Generative artificial intelligence expectations and experiences in management education: ChatGPT use and student satisfaction

Abstract

Generative artificial intelligence (AI) has witnessed a major boom in recent years and is increasingly penetrating the higher education sector. This study focused on the use of ChatGPT by undergraduate management students. We developed a model called the “AI Student Satisfaction with Studies model” (AI 3S-model) to investigate how generative AI, specifically ChatGPT, affects student satisfaction with their management studies. Factors used in the model included AI-related student expectations, AI-related student job expectations, perceived quality of AI among students, and AI-related overall student satisfaction. An online questionnaire was administered to students from economics faculties at various universities in the Czech Republic. We deliberately focused on one specialized economics college and several large economics faculties. The sample comprised 231 respondents. To analyze the data, we applied covariance-based structural equation modelling using maximum likelihood estimation. Our findings indicate that two factors directly and positively affect overall student satisfaction with AI use: their perceived quality of studies and their expectations. Additionally, perceived quality acts as a significant mediator between student expectations and overall satisfaction, as well as between job expectations and overall satisfaction. Students believe that ChatGPT enhances their quality of education, which boosts their overall satisfaction. For management education programs, this means that finding ways to effectively integrate generative AI into students’ learning and establishing reasonable limits is highly beneficial, whereas prohibiting the use of generative AI tools would likely decrease student satisfaction and diminish the perceived quality of their studies.