Background: In recent years, the use of artificial intelligence (AI) in education has increased worldwide. The launch of the ChatGPT-3 posed great challenges for higher education, given its popularity among university students. The present study aimed to analyze the attitudes of university students toward the use of ChatGPTs in their academic activities. Method: This study was oriented toward a quantitative approach and had a nonexperimental design. An online survey was administered to the 499 participants. Results: The findings of this study revealed a significant association between various factors and attitudes toward the use of the ChatGPT. The higher beta coefficients for responsible use (β=0.806***), the intention to use frequently (β=0.509***), and acceptance (β=0.441***) suggested that these are the strongest predictors of a positive attitude toward ChatGPT. The presence of positive emotions (β=0.418***) also plays a significant role. Conversely, risk (β=-0.104**) and boredom (β=-0.145**) demonstrate a negative yet less decisive influence. These results provide an enhanced understanding of how students perceive and utilize ChatGPTs, supporting a unified theory of user behavior in educational technology contexts. Conclusion: Ease of use, intention to use frequently, acceptance, and intention to verify information influenced the behavioral intention to use ChatGPT responsibly. On the one hand, this study provides suggestions for HEIs to improve their educational curricula to take advantage of the potential benefits of AI and contribute to AI literacy.

This systematic review examined, through the UTAUT2 model, the factors influencing the acceptance of artificial intelligence (AI) applications in university contexts. A total of 50 scientific texts published between 2018 and 2023 were analyzed and selected after a rigorous search of specialized databases. These findings confirm the versatility of UTAUT2 in elucidating technological adoption processes in higher education. Performance expectancy and hedonic motivation emerged as significant predictors of intentions and effective use among students, faculty, and administrative staff. Among students, perceived ease of use and social influence were also relevant. The analysis revealed differences in adoption patterns between STEM and non-STEM disciplines and between public and private institutions. Despite widespread positive perceptions of AI's potential, barriers such as distrust and lack of knowledge persist. The research also identified moderating and mediating factors, such as prior technology experience and technological self-efficacy. These results have important implications for the implementation of AI in higher education, suggesting the need for differentiated approaches according to the characteristics of each group and institutional context. It is recommended to develop strategies that address the identified barriers and leverage facilitators, with an emphasis on training, ethical design, and contextual adaptation of AI applications. Future research should explore the longitudinal evolution of these factors and examine AI adoption in non-STEM disciplines in greater depth.

Artificial intelligence (AI) has been integrated into higher education (HE), offering numerous benefits and transforming teaching and learning. Since its launch, ChatGPT has become the most popular learning model among Generation Z college students in HE. This study aimed to assess the knowledge, concerns, attitudes, and ethics of using ChatGPT among Generation Z college students in HE in Peru. An online survey was administered to 201 HE students with prior experience using the ChatGPT for academic activities. Two of the six proposed hypotheses were confirmed: Perceived Ethics (B = 0.856) and Student Concerns (B = 0.802). The findings suggest that HE students’ knowledge and positive attitudes toward ChatGPT do not guarantee its effective adoption and use. It is important to investigate how attitudes of optimism, skepticism, or apathy toward AI develop and how these attitudes influence the intention to use technologies such as the ChatGPT in HE settings. The dependence on ChatGPT raises ethical concerns that must be addressed with responsible use programs in HE. No sex or age differences were found in the relationship between the use of ChatGPTs and perceived ethics among HE students. However, further studies with diverse HE samples are needed to determine this relationship. To promote the ethical use of the ChatGPT in HE, institutions must develop comprehensive training programs, guidelines, and policies that address issues such as academic integrity, privacy, and misinformation. These initiatives should aim to educate students and university teachers on the responsible use of ChatGPT and other AI-based tools, fostering a culture of ethical adoption of AI to leverage its benefits and mitigate its potential risks, such as a lack of academic integrity.

ChatGPT, a large language model AI, has the potential to transform higher education by providing students with personalized learning support, assisting in writing tasks, and enhancing their level of engagement. This study examines the factors influencing the acceptance of ChatGPT among university students in Peru, following the extended UTAUT2 model with the addition of a construct called knowledge sharing (KS). A total of 772 students from seven universities in Lambayeque and La Libertad participated in an online survey, providing insights into their perceptions and experiences with using ChatGPT for academic purposes. The results from the structural equation model showed that effort expectancy, behavioral intention, and knowledge sharing positively influenced the actual use of ChatGPT. Furthermore, effort expectancy and performance expectancy were found to be determinants of the behavioral intention to use ChatGPT. The study also revealed that performance expectancy and behavioral intention serve as sequential mediating variables regarding the effect of effort expectancy on actual use. These findings suggest a positive adoption of ChatGPT among students, driven by individual and contextual factors, and highlight the importance of managing effort and performance expectations appropriately. This study represents a significant advancement in understanding the acceptance of ChatGPT in higher education and provides valuable guidance for practical implementation efforts, ensuring that this powerful AI tool is effectively leveraged to support student learning and success.

This study examines the determinant factors influencing artificial intelligence (AI) adoption among university teachers and its impact on teacher leadership and concerns. Through a quantitative cross‐sectional study involving 452 professors from six public and private universities in northern Peru, the research tested six hypotheses regarding the relationships between attitudes toward AI, constructivist pedagogical beliefs, facilitating conditions, and teaching modality. Data were collected via validated instruments and analyzed via structural equation modeling (PLS‐SEM). The results revealed that attitudes toward AI ( β = 0.529, p < 0.001) and constructivist pedagogical beliefs ( β = 0.253, p < 0.01) significantly influence AI adoption, whereas facilitating conditions have no significant effect. The study also revealed that AI use strongly impacts teacher leadership ( β = 0.711, p < 0.001) and teacher concerns ( β = 0.597, p < 0.001). However, teaching modality did not significantly moderate the relationship between attitudes and AI use. The model showed robust explanatory power, with AI use explaining 50.5% of the variance in teacher leadership and 35.6% in teacher concerns. These findings contribute to understanding the complex dynamics of AI adoption in higher education and provide valuable insights for developing effective institutional strategies for AI integration in educational settings.

This study examines the determinants of the sustainable use of artificial intelligence (AI) among university professors in Peru. This research adopted a quantitative approach through a cross-sectional empirical–explanatory study, employing a structural equation model. Data were collected from 368 professors from eight Peruvian universities using a structured questionnaire that assessed six main constructs: attitude toward AI, prejudice against AI, facilitating conditions, use of AI, teaching concerns, and ethical perception. While the results reveal significant correlational relationships—with attitude toward AI, facilitating conditions, and prejudice against AI showing a significant association with its sustainable use, and the use of AI showing a significant relationship with professors’ ethical perceptions—the cross-sectional nature of this study precludes causal inferences. No significant relationship was found between the use of AI and teaching concerns. Additionally, demographic variables such as gender and age did not exhibit significant moderating effects. These findings contribute to understanding the factors related to the sustainable adoption of AI in higher education and provide valuable insights for the development of effective institutional strategies in the Latin American context.