Application of Artificial Intelligence in Case-Based Teaching: A Qualitative Study in MBA Education
Year: 2026
Type: article
Abstract: This study examines the incorporation of artificial intelligence (AI) into case-based teaching (CBT) within Master of Business Administration (MBA) programs in China, amidst the rapid digital transition in higher education. Guided by the Context–Input–Process–Product (CIPP) evaluation framework, the study adopted a qualitative design and conducted semi-structured interviews with five instructors from three core MBA courses. The findings indicate that AI enhanced classroom interaction and reduced teachers’ workload by supporting real-time feedback and dynamic discussion processes. Institutional support, including teacher training, digital infrastructure, and technical assistance, was recognized as a vital facilitator of effective implementation. Despite its various benefits, the study also identified shortcomings in AI-generated material, particularly in subject-specific depth and the potential for misleading outputs. Rather than replacing teachers, AI was found to serve as a cognitive instrument and pedagogical support tool, highlighting the continuing importance of teacher expertise and professional judgment. This study contributes to current discussions on AI-assisted pedagogy by providing empirical insights into teacher and AI collaboration in MBA case-based teaching.
Authors: Tianjiao Xu, Mohd Nazir Bin Zabit
Institution: Sultan Idris Education University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7204206491