In response to the heightened demands placed on accounting professionals in the era of big data, and the need to cultivate students’ capacities in big data analysis and digital literacy, this study proposes an innovative approach to teaching financial big data analysis courses rooted in the Outcome-based Education (OBE) framework. Addressing prevalent issues in current teaching practices, such as inadequate alignment with real-world business scenarios, students’ lack of a strong sense of purpose in their learning, and rigid assessment methods, the research undertakes a thorough optimization of the course structure. By carefully considering institutional context, student requirements, and market dynamics, the study refines course objectives, reconfigures instructional content and resources, and advocates for teaching mode innovation and assessment reform. Resulting from these efforts is a comprehensive teaching model that seamlessly integrates “theoretical exposition, practical business scenario analysis, hands-on Python demonstrations, and task-oriented exercises”. Grounded in a pedagogical logic that emphasizes an instructional approach “digging deep into a single case”, this model significantly enhances students’ proficiency in accounting practices, data analysis techniques, business acumen, and data literacy.
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Shi et al. (2024) studied this question.
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