Producción Científica
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- Self-regulated learning systemic and innovative thinking in women studying STEM careers a mastery level analysis(2024) Glasserman-Morales, Leonardo David; Alcantar-Nieblas, Carolina; Portuguez-Castro, May Iliana; Pacheco-Velázquez, Ernesto Armando; Tecnológico de Monterrey; Universidad de BraganzaSelf-regulated learning and systemic and innovative thinking are crit-ical for students’ academic success at all levels nowadays, particularly in higher education. This study aimed to analyze self-regulated learning and systemic and innovative thinking among women in Science, Technology, Engineering, and Mathematics (STEM) disciplines at the university level. A quantitative study was performed analyzing data from a non-probabilistic sample of 190 women study-ing careers in the STEM, with ages between 19 and 35 years. The results indi-cated significant differences in self-management, motivation, self-monitoring, and innovative thinking in the different STEM disciplines. Mechanical engineer-ing students exhibited high self-regulated learning and systemic thinking, while chemical and biological engineering students showed strong innovative thinking but lower self-regulation. These findings underscore the need for personalized STEM education programs that address specific strengths and areas for improve-ment. This paper discusses the implications for educational practice and the pro-motion of gender equity in STEM.
- Mapping the intelligent classroom: examining the emergence of personalized learning solutions in the digital age(2025-01-10) Lagos Castillo, Alez; Chiappe, Andrés; Ramírez-Montoya, María Soledad; Becerra Rodríguez, Diego Fernando; EGADE Business School; Bacca Acosta, Jorge Luis; Soykan, Emrah; Rob Koper; Teo, TimothyIt may seem that learning platforms and systems are a tired topic for the academic community; however, with the recent advancements in artificial intelligence, they have become relevant to both current and future educational discourse. This systematic literature review explored platforms and software supporting personalized learning processes in the digital age. The review methodology followed PRISMA guidelines, searching Scopus and Web of Science databases. Results identified three main categories: artificial intelligence, platforms/software, and learning systems. Key findings indicate artificial intelligence plays a pivotal role in adaptive, personalized environments by offering individualized content, assessments, and recommendations. Online platforms integrate into blended environments to facilitate personalized learning, retention, and engagement. Learning systems promote student-centered models, highlight hybrid environments’ potential, and apply game elements for motivation. Practical implications include leveraging hybrid models, emphasizing human connections, analyzing student data, and teacher training. Future research directions involve comparative studies, motivational principles, predictive analytics, adaptive technologies, teacher professional development, cost-benefit analyses, ethical frameworks, and diverse learner impacts. Overall, the dynamic interplay between artificial intelligence, learning platforms, and learning systems offers a mosaic of opportunities for the evolution of personalized learning, emphasizing the importance of continuous exploration and refinement in this ever-evolving educational landscape.
- Complex thinking and adopting artificial intelligence tools: a study of university students(Frontiers, 2024) Vázquez Parra, José Carlos; Gonzalez Gonzalez, Carina Soledad; Amézquita Zamora, Juan Alberto; Cotino Arbelo, Andrea E.; Palomino Gámez, Sergio; Cruz Sandoval, Marco; Eileen ScanlonIn the next 5 years, artificial intelligence (AI) tools are expected to become commonplace in people’s lives, especially in their work processes. Therefore, educational institutions feel intrinsically responsible for ensuring that their students acquire and develop competences associated with the appropriate use of this technology in their educational programs. However, what are the perceptions of students regarding the inclusion of artificial intelligence tools in their educational process and future careers, and what competencies can influence a greater adoption of this technology in the classroom? The objective of this article presents the results of an exploratory study in a sample population of students from a technological university in Mexico, in which their perception and openness toward the training and use of artificial intelligence tools for their professions was examined. Their perception of the development of complex thinking and its sub-competencies was evaluated, recognizing that complex thinking is a valuable cognitive skill to face changes in uncertain environments. The methodology of the study consisted of a multivariate descriptive statistical analysis using R software. The results determined a positive correlation between students’ perceived improvement in the achievement of complex thinking competence and their perception of the use of AI tools. In conclusion, participants perceived the use of these tools as a feature of their profession, although they questioned whether this knowledge is included in their professional training. This article presents several findings that offer ample opportunities for future research.
- Perception of AI tool adoption and training: initial validation using GSEM method(Emerald Publishing, 2024) Vázquez Parra, José Carlos; Henao Rodríguez, Carolina; Lis Gutiérrez, Jenny Paola; Palomino Gámez, Sergio; Suárez Brito, PalomaPurpose This study develops and validates the “Perception of the Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” instrument, designed to measure Latin American university students' attitudes and perceptions regarding AI training in their professional education across diverse fields. Design/methodology/approach The instrument was administered to 238 students from various disciplines at a Mexican university. Structural validity and reliability were assessed using a generalized structural equation model (GSEM) with quasi-maximum likelihood (QML) to handle data non-normality and analyze latent construct relationships. Findings Results show high internal consistency and validity, with strong correlations between items and constructs of “attitude” and “perception of AI training value.” The study found significant relationships between understanding AI tools and the perceived value of AI training, as well as between this perception and attitudes toward incorporating AI in professional training. Practical implications The instrument helps institutions identify student attitudes and training needs related to AI, enabling tailored curricula and training programs that foster positive AI acceptance, thus preparing students for modern technological challenges. Originality/value This study offers a validated instrument tailored to the Latin American context, addressing a gap in measuring student perceptions of AI in professional training. It serves as a diagnostic tool for educators and policymakers in designing AI-integrated pedagogical strategies that align with student needs.
- Robots Teaching Teachers: Acceptanceof Technology in Higher Education(2025-01-01) López Caudana, Edgar Omar; Suarez Brito, Paloma; Baena Rojas, Jose Jaime; admmsernaThis study aimed to investigate teacher perceptions of using advanced technological tools, specifically the NAO robot, in co-teaching settings to enhance class development and promote complex thinking in higher education. Complex thinking is a crucial skill in higher education, enabling students to effectively address and solve multifaceted problems.
- Challenges of implementing ChatGPT on education: Systematic literature review(Elsevier, 2025-01-10) García-Lopez, Iván Miguel; González, Carina; Ramírez-Montoya, Maria Soledad; Molina-Espinosa, Jose Martin; EGADE Bussiness SchoolSince its launch in 2022, ChatGPT has sparked considerable interest in higher education, raising debates about its benefits, challenges, and ethical implications. This systematic literature review, spanning January 2019 to January 2024, analyzes 42 articles from Web of Science and Scopus to identify key opportunities and challenges in its academic integration. Four core issues emerge: (a) technological integration and obsolescence, emphasizing the need for scalable, modular infrastructures; (b) personalization and equity, focusing on the balance between individualized learning and avoiding algorithmic bias; (c) data quality and security, highlighting the importance of transparent data management and robust encryption to protect sensitive information; and (d) ethics and human-AI collaboration, stressing the importance of institutional policies and continuous teacher intervention to ensure responsible and effective use. This study advances the discourse by recommending sustainable strategies for AI adoption, including professional development and fairness audits, while underscoring the critical role of human oversight in maximizing ChatGPT’s educational impact. Ultimately, it offers actionable insights for institutions to align AI use with ethical principles and long-term educational goals.
- Construyendo Puentes para el Futuro: Modelos Sostenibles en REA, Educación y Ciencia Abierta(2025-01-23) Burgos Aguilar, José Vladimir; Tecnológico de Monterrey; Instituto para el Futuro de la Educación del Tecnológico de MonterreyRecomendaciones y casos de referencia para abordar el desarrollo y creación de modelos de sostenibilidad para los Recursos Educativos Abiertos (REA)
- S4L: Simulating for Learning. Progress report stage 4.(Institute for the Future of Education, 2024-12-12) Ramírez Montoya, Maria Soledad; Pacheco Velázquez, Ernesto Armando,; Tecnológico de MonterreyS4L: Simulating for Learning. Progress report stage 4.
- Appendix 12. Interdisciplinary Team(Institute for the Future of Education, 2024-11-12) Ramírez Montoya, María Soledad; Tecnológico de MonterreyAppendix 12. Interdisciplinary Team. Technical report stage 4
- Appendix 11. Total SCOPUS articles(Institute for the Future of Education, 2024-11-11) Vazquez Parra, José Carlos; Tecnológico de MonterreyAppendix 11. Total SCOPUS articles. Technical report stage 4. Project E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity.