Jul 2026· Current Psychology· Vol 45· 0 citations· 46 references
TL;DR
Investigation of the adoption of ChatGPT among 409 Italian university students finds that perceived usefulness is the most influential factor, strongly affecting students’ attitudes toward ChatGPT and their intentions to use it, and indirectly influencing its actual use.
Abstract
The rapid advancement of Artificial Intelligence technologies, particularly generative Artificial Intelligence, has revolutionized numerous domains, including education. This study investigates the adoption of ChatGPT, a prominent generative Artificial Intelligence tool, among 409 Italian university students (Mage = 23.24 years, SD = 2.61; 58.3% female) using the Technology Acceptance Model as a theoretical framework. A path analysis model was employed to examine the relationships between Technology Acceptance Model variables influencing ChatGPT’s adoption. Findings suggest that perceived usefulness is the most influential factor, strongly affecting students’ attitudes toward ChatGPT and their intentions to use it, and indirectly influencing its actual use. Perceived usefulness of ChatGPT is higher in students who have positive social norms related to technology use and perceive ChatGPT as easy to use, which, in turn, is predicted by a high level of technology self-efficacy and low level of technology anxiety. The results provide insights for academic institutions on how to facilitate the adoption of ChatGPT, contributing to more inclusive and effective education. Enhancing technology self-efficacy, promoting positive social norms related to technology use, and reducing technology anxiety are crucial for facilitating ChatGPT’s integration into academic settings.
In recent years, artificial intelligence (AI) technologies have become increasingly prominent in education, with ChatGPT emerging as a notable tool that enhances learning experiences. This study explores teachers’ attitudes towards the adoption of ChatGPT as a learning technology, focusing on its potential benefits, limitations and implications for education. A quantitative approach was employed, involving an online survey targeting university educators. The survey assessed teachers’ perceptions of ChatGPT in higher education and identified barriers to its implementation. The conceptual framework integrates elements from the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology and insights from risk perception theory. Data analysis was conducted using Partial Least Squares Structural Equation Modelling with SMART PLS software, ensuring reliability and discriminant validity. Findings indicate that most teachers view ChatGPT as an effective tool for enhancing student motivation, personalised learning and critical thinking. While teaching experience fosters positive perceptions and reduces perceived risks, it does not significantly influence challenges or trust in adoption decisions. Nonetheless, challenges persist, particularly regarding the reliability of information generated by ChatGPT. This study can assist policymakers, educators and technology developers in collaborating to implement practical and ethical AI-enabled tools like ChatGPT. Ultimately, while ChatGPT holds significant potential as an educational technology, its effectiveness hinges on addressing technical and pedagogical challenges.
Latifa Alzahrani· International journal of res...· 0 citations
Chatbots powered by artificial intelligence are becoming a part of higher education, supplementing teaching and learning as well as student services. Nevertheless, there is only limited evidence regarding the factors influencing students’ intention to use these technologies in the Indian higher education context. The influence of performance expectancy, effort expectancy, social influence and perceived trust on students’ intention to adopt artificial intelligence-based chatbot. This study adopted a quantitative research design using a self-administered, structured questionnaire administered to students of Pondicherry University. For data analysis, 477 valid responses were analyzed through IBM SPSS Statistics and SmartPLS after screening. The results demonstrate that performance expectancy was the strongest predictor of chatbot adoption intention, suggesting students are likely to adopt chatbots when they see obvious academic and learning gains. Social influence, perceived trust, and perceived intelligence also significantly and positively impact adoption intention, whereas effort expectancy does not significantly affect students' behavioral intention, implying that ease of use may be less important for digitally literate learners. This study recommends that educational institutions should focus on developing chatbot system programs with high efficiency, elegance and academic aptness while promoting their usage through institutional initiatives alongside peer influence. Combining the factors of the Technology Acceptance Model with artificial intelligence-specific features provides this study with a holistic view and practical advice to increase student acceptance and intent to engage.
Keywords: students; Chatbots; trust; adoption intention
K. Srilekha, Dwi Rama, Krishna Naik et al.· International Journal of Tec...· 0 citations
Investigating factors influencing university students’ acceptance of ChatGPT in English academic writing in Malaysia and those that influenced students’ behavioural intention most revealed that social influence, effort expectancy, and performance expectancy influenced university students’ acceptance of ChatGPT but not facilitating conditions.
Faizah Mohamad, N. Hadi, Z. A. Kadir et al.· International journal of res...· 0 citations
Many students consider statistics one of the difficult subjects to learn throughout their academic period because of many complex theories and statistical analysis methodologies, which can increase anxiety in the learning process. Generative Artificial Intelligence gives birth to ChatGPT, which provides interesting descriptions and allows independent learning. Nevertheless, not enough literature is found regarding the use of ChatGPT in the context of statistics learning, particularly in Indonesia. In this study, we aim to analyze the perceptions of using ChatGPT as a tool in statistics education through Technology Acceptance Model (TAM). A survey with a quantitative approach was conducted with 203 statistics learners (103 females, 100 males) who have already used ChatGPT. To obtain the data, Likert scale questionnaire was used, and PLS-SEM was applied in analyzing data through five constructs of Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude Toward Using (AT), Behavioral Intention (BI), and Actual Use (AU). It was found that all five hypotheses were confirmed, and all relationships between constructs of TAM were positive and significant. Particularly, PEOU significantly affected PU (β = 0.347) and AT (β = 0.255), while AT had the highest impact on BI (β = 0.330). These findings indicate that ChatGPT is perceived as an assisting technological tool for learning statistics, where usability and attitudes of users become very crucial factors.
Siva Nur Samrotissaadah, Kemas Muslim Lhaksmana· Rabit : Jurnal Teknologi dan...· 0 citations
The results highlight the robustness of the extended UTAUT model, where the two constructs become predictors of behavioural intention to use of ChatGPT, indicating students’ dependency on the perceived reasoning of ChatGPT.
Shafinah Farvin Packeer Mohamed, Fauziah Baharom, Haslina Mohd et al.· Journal of Information and C...· 0 citations
This study investigates the factors influencing university students’ decision to use ChatGPT for learning in Hanoi, Vietnam. Drawing on the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, and recent research on generative AI in higher education, the study examines five antecedent groups: student-related factors, ChatGPT characteristics, social influence, technological context, and institutional support. A cross-sectional survey of 289 university students was analysed using SPSS 22, including descriptive statistics, reliability testing, exploratory factor analysis, Pearson correlation, and multiple linear regression. The measurement scales demonstrate satisfactory reliability, with Cronbach’s alpha values ranging from 0.834 to 0.861. Exploratory factor analysis supports a five-factor structure explaining 68.998% of the total variance. The regression model is statistically significant and explains 68.5% of the variance in students’ decisions to use ChatGPT. Student-related factors are the strongest predictor, followed by institutional support, ChatGPT characteristics, and social influence. Although the technological context is positively correlated with the dependent variable, it does not retain a significant unique effect in the regression model. The findings indicate that students’ adoption of ChatGPT is driven less by the general diffusion of AI technology and more by perceived personal usefulness, institutional guidance, and tool-level value. The study offers practical implications for universities, lecturers, AI developers, and policymakers seeking to promote responsible and effective use of generative AI in higher education.
Huyen Thi Thanh Le, N. Nguyen, Dang Hai Le et al.· Journal of Social Science St...· 0 citations
