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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
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- User experience measurement in design-based research on online educational platforms: contextualization of real-world environments within sustainable development goals for computational thinking(SAGE Publications, 2025-09-15) Tariq, Rasikh; Ramírez Montoya, María Soledad; Awotwe, Tabbi Wilberforce; Fernández Castro, Verónica; Martínez Reyes, Magally; Novak, AngelaThe importance of User Experience Measurement allows understanding how experiences can be optimized to meet functional and emotional needs, complemented with Design-Based Research to scale the redesign of educational platforms, four online educational platforms presented are powered by Artificial Intelligence and educational data mining to offer a tailored learning experience, combining computational thinking with Sustainable Development Goals. We present the analysis of responses of 1,573 users, which yield elements of improvement that will be implemented in the redesign. To measure User Experience of the platform, a nonexperimental quantitative analysis was carried out, using a Feedback survey based on a Likert-scale instrument, measuring perceptions: Emotional impact, Usability, and Satisfaction. The transcendence of this proposal demonstrates good practice in documenting experiences with the redesign of educational platforms that incorporate Artificial Intelligence and data mining, thereby opening a gap in Research on the quality of assessments and scaling of this approach.
- Generative artificial intelligence in education: a systematic analysis of opportunities, challenges, and responses(Taylor & Francis, 2025-08-04) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; Tecnológico de MonterreyGenerative artificial intelligence (GenAI), exemplified by tools such as ChatGPT, is transforming the educational field by offering innovative solutions for the personalization of learning, student motivation, and the optimization of pedagogical processes. The core research question is: How is GenAI transforming educational processes, and what are the challenges and opportunities associated with its implementation? To answer it, a systematic literature review (SLR) was conducted, analyzing recent studies that address applications, policies, and limitations of AI in education. The main findings highlight three key constructs: personalization of learning, which improves academic performance through adaptive interventions; educational innovation, which boosts motivation through interactive and gamified environments; and the need for ethical and inclusive regulation, which guarantees transparency and equity in the use of these technologies. In addition, gaps were identified in institutional policies and existing legal regulation, evidencing the urgency of updating them to respond to emerging challenges. The added value of this study lies in its holistic and comprehensive approach, which connects pedagogical applications, ethical challenges, and regulatory policies, proposing concrete recommendations for the responsible and effective implementation of AI in educational contexts.
- Measuring digital transformation in education 4.0 with DT-Smarty: valid and reliable model(Springer, 2025-04-23) González Pérez, Laura Icela; Enciso González, Juan Antonio; Vicario Solórzano, Claudia Marina; Ramírez Montoya, María Soledad; Tecnológico de Monterrey; Universidad Autónoma de Nuevo León; Dirk IfenthalerValidated instruments enable strategic decision-making in an increasingly complex tech- nological environment. Higher Education Institutions (HEIs) should have data measuring technological maturity and readiness for cyber-physical environments, crucial to leading digital transformation and sustainable development. This study presents the validation of an instrument designed to assess academicians’ perceptions of the technological maturity and digital transformation readiness of HEIs. The scale dimensions were constructed and vali- dated in three steps: (1) operationalization of the study variables and scale development, (2) content validation through a nine-expert judgment panel with Aiken’s V, and (3) factor exploratory analysis (EFA) and reliability analysis using Cronbach’s Alpha method. The validation yielded three main findings: Aiken’s V coefficient yielded a value of (>0.82), indicating substantial agreement for the content evaluation of nine experts; reliability test- ing produced a Cronbach’s alpha of .957, demonstrating excellent internal consistency. The Kaiser–Meyer–Olkin (KMO) measure was .919, confirming the questionnaire’s suitability for 19 items. Four critical dimensions were established: (1) Cyber-Physical Systems, (2) Educational platforms and data and analytics, (3) Organizational platforms, and (4) Conti- nuity and security plans. These results validate the instrument as a robust tool for diagnos- ing digital maturity in university contexts, effectively capturing the proposed dimensions essential for educational innovation. The future work to evolve this instrument could shed light on the roadmap for incorporating technological enablers, aligning vocational training with the challenges of Industry 4.0, and supported by predictive AI models that allow the creation of solid governance to lead the digital evolution.
- A look at sustainability through the lens of the sustainable development goals and education 5.0: A systematic review of the literature(Journal of Social Studies Education Research, 2025-03-31) Ramírez Montoya, María Soledad; Tariq, Rasikh; Rozo García, Hugo Alexander; Casillas Muñoz, Fidel; Tarman, BulentWe discuss a new construct called Industry 5.0, which has infiltrated the education sector, enabling us to explore Education 5.0. This concept is based on the use of advanced technologies that enable it to address global issues in contemporary society, many of which are related to sustainability. In line with the above, the aim of this research was to reveal the possible advances that have been made in Education 5.0 and its relationship with Sustainable Development Goals, especially sustainability, to achieve this, a systematic literature review was carried out, analyzing 92 articles from the Web of Science (WoS) and Scopus databases. The analysis was carried out through research questions that allowed the documentary corpus to be explored, organized, and segmented in order to focus on three elements How sustainability has been approached by Education 5.0, the possible challenges it faces in working toward sustainability in the immediate future, and finally, a characterization of the publications. The results take into account that: a) the management of education and its relationship with industry 5.0 seems to be the favorite topic when SDGs are addressed; b) the impact on sustainability for 5.0 technologies is diverse, ranging from facilitating intelligent resource management to refining teaching methods, raising awareness of sustainability, improving collaboration and promoting virtuality; c) SDGs is the topic less addressed in the literature in the margin of Education 5. 0; d) Most of the authors agreed that the main challenge is the widespread adoption of technologies in Education 5.0. The review concludes that the emergence of Education 5.0 introduces technological advances accentuated by a human-centered vision. However, it is urgent that institutions adopt an inquisitiveness about quality education, the achievement of SDGs, and the sustainability of education to amplify sustainable key competencies, such as creativity and human-centered thinking.
- Financial inclusion of vulnerable sectors with a gender perspective: risk analysis model with artificial intelligence based on complex thinking.(Springer, 2025-01-14) Medina-Vidal, Adriana; Alonso Galicia, Patricia Esther; González Mendoza, Miguel; Ramírez Montoya, María SoledadThe objective is to present a proposal for a gender-sensitive risk analysis model using artificial intelligence (AI) within the framework of complex thinking that provides access to opportunities, specifically for vulnerable populations such as women from underprivileged sections. This international non-parametric study highlights the vulnerability of this population in Mexico through a sample of 2787 women. The methodological design included data analysis, the postulation of a proposed model, and a validation method for the credit risk analysis model. There is a correlation between the level of schooling of impoverished and vulnerable women with the possibility of self-employment and selling a product or service. In the framework of complex thinking, the perception of innovative thinking is related to the level of education and innovative decision-making in professional projects. Women with a higher level of schooling tend to think about their professional projects systematically. Promoting complex thinking involves innovative educational practices to encourage critical, systemic, scientific, and innovative thinking in entrepreneurship and sustainable development. Integrating reasoning for complexity benefits women and contributes to economic and social growth in vulnerable regions. In contrast to other models, our credit risk analysis model uses AI and variables for gender, vulnerability, and complex thinking to detect patterns in women’s behaviors and attitudes in the venture start-up process. Our proposal is the starting point of many analyses to develop further about artificial intelligence based on complex thinking.
- Remaigining the future through the co-creation of social entrepreneurship in higher education: a multivariate prediction model approach(Emerald, 2024-12-10) Ramírez Montoya, María Soledad; Casillas Muñoz, Fidel; Tariq, Rashik; Icaza Longoria, Inés Álvarez; Portugués Castro, May; EGADE Bussines SchoolPurpose – This remastered analysis focuses on the impact of entrepreneurial interventions in higher education institutions (HEI), particularly in social entrepreneurship. The study evaluated the effectiveness of such interventions through a pre-and post-test approach, examining various skill sets in students. The primary goal was to analyze the influence of entrepreneurial training programs on students’ competencies in social entrepreneurship by analyzing changes in personal behavior, leadership, innovation, social value and management skills before and after the educational interventions. Design/methodology/approach – The study employed a quasi-experimental design, analyzing pre-and post-test results in three distinct social entrepreneurship training experiences. The sample consisted of 304 participants, providing a comprehensive view of the impact of these interventions. Findings – The main findings were: (1) Educational interventions in social entrepreneurship must emphasize strategies for self-awareness, emotional intelligence and personal development improvement. The analysis revealed significant improvements in these areas, indicating that targeted strategies in these domains are essential for enhancing the effectiveness of social entrepreneurship education. (2) The impact of educational interventions on these capabilities can be effectively evaluated using machine learning methods such as ordinary least squares (OLS) regression. This approach allows for the inclusion of variables such as gender, age or location, providing a comprehensive assessment of the interventions’ impact. (3) The interventions were particularly effective in improving students’ innovation and leadership competencies. The analysis demonstrated substantial enhancements in these areas, underscoring the success of the interventions in developing these critical skills. (4) The study highlighted the need for a more focused approach in future interventions, emphasizing the importance of management, social value and personal skills. Additionally, it pointed out the necessity of developing and utilizing appropriate tools to create and evaluate these interventions effectively. Practical implications – The study provides insights into improving educational interventions in social entrepreneurship to better develop essential skills in students. Originality/value – This research introduces a significant approach to educational interventions for educational communities and decision-makers by demonstrating the effectiveness of entrepreneurial training for competencies in innovation and leadership, which are crucial for societal and economic development.
- Serious games and experiential learning:options for engineering education(Università di Genova, 2023-09-04) Pacheco Velázquez, Ernesto Armando; Salinas Navarro, David Ernesto; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504; https://ror.org/05j0ve876This research delves into the use of simulation games as a learning tool in logistics education, with a focus on the Logistics Simulator and Production Game Simulator. Through an analysis of these two cases, relevant findings were uncovered. Firstly, simulation games can recreate concrete experiences, allowing students to engage with challenging problems in a practical manner. In addition, simulation games offer a platform for experimentation with diverse scenarios, enabling students to hone their decision-making skills in a safe environment. Furthermore, the degree of motivation and engagement exhibited by students was found to be positively correlated with their experience gained through simulators. However, while the results obtained from the simulator were associated with student motivation and engagement, the study did not yield conclusive evidence in terms of student learning outcomes. The findings underscore the significance of employing strategies that enhance student motivation and support deep learning, thereby enabling students to apply and transfer knowledge to new situations. Notably, simulation games have great potential in logistics education as they facilitate faster and more enjoyable comprehension of key decision-making factors. Nevertheless, limitations of this study include the small sample size in both cases, which restricts generalizability, and the lack of consideration for sociodemographic factors in the baseline survey. Future research should address these limitations for more reliable findings on the specific needs of students in game-based and experiential learning contexts.
- Gender prediction through complex thinking competence using machine learning(Springer, 2023-06-13) Ibarra Vázquez, Gerardo; Ramírez Montoya, María Soledad; Terashima Marín, Hugo; https://ror.org/03ayjn504This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following data analyses: 1) predict students’ gender based on their perception of complex thinking competency and sub-competencies from a 25 items questionnaire, 2) analyze models’ performance during training and testing stages, and 3) study the models’ prediction bias through a confusion matrix analysis. Our results confirm the hypothesis that the four machine learning models (Random Forest, Support Vector Machines, Multi-layer Perception, and One-Dimensional Convolutional Neural Network) can find sufficient differences in the eComplexity data to classify correctly up to 96.94% and 82.14% of the students’ gender in the training and testing stage, respectively. The confusion matrix analysis revealed partiality in gender prediction among all machine learning models, even though we have applied an oversampling method to reduce the imbalance dataset. It showed that the most frequent error was to predict Male students as Female class. This paper provides empirical support for analyzing perception data through machine learning models in survey research. This work proposed a novel educational practice based on developing complex thinking competency and machine learning models to facilitate educational itineraries adapted to the training needs of each group to reduce social gaps existing due to gender.
- Collaborative online international learning between Spain and Mexico: a microlearning experience to enhance creativity in complexity(Emerald, 2022-11-19) Ramírez Montoya, María Soledad; Romero Rodríguez, José María; Glasserman Morales, Leonardo David; Navas Parejo, Magdalena Ramos; Instituto Tecnológico y de Estudios Superiores de MonterreyThe aim of this paper was to analyse the creative competence of students before and after a microlearning experience carried out in a collaborative online international learning (COIL) environment between Spanish and Mexican university students in the field of education and entrepreneurship. A single-group quasi-experimental design with pretest and posttest measures was adopted. The composition of the group was natural and included a total of 57 students who participated in the COIL experience. The duration was three weeks, where students from both countries were linked together in the development of a microlearning project. The Creativity Self-Efficacy Scale was used as a data collection instrument. The microlearning activities through COIL developed the creative competence of the participating students. In particular, the groups from both universities improved their scores on the creative competence in the post-test compared to the pre-test measure. The limitations of this study were linked to the sample loss of some cases, as some students did not complete the post-test measure. The main implication of the study was to demonstrate that COIL experiences are suitable for developing certain skills in students, such as creative competence or cooperative work. COIL experiences break down the barriers of physical space and give students an active role, allowing them to fully develop competences and offering an intercultural perspective, which encourages open-mindedness and understanding of the world.
- Measurement of the social construction of knowledge: validation and reliability of the K-Social-C instrument(Springer, 2022-04-26) Ramírez Montoya, María Soledad; García Peñalvo, Francisco José; Yañez Figueroa, José Antonio; Instituto Tecnológico y de Estudios Superiores de MonterreyThe social construction of knowledge developed in social innovation laboratories occurs through the open innovation approach, which is the focus of the present study. The study variables were measured with the K-Social-C questionnaire. It was necessary to consider the indicators of each of these variables reported in the literature and the characteristics of construct, content, and criterion validity and reliability to demonstrate solidly that the instrument measures what it is intended to measure. This document confirms the conceptualization and measurement of three variables: social construction of knowledge (SCK), open innovation (OI), and social innovation laboratories (SIL). The K-Social-C questionnaire is a self administered instrument that can measure the three variables and their indicators. The questionnaire's validity and reliability cordance coefficient and the content validity coefficient. We also calculated the internal consistency with Cronbach's alpha as the reliability coefficient. We extended the calculation with exploratory factor analysis and convergent and discriminant validity. However, to study the SCK, OI and SIL variables, we still had to consider the needs and social implications of innovation in each context.