Conferencia
Permanent URI for this collectionhttps://hdl.handle.net/11285/636053
Presentación o disertación realizada dentro de un congreso o evento similar, o como evento académico independiente, tales como: Conferencia inaugural, conferencia magistral, conferencia de clausura.
Browse
Search Results
- Movilizando las recomendaciones UNESCO 2019 y declaración de Dubái en educación y ciencia abierta. Estancia internacional UNESCO 2025(2025-01-20) Ramírez Montoya, María Soledad; Varoglu, Zeynep; EGADE Busciness School; Tecnológico de MonterreyConferencia para incentivar la reflexión para movilizar las Recomendaciones UNESCO 2019 y Declaración de Dubái en Educación y Ciencia Abierta.
- Estancia UNESCO Presentación del libro "Horizontes en el aprendizaje vinculado con el desarrollo sostenible. Nuevas vías en la era digital"(2025-01-20) Pacheco Velázquez, Ernesto Armando; Ramírez Montoya, María Soledad; Zavala Enríquez, Genaro; Martínez Arboleda, Antonio; Montoya Bayardo, Miguel Ángel; Tecnológico de Monterrey; IFE Tecnológico de MonterreyPresentación del libro "Nuevos horizontes en el aprendizaje vinculado con el desarrollo sostenible. Nuevas vías en la era digital" en la Estancia UNESCO 2025.
- Generative artificial intelligence in higher education: a literature mapping perspective(IATED Digital Library, 2024-11-11) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504Generative Artificial Intelligence (GAI) opens intriguing possibilities for creating unique and innovative content. This systematic literature review (SLR) analysed the published evidence on GAI in higher education institutions from January 2018 to October 2023. Fourteen articles on the topic were identified in the Web of Science (WOS) and Scopus databases. We screened to obtain the most relevant data by applying inclusion, exclusion, and quality criteria. The results identified (1) the characteristics of the publications, (2) methodological trends, and (3) the approaches implemented. The study aims to be of value to the academic community and developers of GAI initiatives
- Design and challenges of open large language model frameworks (Open LLM): a systematic literature mapping(IATED Digital Library, 2024-11-11) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504Analyzing the frameworks of open large language models (OLLM) is essential to understanding how the management of these artificial intelligence (AI) models can be regulated. This study aims to analyze the evidence published from 2019 to 2024 regarding OLLM frameworks that integrate AI. Systematic mapping was the method for reviewing 227 articles published in the Scopus and Web of Science (WoS) databases. Inclusion, exclusion, and quality criteria filtered the papers to obtain the maximum relevant information. The analysis and classification of articles related to open LLM frameworks and models yielded significant findings per our research questions. The challenges identified were a) improving customization and accuracy through open LLMs, b) latency and efficiency challenges, c) the importance of reliability and security, and d) complex operational management (LLMOps). This review provides a framework for identifying the topic's state of the art and current and emerging research trends.
- Social entrepreneurship and complex thinking competencies with an open technology platform: a gender approach(2024-11-01) Ramírez Montoya, María Soledad; Vázquez Parra, José Carlos; Echaniz Barrondo, Arantza; https://ror.org/03ayjn504; https://ror.org/00ne6sr39In addition to specialized disciplinary training, cross-disciplinary skills are relevant to lifelong learning. One such skill is complex thinking, which involves integrating different reasoning to solve problems. To ensure that all students can achieve the same professional learning goals, in this paper, we present the results of an analysis of students’ perceived achievement of complex thinking competency through self-managed activities on an open education technology platform that diagnoses, develops, and evaluates social entrepreneurship competency. The research objective was to identify statistically significant gender differences in the two competencies (complex thinking and social entrepreneurship) in a group of students attending a technological university in Mexico. Methodologically, a multivariate descriptive analysis calculated arithmetic means and standard deviations, supplemented by boxplot and violin plot analyses and a scatter plot with lines of central tendency. In addition, a t-test analysis with a p-value of 90% was performed to identify the statistical significance of differences in the mean values by gender. The findings confirmed a statistically significant gender gap in the development and level attained in the students’ perceived achievement of both competencies (social entrepreneurship = 0.007 p-value; complex thinking = 0.068 p-value). Women showed the best results after using this technological platform. This study highlights the need to design technological tools for developing disciplinary and cross-disciplinary competencies from a gender perspective, to promote educational innovations that equitably ensure lifelong learning.
- Regulatory challenges and optimization strategies for open large language models: a multidimensional framework for efficient management(Springer Link, 2024-10-23) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504Innovations in artificial intelligence are rapidly transforming various in-dustries, particularly through the development and deployment of Open Large Language Models (OLLMs). However, the absence of a robust regula-tory framework presents significant challenges in ensuring the ethical, safe, and effective use of these models. This research aims to address this gap by proposing a comprehensive regulatory framework designed to optimize the scalability and performance of OLLMs, emphasizing the importance of structured pruning techniques. By integrating both quantitative and qualita-tive analyses, the study will assess the technical capabilities and societal implications of OLLMs, ultimately providing clear guidelines that promote responsible and sustainable innovation. The expected outcomes include the development of a governance model that balances the need for innovation with ethical considerations, offering a pathway for the regulation of OLLMs that supports their continued evolution while safeguarding public interests.
- Modelos de lenguaje grande, la revolución silenciosa en educación, salud e industria: mapeo sistémico de literatura(International Insitute of Systemics, Cybernetics, and Informatics: IIIS, 2024-09-10) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504Los Modelos de Lenguaje Grande (LLMs) están revolucionando múltiples sectores mediante su capacidad para procesar y generar texto con un alto nivel de coherencia y contexto. Estos modelos no permiten acceso público a su código fuente ni datos de entrenamiento, lo que restringe su uso a la organización que los posee. A diferencia de los modelos de código abierto, los LLMs cerrados presentan tanto oportunidades como desafíos únicos. Nos preguntamos: ¿Cuáles son las estrategias efectivas para integrar LLMs en educación, salud e industria, y cómo pueden manejar los retos éticos, de seguridad y transparencia? El método del estudio es una revisión sistemática de la literatura, analizando artículos de las bases de datos Scopus y Web of Science desde enero de 2019 hasta mayo de 2024. Se seleccionaron los datos más relevantes utilizando criterios de inclusión, exclusión y calidad, y se delimitaron 60 artículos para su análisis. Los hallazgos destacan: (a) oportunidades significativas en la personalización y eficiencia en diversos sectores, (b) marcos de trabajo para la integración efectiva de LLMs y (c) estrategias para abordar desafíos éticos y de seguridad. Este escrito invita a otros investigadores a explorar el uso de LLMs en distintos ámbitos, resaltando su potencial para transformar procesos educativos, médicos e industriales, mientras se asegura un uso responsable y ético.
- Next-Gen information architecture: open STEAM platforms(2024-08) González Pérez, Laura Icela; Enciso Gonzalez, Juan Antonio; Lindín, Carles; Vicario Solórzano, Claudia Marina; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504; University of AlicanteSmart technologies in educational platforms need a new vision to organize attributes and characteristics that facilitate search and retrieval. This study reports the evaluation results of Open Educational Platforms (OEPs) in Science, Technology, Engineering, Arts, and Mathematics (STEAM). In a webinar, participants selected OEPs using a structured instrument provided during the session. The instrument includes a two-section rubric. The first section validates the obligatory metadata and adherence to an open license. The second quantitatively assesses the quality of the OEPs in seven dimensions. The questions guiding this research were: Which OEPs in STEAM aligned with the principles of open education scored the highest quality assessment, and in which dimensions? Which dimensions obtained the lowest means? 1) The highest-scoring STEAM OEPs were Khan Academy and GeoGebra, scoring highest in the dimensions "Smart Components," "Learner Support," and "Technical Support." 2) On average, the dimensions with the lowest scores were "Smart Components," "Learner Support," and "Technical Support." OEP developers should consider a new information architecture with metadata for demarcations that require new data sets for greater long-term scalability.
- Transforming logistics education by a virtual logistics simulation generator: UX pilot study(2024-06) Ramírez Montoya, María Soledad; Rodés Paragarino, Virginia; Pacheco Velázquez, Ernesto Armando; Ramírez Echeverri, Sergio Augusto; https://ror.org/03ayjn504; https://ror.org/03y3y9v44; IEEEIn the era of Industry 5.0 and the impact of the changes in the supply chain, educational institutions, SMEs, and the labor market are challenged by technological advancements. The "Simulations for Learning" (S4L) project responds to this challenge by introducing the Virtual Logistics, asimulation generator platform designed to transform logistics education through enhanced decision-making skills and customizable simulations. This tool allows students to design and adapt logistics networks, tailoring their educational experience to real-world logistics scenarios, and by doing so, creating simulation-based serious games. A pilot study was conducted with 249 students from eight universities across five Latin American countries to assess the usability of this simulation generator on logistics education. The study revealed significant findings: (a) the simulation generator provides learners with flexible and tailored educational experiences. (b) the Interface and Performance and Effectiveness aspects of the Virtual Logistics were highly rated, achieving an "Excellent" usability level; (c) however, Content Organization and Navigation were perceived as slightly less effective, receiving a "Good" usability rating and highlighting areas in need of improvement. These results demonstrate student’s satisfaction, and therefore, the transformative potential of simulation-based learning tools in logistics education. Virtual Logistics offers valuable guidance for educators, policymakers, and industry leaders, aligning educational tools with dynamic requirements, ensuring that future professionals are well-equipped to face the complexities of the modern logistics landscape.
- Inteligencia artificial generativa y el aprendizaje para toda la vida: Mapeo de literatura(2024-03-26) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504; International Institute of Informatics and SystemicsEl aprendizaje está presente en cada día de nuestras vidas, por lo que siempre seguimos aprendiendo a lo largo de la vida. El aprendizaje para toda la vida (LLL) representa la oportunidad de seguirnos preparando día a día. Con el auge de las nuevas tecnologías como la inteligencia artificial generativa (GAI) surgen nuevos retos sobre la forma en que se aprende. En este sentido se partió de la pregunta ¿Cuáles son las características de GAI que se ubican en las implementaciones del ámbito educativo, en el presente y futuro del LLL? El método del estudio es una revisión sistemática de la literatura, de los sistemas Scopus y Web of Science en el marco de enero de 2018 y octubre de 2023. Se cribaron los datos más relevantes utilizando criterios de inclusión, exclusión y calidad y se delimitaron 2 artículos de estudios. Los hallazgos destacan (a) oportunidades para explorar ambos conceptos (b) marcos de trabajo que con juntan la GAI y LLL y (c ) LLL abordado desde el aspecto tecnológico-pedagógico. Este escrito llama a otros investigadores a hacer uso del concepto de GAI en el LLL, particularmente por ser un tema naciente para el futuro de la educación.
