Explore the vast range of titles available.

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 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.

Conocer la diversidad y usos del maíz es sustancial para la seguridad alimentaria. Las características de las semillas son importantes debido a que poseen rasgos particulares que buscan los productores para su consumo o almacenamiento. En diez materiales de maíz (siete criollos y tres variedades de polinización libre) se obtuvo información de las características  orfométricas en semillas (largo, ancho, espesor y área), porcentaje de endospermo harinoso y cristalino por medio de imágenes, dureza con ayuda de un texturometro y oviposición de Sitophilus por medio de una técnica de tinción. Se identificaron diferencias entre todos los materiales en todas las variables analizadas. Los materiales Sac beh y Nukuch nah registraron mayor dureza, también sobresalieron en la cantidad de endospermo cristalino registrando 85 y 84 % respectivamente, sin embargo, el primero fue de los más afectados con la oviposición de Sitophilus con nueve huevos por cada 10 semillas en promedio, en contraste con Chac choc (semilla roja) que solo presentó un huevo por cada 10 semillas. La variabilidad dentro de los materiales criollos puede proporcionar alternativas para los  rogramas de mejoramiento genético orientados al manejo postcosecha, poseen características que en conjunto disminuyen los efectos del ataque de Sitophilus.

Conocer la diversidad y usos del maíz es sustancial para la seguridad alimentaria. Las características de las semillas son importantes debido a que poseen rasgos particulares que buscan los productores para su consumo o almacenamiento. En diez materiales de maíz (siete criollos y tres variedades de polinización libre) se obtuvo información de las características morfométricas en semillas (largo, ancho, espesor y área), porcentaje de endospermo harinoso y cristalino por medio de imágenes, dureza con ayuda de un texturometro y oviposición de Sitophilus por medio de una técnica de tinción. Se identificaron diferencias entre todos los materiales en todas las variables analizadas. Los materiales Sac beh y Nukuch nah registraron mayor dureza, también sobresalieron en la cantidad de endospermo cristalino registrando 85 y 84 % respectivamente, sin embargo, el primero fue de los más afectados con la oviposición de Sitophilus con nueve huevos por cada 10 semillas en promedio, en contraste con Chac choc (semilla roja) que solo presentó un huevo por cada 10 semillas. La variabilidad dentro de los materiales criollos puede proporcionar alternativas para los programas de mejoramiento genético orientados al manejo postcosecha, poseen características que en conjunto disminuyen los efectos del ataque de Sitophilus.

Higher education institutions (HEIs) have been permeated by the technological advancement that the Industrial Revolution 4.0 brings with it, and forces institutions to deal with a digital transformation in all dimensions. Applying the approaches of digital transformation to the HEI domain is an emerging field that has aroused interest during the recent past, as they allow us to describe the complex relationships between actors in a technologically supported education domain. The objective of this paper is to summarize the distinctive characteristics of the digital transformation (DT) implementation process that have taken place in HEIs. The Kitchenham protocol was conducted by authors to answer the research questions and selection criteria to retrieve the eligible papers. Nineteen papers (1980–2019) were identified in the literature as relevant and consequently analyzed in detail. The main findings show that it is indeed an emerging field, none of the found DT in HEI proposals have been developed in a holistic dimension. This situation calls for further research efforts on how HEIs can understand DT and face the current requirements that the fourth industrial revolution forced.

Las Instituciones de Educación Superior se han visto influenciadas por el avance tecnológico que trae la Revolución Industrial 4.0, que les obliga a enfrentarse a una transformación digital en todas sus dimensiones. El objetivo de esta investigación es identificar cuáles son los diferentes escenarios de docencia frente a la transformación digital en Instituciones de Educación Superior. Después de una revisión sistemática de literatura sobre el tema, y una vez analizados los 19 artículos clasificados para la lectura total, se evidencia que la transformación digital en Instituciones de Educación Superior se ha desarrollado desde diferentes dimensiones, especialmente desde la docencia, respondiendo a iniciativas individuales, múltiples, separadas y/o no coordinadas a través de políticas institucionales de transformación digital. Como consecuencia, impera el riesgo latente de no considerar soluciones integrales que den respuesta asertiva a los requerimientos actuales y futuros de las Instituciones que les permita apropiarse, y tomar ventaja de, los nuevos retos enmarcados en la cuarta revolución industrial.

Las Instituciones de Educación Superior se han visto influenciadas por el avance tecnológico que trae la Revolución Industrial 4.0, que les obliga a enfrentarse a una transformación digital en todas sus dimensiones. El objetivo de esta investigación es identificar cuáles son los diferentes escenarios de docencia frente a la transformación digital en Instituciones de Educación Superior. Después de una revisión sistemática de literatura sobre el tema, y una vez analizados los 19 artículos clasificados para la lectura total, se evidencia que la transformación digital en Instituciones de Educación Superior se ha desarrollado desde diferentes dimensiones, especialmente desde la docencia, respondiendo a iniciativas individuales, múltiples, separadas y/o no coordinadas a través de políticas institucionales de transformación digital. Como consecuencia, impera el riesgo latente de no considerar soluciones integrales que den respuesta asertiva a los requerimientos actuales y futuros de las Instituciones que les permita apropiarse, y tomar ventaja de, los nuevos retos enmarcados en la cuarta revolución industrial.

Antimicrobial agent usage is common in animal agriculture for therapeutic and prophylactic purposes. Selective pressure exerted by these antimicrobials on soil bacteria could result in the selection of strains that are resistant due to chromosomal- or plasmid-derived genetic components. Multiple antimicrobial resistances in Escherichia coli and the direct relationship between antimicrobial agent use over time has been extensively studied, yet the relationship between the age of an animal agriculture environment such as a dairy farm and antibiotic resistance remains unclear. Therefore, we tested the hypothesis that antimicrobial-resistance profiles of E. coli isolated from dairy farm topsoil correlate with dairy farm age. E. coli isolated from eleven dairy farms of varying ages within Roosevelt County, NM were used for MIC determinations to chloramphenicol, nalidixic acid, penicillin, tetracycline, ampicillin, amoxicillin/clavulanic acid, gentamicin, trimethoprim/sulfamethoxazole, cefotaxime, and ciprofloxacin. The minimum inhibitory concentration values of four antibiotics ranged 0.75 to >256 μg/ml, 1 to >256 μg/ml, 12 to >256 μg/ml, and 0.75 to >256 μg/ml for chloramphenicol, nalidixic acid, penicillin, and tetracycline, respectively. The study did not show a direct relationship between antibiotic resistance and the age of dairy farms.