Conference Agenda

Digital transformation in higher education has introduced significant challenges for police training, particularly regarding the pedagogical integration of Information and Communication Technologies (ICT). This study examines ICT-mediated pedagogical practices within the training schools of the Colombian National Police, aiming to identify their scope, limitations, and strategic implications. A qualitative hermeneutic-interpretative approach was adopted, involving a purposive sample of 15 instructors, 3 academic administrators, and 30 cadets. Data were collected through semi-structured interviews, focus groups, non-participant classroom observations, and document analysis, and were processed using NVivo software.

Findings reveal a heterogeneous integration of digital tools, including learning management platforms, interactive resources, and virtual simulators, alongside structural barriers related to connectivity, technological infrastructure, and faculty training. However, when ICT is implemented through active and situated methodologies, it enhances student motivation, participation, decision-making skills, and situational awareness. The study concludes that consolidating a digital police education model requires an articulated institutional policy combining infrastructure investment, continuous faculty development, technical support, and ethical guidelines for the use of emerging technologies. This research provides applied empirical evidence in the field of professional security training and offers relevant insights for police academies in Latin American and comparative contexts.

The literature shows that experiential education, through simulation, real-world practice, immersion, guided reflection, service-learning, immersive technologies, and community interaction, strengthens cognitive, emotional, ethical, and professional competencies, improving theory-practice transfer, self-regulation, self-efficacy, and employability. At the same time, academic performance is influenced by personal factors (emotional intelligence, motivation, executive functions, self-efficacy), contextual factors (school climate, institutional support, safety, educational modality), and socioeconomic factors. Both approaches converge on the idea that active, reflective, and contextualized learning enhances both academic performance and the student's holistic development.

The emergence of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) has reconfigured mathematics education, shifting the boundaries of traditional instruction toward dynamic conversational tutoring models. Objective: This study aimed to analyze the impact of GenAI-based virtual tutors on self-directed learning in mathematics by identifying pedagogical trends, benefits for student autonomy, and implementation challenges. Methodology: A systematic literature review of scientific publications between 2022 and 2026 was conducted following the PRISMA guidelines. Empirical and theoretical studies integrating tools such as ChatGPT and adaptive models in higher and secondary education contexts were analyzed. Results: Evidence indicates that GenAI integration significantly improves academic performance and the understanding of abstract concepts (such as functions and calculus) while reducing math anxiety and cognitive load. These tools act as scaffolding that fosters self-regulation through immediate and personalized feedback. However, risks associated with data accuracy ("hallucinations") and potential technological dependence limiting critical thinking were identified. Conclusions: It is concluded that virtual tutors are effective catalysts for personalized mathematical learning, provided their implementation is mediated by critical digital literacy strategies and instructional design that prioritizes human validation over automation.

Los entornos digitales tienen una presencia significativa en los contextos educativos por lo que es necesario identificar los aportes para la educación superior. El objetivo del estudio fue determinar el impacto del aprendizaje ubicuo en el desarrollo de las habilidades comunicativas reconociendo los aportes para la expresión oral, producción textual, comprensión lectora y expresión artística. El tipo de investigación fue básico con un enfoque cuantitativo y de nivel correlacional. La muestra estuvo formada por 150 universitarios elegidos por el muestreo probabilístico aleatorio. La técnica aplicada fue la encuesta y el instrumento fue el cuestionario validado por expertos quienes determinaron la relevancia, coherencia y pertinencia. En el resultado se evidenció el impacto positivo del aprendizaje ubicuo en las habilidades comunicativas observándose que la interacción virtual favorece la verbalidad, redacción, comprensión y la expresión artística. Estos hallazgos se contrastaron con estudios previos que señalan la eficacia del aprendizaje como estrategia pedagógica para promover las competencias comunicativas. A partir de ello se concluye que el aprendizaje ubicuo optimiza la comunicación académica y profesional de los universitarios debido a que permite el acceso a la información en cualquier momento y lugar influyendo en la adquisición de conocimientos. Por ello, su incorporación mejora los resultados académicos de las habilidades comunicativas; además que genera una participación activa en toda la comunidad educativa.

The objective of this research was to systematically analyze the regulatory frameworks governing the use of artificial intelligence in higher education. To this end, the scientific literature in the Scopus database was reviewed. Initially, 208 scientific articles were evaluated. The PICOC methodology and the Boolean operators "OR" and "AND" were used to determine the search equation and research questions. The PRISMA framework was also employed for the appropriate selection of articles based on inclusion and exclusion criteria. The first filter yielded 61 articles, and the second, 32 articles, which were included in the research. Regarding the results, three types of regulations were found: legal, institutional, and ethical. The study concluded that these three regulatory frameworks are complementary and that the regulation of AI is positive in the higher education academic sphere.

Ultraviolet radiation poses a significant risk to human health, as it is associated with sunburn, premature aging, skin cancer, and ocular damage. Peru records UV index levels ranging from 14 to 20, which are considered among the highest worldwide, thereby highlighting the need for reliable monitoring and prediction systems. In this study, a predictive model was developed to estimate the maximum UV index using meteorological variables, including temperature, humidity, heat index, barometric pressure, solar radiation, and solar energy, through the application of machine learning techniques to historical records collected from the DAVIS Vantage PRO 2.0 meteorological station located in Puno during the 2017–2024 period. Following data cleaning, exploratory analysis, and model training, linear regression and Random Forest approaches were evaluated, with solar radiation and solar energy identified as the most influential predictors. Although linear regression achieved a satisfactory fit (R² = 0.87), the Random Forest algorithm demonstrated superior performance (R² = 0.95, MAE ≈ 0.75), with homogeneously distributed residuals and no evidence of systematic bias. Consequently, decision tree–based methods emerge as robust tools for real-time UV index estimation, with potential applications in public health, risk prevention, and the planning of outdoor activities.