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This study aims to assess the adoption and impact of Artificial Intelligence (A.I.) tools in higher education, focusing on a private university in Latin America. Guided by the question, \"What is the impact, as perceived by university students, of using Artificial Intelligence tools on various dimensions of learning and teaching within the context of higher education?\" the study employs a rigorously validated 30-item instrument to examine five key dimensions: 1) Effectiveness use of A.I. tools, 2) Effectiveness use of ChatGPT, 3) Student's proficiency using A.I. tools, 4) Teacher's proficiency in A.I. and 5) Advanced student skills in A.I. These dimensions form a synthetic index used for comprehensive evaluation. Targeting 4,127 students from the university's schools of Engineering, Business, and Arts, the study garnered 21,449 responses, analyzed using Confirmatory Factor Analysis for validity. Findings indicate a significantly positive impact of A.I. tools on student academic experiences, including enhanced comprehension, creativity, and productivity. Importantly, the study identifies areas with low and high A.I. integration, serving as an institutional diagnostic tool. The data underscores the importance of A.I. proficiency among both educators and students, advocating for its integration as a pedagogical evolution rather than just a technological shift. This research has critical implications for data-driven decision-making in higher education, offering a robust framework for institutions aiming to navigate the complexities of A.I. implementation.

This study examines the incidence of academic stress and its determinants on mental health among university students. It employs a comparative approach to evaluate the role of academic stress as a predictor of mental health outcomes during and after the COVID-19 pandemic. Utilizing a mixed-methods approach, the research surveyed students using standardized instruments to measure academic stress and mental health. Cross-sectional analyses were conducted at two time points, drawing on responses from undergraduate students at a private university in Latin America. The primary objectives were to quantify academic stress levels and their stressors, evaluate mental health status, and explore this relationship during these periods. Data collection yielded 1,265 and 707 valid responses for each respective period, employing the Academic Stress Inventory and the Mental Health Continuum-Short Form for assessments. Findings indicated high stress levels among students, regardless of the pandemic phase, with notable stressors including teacher, exam, results, group work, peer, time management, and self-inflicted stress. The post-pandemic phase revealed changes in the impacts of stressors, with self-inflicted stress, group work, and time management stress showing significant relevance to mental health. The study highlights the challenge of academic stress on mental health, urging educational institutions to address pressures and provide support mechanisms for student well-being.

Identifying the relationship between academic stress and mental health of undergraduate university students is crucial for reducing and understanding its negative effects, enhancing students' ability to cope with stressful situations, and thereby reducing the harm it causes on academic performance and overall well-being. This study aims to examine the correlation and predictive value of academic stress on mental health in undergraduate university students. A representative sample of 1,265 undergraduate university students from a private university in Bolivia was assessed using Pearson's correlation analysis to determine the predictive value of academic stress on mental health. To validate the measurements obtained, a stepwise Hierarchical Multiple Linear Regression analysis was applied. A probability model was estimated to identify academic stressors that contribute to the probability of students experiencing Languishing Mental Health. The study revealed that Self-inflicted Stress was the most significant stressor among undergraduate students. This indicates that students' self-demands and self-efficacy perceptions are essential factors in the development of high academic stress levels. There is a clear correlation between high levels of academic stress and the probability of experiencing Languishing Mental Health.

This study investigates the integration of Artificial Intelligence (AI) tools within the School of Arts at a private university in Latin America, focusing on student perceptions and emotional reactions. The research addresses two primary questions: how students perceive the integration of AI tools in their educational experience, and how AI-enhanced classes affect students' emotional reactions compared to traditional lecture-based classes. To explore the first question, we constructed the Synthetic Index of Use of Artificial Intelligence Tools (SIUAIT) to measure the perceived effects of AI usage across five dimensions: effectiveness of AI tools, implementation of ChatGPT, student proficiency, instructor proficiency, and advanced student skills. Confirmatory Factor Analysis (CFA) validated the SIUAIT, revealing an increase from 58.84 in the first semester to 60.60 in the second semester of 2023, indicating growing acceptance and perceived utility of AI tools in arts education. To address the second question, we employed advanced neuromarketing technologies, including eye tracking and facial expression analysis, to assess emotional reactions in AI-enhanced versus traditional lecture-based classes. The findings showed that AI-enhanced classes elicited more positive emotions, such as joy and surprise, compared to traditional methods. Statistical analyses, including Pearson correlation, Student's t-test, and Kruskal-Wallis test, confirmed the significance of these differences. This comprehensive approach provides valuable insights into the benefits and challenges of integrating AI in arts education. The study highlights AI's potential to enhance educational experiences and emotional engagement while emphasizing the need for ongoing training and addressing ethical concerns to ensure the effective and equitable use of AI tools. This study explores how Artificial Intelligence (AI) tools enhance the educational experience in a higher education setting. It focuses on two key aspects: the Synthetic Index of Use of Artificial Intelligence Tools (SIUAIT) and the measurement of students' emotional reactions when taught with AI compared to traditional lecture-based classes. The results show that learning experiences are significantly improved in AI-enhanced classes, with students displaying more positive emotions. Additionally, the SIUAIT provides valuable insights for making informed decisions on training both students and teachers over time. These findings highlight the potential of AI to create more engaging and effective learning environments, emphasizing its importance for future educational strategies and the continuous development of AI proficiency among educators and learners.

This study explored the integration of Artificial Intelligence (AI) tools in finance education, focusing on student perceptions, emotional reactions, and educator experiences. Quantitative data were gathered using the Synthetic Index of Use of AI Tools (SIUAIT) instrument, administered over three semesters. The findings revealed that finance students perceived AI tools as essential for enhancing their learning experience. Notably, Financial Engineering students exhibited higher proficiency and more positive perceptions of AI tools compared to students in other disciplines, such as Engineering and Business. An observational study utilizing eye tracker technology and facial expression analysis highlighted the emotional dynamics between AI-enhanced and traditional lecture-based classes. Positive emotions, such as joy and surprise, were significantly more prevalent in AI-enhanced environments, contributing to a more engaging and emotionally positive learning experience. However, an increase in fear was also observed, which could be considered a negative activating emotion that, ultimately, still fostered learning. Semi-structured interviews with educators revealed both the opportunities and challenges of AI integration. Educators acknowledged AI's benefits in enhancing pedagogy but expressed concerns about over-reliance and ethical implications. Thematic analysis identified key dimensions: knowledge, usage, and ethics in AI. The study concluded that AI tools could significantly transform finance education, offering enhanced learning experiences and better preparing students for future careers. However, a balanced approach, addressing ethical and psychological impacts, was essential to maximize benefits and minimize potential drawbacks. Future research should explore AI's long-term effects and its correlation with academic performance. This study highlights how Artificial Intelligence (AI) tools are shaping finance education by examining their effects on students' learning experiences, emotional responses, and educators' perspectives. AI tools, such as ChatGPT and FinChat, were shown to improve students' engagement and understanding, particularly in finance-related subjects. The study's findings suggest that students, especially in Financial Engineering, not only gain valuable skills but also experience increased positive emotions, like joy and surprise, during AI-enhanced classes. However, an observed rise in fear also indicated the importance of addressing emotional challenges in AI-driven learning. Educators viewed AI tools as beneficial for enhancing teaching but raised concerns about ethical considerations and over-reliance. This research underscores the transformative potential of AI in finance education while advocating for a thoughtful balance between its advantages and challenges. These insights are relevant for educators, students, and policymakers as they consider the future integration of AI in academic environments.