J 2025

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

SUCHÁNEK, Petr and Mária KRÁLOVÁ

Basic information

Original name

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

Name in Czech

Literatura o event managementu: zkoumání chybějícího korpusu znalostí

Authors

SUCHÁNEK, Petr and Mária KRÁLOVÁ

Edition

Journal of Innovation & Knowledge, THOUSAND OAKS, CA 91320 USA, SAGE PUBLICATIONS INC, 2025, 2530-7614

Other information

Language

English

Type of outcome

Article in a journal

Field of Study

50200 5.2 Economics and Business

Country of publisher

Spain

Confidentiality degree

is not subject to a state or trade secret

References:

Impact factor

Impact factor: 15.500 in 2024

Marked to be transferred to RIV

Yes

Organization unit

Ambis University

EID Scopus

Keywords in English

Generative artificial intelligence (AI);ChatGPT;Management studies;Student satisfaction;AI student satisfaction with studies model

Tags

Changed: 2/3/2026 12:14, Ing. Kateřina Lendrová

Abstract

In the original language

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 stu- dents 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 esti- mation. 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 gener- ative 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.