Reform of Teaching Methods for Big Data and Accounting Programs in Higher Vocational Colleges Driven by New Quality Productivity

Abstract

To align with the transformative trends of the digital and intelligent era and effectively meet the escalating demands of new-quality productivity development, teaching methodologies in big data and accounting programs at higher vocational colleges require urgent and comprehensive reform. This paper begins by systematically examining the fundamental restructuring of professional competencies driven by the emergence of new-quality productivity. It provides a detailed, multidimensional analysis of the updated competency requirements across three critical domains: advanced data governance and intelligent analysis, seamless industry-finance integration and process reengineering, as well as rigorous technological ethics and risk compliance. Furthermore, the study comprehensively identifies and evaluates the structural challenges inherent in current pedagogical approaches, including outdated curriculum frameworks, inadequate practical training design, ineffective evaluation mechanisms, and superficial industry-academia collaboration. Building upon this robust analytical foundation, the paper proposes an integrated, forward-looking reform strategy. This strategic framework encompasses the complete restructuring of curriculum models, the development of a dynamic practical training ecosystem, the implementation of innovative and multifaceted evaluation paradigms, and the deepening of industry-academia symbiosis to foster sustainable educational partnerships. Ultimately, this research aims to offer highly practical and actionable references for higher vocational colleges, guiding them in establishing resilient teaching models for big data and accounting that perfectly align with the core developmental principles of new-quality productivity and future workforce requirements.