Understanding university students’ adoption of ChatGPT: A TAM-based exploration of key factors

The rapid rise of AI chatbots like ChatGPT has spurred growing interest in understanding the factors that influence their adoption, especially in educational settings. This study focuses on identifying the key elements that shape university students’ intentions to use ChatGPT, using the technology acceptance model (TAM) as the theoretical foundation. The research integrates core constructs such as perceived ease of use (PEU), perceived usefulness (PU), perceived risk, trust, and technostress to examine their influence on the intention to use (IU) ChatGPT. Survey data from Indian university students were analyzed using the Smart PLS structural equation modeling technique. The findings reveal significant relationships between PEU, PU, and IU. Specifically, PEU emerged as a strong determinant of both PU and IU, underlining the importance of a user-friendly, intuitive interface in promoting ChatGPT adoption. Additionally, perceived risk was found to negatively impact IU, suggesting that addressing concerns related to privacy and misinformation is crucial for fostering trust and encouraging use. Although technostress had a smaller effect, it still played a notable role, indicating that the stress associated with using new technologies needs to be managed effectively through support mechanisms. Interestingly, trust did not significantly affect IU, challenging assumptions about its role in AI-driven technology adoption. This raises important questions about the specific factors that contribute to trust in such tools. The study’s findings reaffirm the relevance of TAM constructs in understanding ChatGPT adoption while also highlighting the importance of emotional and cognitive factors, such as perceived risk and stress. These findings contribute to the growing academic discussion surrounding AI chatbot adoption and offer actionable insights for AI developers, educators, and policymakers. This research highlights the importance of addressing both technical and emotional factors to ensure broader acceptance and effective use of AI technologies like ChatGPT in learning environments.