In a context where artificial intelligence (AI) is transforming higher education, this study analyzes how students’ perceptions of AI influence their academic integrity (INA), with a focus on sustainable education. Through a correlational-explanatory analysis based on Structural Equation Models (SEMs) applied to a sample of 659 students from 13 universities in Chile and Peru, it is observed that AI has a significant and direct impact on academic integrity in both countries (β = 0.44). In Peru, the most influential dimension is trust in education (λ = 0.86), followed by social, economic, security, and risk implications (λ = 0.78), while attitudes towards AI also have a direct impact on integrity factors (β = 0.15). In Chile, the dimensions of trust in education (λ = 0.83) and social and economic impact (λ = 0.79) are most relevant, and the relationships between the dimensions of academic integrity such as justice, respect, and responsibility (λ = 0.71) are stronger. The study highlights the importance of incorporating AI literacy into educational curricula and developing regulatory frameworks that promote its ethical use, linking these actions to sustainable education. The findings highlight the need for sustainable educational approaches that enhance understanding of AI and ensure that its use in academia is beneficial, ethical, and contributes to sustainable development.

As Latin American universities pursue digitally and environmentally sustainable teaching models, understanding why students adopt generative AI is essential. We analyzed data from undergraduate students (n = 792) across five Latin American countries (Peru, Chile, Bolivia, Argentina, and Colombia). Grounded in the diffusion of innovations theory, the study evaluated the effects of relative advantage, compatibility, complexity, trialability, and observability on attitudes towards ChatGPT and examined the effect of attitude on intention to use among higher education students in the region. The reliability and validity of the measurement scale were confirmed, and structural relationships were tested using partial least squares structural equation modeling (PLS-SEM). The model explained 58.1% of the variance in attitude: relative advantage (β = 0.247) and compatibility (β = 0.246) exerted the largest effects, followed by trialability (β = 0.223) and observability (β = 0.167); complexity showed a weaker yet significant effect (β = 0.118). Attitude strongly predicted the intention to use ChatGPT (β = 0.777), accounting for 60.4% of its variance. All paths were significant (p < 0.001), and psychometric indicators exceeded recommended thresholds. These findings indicate that student adoption is driven more by perceived academic benefits and alignment with existing learning routines than by technical ease. Highlighting concrete, ethically delineated use cases and providing guided institutional spaces for experimentation may accelerate the responsible, long-term adoption of generative AI in quality higher education.

The purpose of this study was to determine the influences of variables, crisis management, distance education, the organizational image, and student satisfaction on the basic quality conditions in Peruvian universities during the COVID-19 pandemic. A quantitative, nonexperimental explanatory approach with stratified random sampling was used. A questionnaire was applied to 513 students from public and private universities in southern Peru who received distance education during the months of September to November 2022. For the analysis of the results, a structural equation model (SEM). A hierarchical linear regression was carried out to test the hypotheses according to the dimensions studied on the student satisfaction scale. The study findings showed that distance education and student satisfaction had positive impacts on the basic quality conditions, while crisis management and the organizational image had a positive relationship but a smaller effect on the quality of the conditions. We concluded that the applied model allows the causal relationships between variables to be explored and that the results will allow university authorities to generate policies that improve their organizational image and crisis management processes and, at the same time, allow them to better plan their crisis management strategies to achieve better satisfaction within the framework of a sustainable university.

La investigación tuvo por objetivo analizar la percepción de docentes universitarios sobre la relación entre la Responsabilidad Social Universitaria y la cultura organizacional en una universidad privada del Perú. En cuanto a la metodología usada fue básica de enfoque cuantitativo con diseño no experimental. Se utilizaron encuestas validadas por expertos en la materia, aplicándose 150 cuestionarios a docentes y administrativos de la Universidad Privada de Tacna-Perú en el año 2020. Se utilizó el coeficiente de Rho Spearman que permitió la contrastación empírica de las hipótesis y a su vez ayudar a generar estrategias sostenibles de la relación para la universidad. Concluyendo que la buena implementación de la RSU influye positivamente a la transformación institucional de las universidades contribuyendo al desarrollo sostenible y la empleabilidad de los estudiantes.

El estudio analiza las actitudes y comprensión de estudiantes universitarios en Perú hacia la Inteligencia Artificial (IA). A nivel metodológico se siguió la ruta cuantitativa-descriptiva diseñando una encuesta, revela que la mayoría de los estudiantes tienen un conocimiento básico de la IA, pero también expresan preocupaciones sobre su impacto en el empleo y la sociedad. La encuesta fue aplicada a 392 personas siendo validadas para el estudio 379 cuestionarios. Los resultados determinan que los estudiantes de pre y posgrado muestran curiosidad por entender cómo la IA podría influir en sus carreras y en la sociedad en general. Este estudio ofrece una perspectiva valiosa sobre cómo la IA es percibida y entendida por la próxima generación de profesionales peruanos, señalando la importancia de promover la educación y el debate sobre este tema en el ámbito universitario.