Despite global interest in active learning methodologies, limited empirical evidence exists on their implementation in developing countries, particularly regarding their relationship with teaching competencies. This study explores the association between teaching competencies and the application of active learning methodologies in a Peruvian public university. We hypothesized a strong positive correlation between specific teaching competencies–planning, pedagogical practice, and assessment–and the effective use of student-centered, personalized, and globally integrated methodologies. Using a non-experimental, cross-sectional correlational design, data were collected from 167 education students through validated questionnaires. Statistical analyses included descriptive measures, Spearman correlations, cluster analysis, and multiple correspondence analysis. Findings revealed a strong correlation (\(r = 0.862\)) between teaching competencies and active methodology implementation. Three teacher profiles–high-performing, moderate, and developing–were identified, each demonstrating distinct patterns of competency and methodology use. The analysis also uncovered strong associations between pedagogical practice and learning personalization, but weaker integration between student-centered strategies and global-intercultural dimensions. These results emphasize the multidimensional nature of effective teaching and the need for targeted professional development. While the study confirms the relevance of integrated teaching models, limitations related to sample size, context specificity, and self-reported data suggest cautious generalization. Future research should adopt mixed-method, longitudinal designs across diverse institutional contexts.

In this study, different strategies used to count vehicles and people in different image areas at a street intersection were analyzed to obtain counts at appropriate times suitable for real-time control of a traffic light. To achieve this, video recordings of cameras placed at the intersection were used to test and verify image processing algorithms and deep learning using the YOLOv3 network implemented on a 4 GB RAM Jetson Nano card. We counted the vehicles and people that stopped and crossed the polygons to delimit the different areas of interest, with a maximum error of ±2 in the validation tests for all cases. In addition, as a strategy, we combined the images from both cameras into a single one, thereby allowing us to make a single detection and subsequently determine if they are inside or outside the polygons used in separating the areas of interest with the respective counts. Furthermore, this enabled us to obtain information on vehicles and people stopped and crossing in a time of 0.73 s on average. Hence, it was established that the inclusion of the control algorithm is appropriate for real-time control of traffic lights.

Este estudio revisa la producción científica sobre la aplicación de la inteligencia artificial (IA) en el aprendizaje de las matemáticas mediante un análisis bibliométrico. Se busca identificar patrones y tendencias en la literatura existente, evaluando la evolución de las publicaciones, los autores e instituciones más influyentes, y los temas predominantes. La metodología incluyó una búsqueda sistemática en la base de datos SCOPUS, utilizando una ecuación de búsqueda específica sin limitaciones temporales. Se analizaron 251 publicaciones, y se emplearon herramientas como Bibliometrix, VosViewer y Datawrapper para crear mapas científicos de redes semánticas y de coautorías. Los resultados revelan un aumento significativo en las publicaciones desde 2020, con un amplio interés en temas como la personalización del aprendizaje y la tecnología educativa avanzada. Los autores más destacados, como Li C. y Xing W., han sido identificados como líderes en el campo. Las revistas "Lecture Notes in Computer Science" y "CEUR Workshop proceedings" son las más influyentes. Se observó una fuerte colaboración internacional y entre instituciones, especialmente con una destacada participación de instituciones estadounidenses. Las conclusiones subrayan la importancia de la IA en la educación matemática y destacan áreas de crecimiento futuro, como la ética y la competencia digitales. Sin embargo, una limitación notable del estudio es el uso de una sola base de datos, lo que podría sesgar los resultados.

This systematic review of 79 CubeSat antenna studies reveals a progressive "workflow attrition cascade" (68%→70%→87%→92%) wherein electromagnetic design sophistication systematically decouples from deployment-ready system integration. While CubeSats demand reliable communication under severe constraints, our PRISMA 2020-compliant synthesis demonstrates that current research workflows rarely translate theoretical optimization into mission readiness. Specifically, 68% of studies omit critical simulation documentation, 70% rely on single-domain experimental validation inadequate for space qualification, 87% fail to achieve full thermal-mechanical integration of feeding elements, and 92% lack environmental qualification during fabrication. Rather than reflecting technical inability, this attrition highlights systemic gaps between component-level design and system-level engineering, exacerbated by academic incentives and resource constraints. Addressing these discontinuities requires a paradigm shift from isolated electromagnetic optimization toward concurrent multiphysics integration, establishing validated workflows essential for transitioning CubeSat payloads from experimental demonstrations to operational multi-year constellations.