study introduces TAX-EdX 2.0, an experiential tax education ecosystem supported by the SmartTax Auto-Case Builder (STAC), a generative artificial intelligence– driven system guided by the Technological Pedagogical Content Knowledge (TPACK) framework. Undergraduate students engage directly with MSME entrepreneurs through structured interviews to evaluate tax compliance practices and e-invoicing preparedness. Interview data are processed using STAC, which automatically extracts themes and generates preliminary narrative case studies that students refine through higher-order analysis. Implemented among a total of 82 undergraduate students enrolled in the Taxation I course, the initiative integrates experiential learning, AI-assisted analysis, and industry engagement to transform students into active knowledge creators. The method simultaneously enhances student learning outcomes, supports MSME digital transition, and establishes a scalable repository of localized tax education case studies for teaching and research purposes.