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.
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- Horizons of education 5.0 with AI through strategic leadership in the global context: case study research(IEEE Xplore, 2025-01-01) Ramirez Montoya, María Soledad; Maraboto Quepons, José Manuel; Enciso González, Juan Antonio; Miranda Mendoza, Jhonattan; https://ror.org/03ayjn504In the rapidly evolving landscape of education, the concept of Education 5.0 emerges as a transformative paradigm that integrates personalized learning, sustainable development, Artificial Intelligence (AI), and advanced technologies. How can educational institutions integrate AI and advanced technologies in the framework of Education 5.0 and Global Strategic Leadership to enhance personalized learning, promote sustainable development goals (SDGs), and facilitate innovative solutions in dynamic educational environments? This study investigates the case of the postgraduate course “Strategic Leadership in the Global Context,” where the Horizons Architecture method was applied with AI and advanced technologies to identify Education 5.0 components that foster innovative learning environments. The research employed the case study method, with the key components of Education 5.0: competencies, method, technology, infrastructure, stakeholders, and sustainability. The study population included managers, directors, and business leaders. The results indicated that (a) personalized learning links to shared goals for sustainable development; (b) Horizon scanning facilitates the search for solutions for all stakeholders; (c) the strategic integration of AI and advanced technologies enhances personalized learning experiences; (d) strategic leadership fosters agility and open innovation; and (e) collaborative partnerships drive sustainable educational transformations. This research provides a differentiated perspective for educational communities, society at large, and policymakers by illuminating pathways to navigate the complexities of Education 5.0. It underscores the imperative of proactive leadership and strategic foresight to shape future-ready educational ecosystems.
- Harnessing open language models: a systematic literature review unleashing AI's potential for a smarter future(IEEE Xplore, 2025-01-01) García-López I.M., Ramirez-Montoya M.S., Molina-Espinosa J.M.; https://ror.org/03ayjn504This study provides a systematic literature review (SLR) on Open Large Language Models (OLLM), which are large-scale natural language processing (NLP) models with accessible source code, configuration, and training data for the community. Recent advances in supervised and unsupervised learning techniques have improved the accuracy and contextual capabilities of OLLMs, enabling advanced applications in conversational interaction and long-text analysis. This research explored the applications and socioeconomic impacts of OLLMs in various industries, such as healthcare, education, and business management, demonstrating how these models optimize the efficiency and personalization of different processes. The study also addresses the ethical and operational challenges associated with OLLMs, such as bias management, data privacy and security, decision-making transparency, and technological dependency. Strategies are proposed to mitigate these issues, including regular ethics audits and the adoption of explainable AI frameworks. Finally, the study emphasizes the importance of maintaining a balance between OLLMs and human skills, the need for robust governance frameworks to ensure the ethical and legal operation of these models, and the promotion of continuous innovation to expand their capabilities for a positive and lasting impact on society.
- Social entrepreneurship competences for the development of complex thinking: a comparative study by gender in postgraduate students(IEEE Xplore, 2025-01-01) Ramirez Montoya, María Soledad; Martínez Pérez, Sandra; Zepeda Orantes, Laura Patricia; https://ror.org/03ayjn504In the context of complexity and opportunities for the future of education, promoting social entrepreneurship brings new possibilities for education and development in society. In this sense, the study of entrepreneurship in the educational context is of high value for educational institutions. This paper aims to contribute to the academic literature in understanding the differences in the development of social entrepreneurship competences among men and women pursuing postgraduate studies. The study used mixed methods and a concurrent triangulation design. Three instruments were applied: two semi-structured questionnaires and a validated Likert scale. The sample consisted of 89 students(31 men and 58 women) from 11 countries who were studying for a postgraduate degree in Humanities and Education. The question that triggered the present study was: Are there differences in the development of social entrepreneurship competences between men and women in a graduate program in the humanities and education? The overall results show that women scored higher than men, but the difference is not significant. The findings indicate that the horizon architecture model is a suitable method for deploying social entrepreneurship competences without gender barriers in the entrepreneur formation. Multidisciplinarity and long-range perspective in projects stand out as drivers of social entrepreneurship. This study can be of value to teachers, entrepreneurs, and decision-makers interested in innovative educational environments.
- 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.
- Digital educational ecosystem with artificial intelligence: evaluation of complex and computational thinking(Springer Link, 2024-10-23) Valenzuela-Arvizu, S. Y., Ramírez-Montoya, M. S., & García-Peñalvo, F.J.; https://ror.org/03ayjn504Due to the social, work, and technological demands characterizing 21st-century society, developing complex and computational thinking skills in the university environment is essential. This document aims to present the current status of a research plan for a doctoral thesis that analyses how university students’ development of computational and complex thinking skills are correlated using training experiences in an AI driven digital ecosystem. This research utilizes a mixed method concurrent design with a triangulation strategy, that is, the collection of quantitative and qualitative data carried out simultaneously (QUAN-Qual). The expected results will enable the development of an evaluation prototype for educational ecosystems with integration of AI. The document is organized into six sections: a) introduction: context and motivation underlying this research project, b) the state of the art of the primary theoretical constructs, c) the hypothesis and research objectives, d) the methodology followed, e) the status of the thesis and f) expected contributions. The research project will contribute to educational innovation, generating valuable knowledge by designing an evaluation prototype for digital ecosystems integrated with AI focused on developing complex and computational thinking skills in university students.
- User experience in digital ecosystems with integration of Artificial Intelligence: a systematic literature mapping from 2010 to 2024(Springer Link, 2024-10-23) Valenzuela-Arvizu, S. Y., Ramírez-Montoya, M. S., & García-Peñalvo, F.J.; https://ror.org/03ayjn504Analyzing users’ experience in digital ecosystems (DE) is essential to ensure effective spaces capable of satisfying their needs and interests. The present study analyzed the publications in the Scopus and Web of Science (WoS) databases from 2010 to 2024 on the study topic of “user experience (UX) in DEs that integrate artificial intelligence (AI).” One hundred eighty-two published articles were reviewed using the Systematic Mapping methodology. Inclusion, exclusion, and quality criteria were applied to obtain the most relevant information. The results showed a) the preponderance of empirical research articles over theoretical/conceptual; b) the mixed methodology approach and the concurrent triangulation design were the most used; c) the main areas of interest were Health, Education, and Technology, which reflects in d) the contexts of the most cited articles and e) the areas of specialization of the main journals analyzed; f) the United States tops the list of the leading countries in this research topic, followed by China and Australia; and e) the studies emphasized assessing the usability and satisfaction with chatbots, the most prevalent and studied AI tool. This review provides a framework for identifying the state of the art of the research topic, making it possible to identify current and emerging research trends.
- 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.
- Formative assessment in DGBL: a qualitative analysis of players perceptions of game-based feedback in complex scenario(Springer Link, 2024-10-23) Ramirez Montoya, María Soledad; Patiño Zúñiga, Irma Azeneth; Hernandez, L. E.; https://ror.org/03ayjn504Formative assessment in Digital Game-Based Learning (DGBL) involves evaluating students' learning progress through interactions within a game environment. This study aimed to analyze players’ perceptions of game-based feedback during a DGBL intervention among university students. Utilizing a qualitative approach, data were gathered through learning analytics embedded in the game, an online survey and video recordings of the game sessions. The study engaged 11 university students enrolled in a private higher education institution in Mexico, analyzing the data through content analysis and descriptive statistics. The study identified several key findings: (a) the game provided four types of feedback: guided, diegetic, outcome, and static; (b) these feedback types are integrated with game mechanics, quizzes, minigames, and NPCs; (c) perceptions of content-related feedback efficacy varied, with 27.3% average, 54.5% good, and 18.2% excellent, while game-related feedback was rated 9.1% poor, 36.4%average, 45.5% good, and 9.1% excellent; (d) specific feedback types influenced players’ financial behaviors, such as investing and saving strategies. These findings have significant implications for educational communities and decisionmakers, highlighting the importance of effectively integrating feedback mechanisms in educational games to enhance learning outcomes and behavior modification.
