Designing a Learning Matrix for Business Education within a Human–AI Learning Community: A Pedagogical Design Study

Abstract

This study examines the redesign and implementation of a Management Accounting Practice course at a Chinese university during the autumn 2025 semester. Adopting a pedagogical design-study approach, the study draws on learner-context evidence, prior teaching records and reflection, professional digital demands, course-design documents, task and assessment materials, and selected student work. Three design problems were identified: insufficient integration of disciplinary content with digital and intelligent resources; fragmented teaching implementation that limited coherent progression from understanding to analytical application and integrative practice; and an assessment approach that did not adequately capture staged skill development and broader professional growth. In response, a learning matrix was developed around three progressive stages—exploratory understanding, analytical application and integrative practice—and three recurring dimensions of disciplinary knowledge, digital and analytical skills, and professional judgement and decision-making. The matrix was enacted through foundation knowledge practice, project and case learning, integrative practice, differentiated support, and stage-specific use of digital and intelligent tools. Implementation records and an AI-Supported Cost–Volume–Profit (CVP) Decision Lab illustrate how disciplinary reasoning, digital tool use, verification and managerial judgement were connected in practice. The study contributes a problem-to-design framework for integrating digital and intelligent technologies into applied business education while retaining accountable human judgement.