AI-Assisted Cost and Management Accounting Education: Redesigning Case-Based Learning for Decision-Making Competence
Against the backdrop of the digital transformation of the accounting profession, this paper reports a teaching reform that integrates artificial intelligence (AI) into case-based learning in the undergraduate course Cost and Management Accounting. The reform addresses four persistent problems of traditional case teaching: static and outdated case resources, passive student participation, the absence of dynamic decision-making training, and a widening gap between curriculum training and industry demand. Drawing on constructivism, Kolb’s experiential learning cycle and competency-based education, the course was redesigned around an “AI-optimised resources—AI-assisted processes—AI-enabled evaluation” framework, and decision-making competence was operationalized into five assessable dimensions: cost data analysis, variance interpretation, alternative evaluation, risk anticipation, and integrated managerial judgment. The redesigned model was implemented over one semester, and preliminary evidence based on classroom observation, case report analysis, and student feedback indicates broader classroom participation, improved case report quality, and positive student perceptions; a systematic evaluation of its effects on course achievement and decision-making competence is planned as the next step of this ongoing reform. The paper further discusses implementation challenges, including uneven AI literacy among teachers and students, academic integrity and assessment redesign, and proposes corresponding optimization strategies, offering a replicable paradigm for AI-enhanced accounting education in undergraduate programs.
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