Teaching Tax Compliance Using Real Industry Data

Abstract

Traditional taxation education relies heavily on textbook scenarios, theoretical case studies, and hypothetical datasets. While this approach introduces students to tax concepts, it often fails to develop real-world competencies such as filing procedures, compliance analytics, audit documentation, and regulatory interpretation. This paper presents an experiential pedagogical model that integrates real industry data—such as anonymized corporate transactions, GST/VAT filings, payroll records, and financial statements—to improve student readiness for professional taxation roles. The study proposes the Real Data-Driven Tax Learning (RDDTL) framework and demonstrates how real datasets integrated with tax software can enhance compliance accuracy, understanding of tax law applications, and audit preparedness. Challenges including privacy, regulatory constraints, and data standardization are also examined. The findings suggest that real industry data fosters deeper learning, reduces skill gaps, and enhances employability in tax-intensive sectors.