Integrating generative AI in management education: A mixed-methods study using social construction of technology theory

Abstract

Generative AI tools are revolutionizing various sectors, including management education, and assessing their effectiveness is crucial to unlock their full potential. The study explores the perspectives of management educators in utilizing Generative AI tools, as they face a dilemma in balancing technology usage while maintaining relevance and fostering authentic learning. This article utilizes the Social Construction of Technology (SCOT) theory, which emphasizes the influence of human interventions and discourses on Generative AI technology. The study utilized a mixed-methods approach to evaluate the impact of Generative AI on teaching-learning compared to the traditional method. Initially, it analyzed news stories and found the frequently used words like management education, ChatGPT, AI, ethics, B-schools etc. in form of word cloud. Further, sentiment analysis of tweets from the ‘X’ platform was conducted to understand the ongoing discussions. The analysis revealed positive and negative emotions which were associated with specific terms related to management education. Thereafter, the qualitative insights gathered from management education experts helped in identifying various focal themes like assessment, curriculum, pedagogy, and regulation considering early adopters' perspectives. The study shed light on how Generative AI tools can be judiciously embraced through research and application and how they can reshape the management education landscape. It provides evidence-based guidance for educators and researchers to effectively utilize this technology while addressing administrative and ethical issues.