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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
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- 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.
- 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.
- 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.
- 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.
- Transformation and digital literacy: Systematic literature mapping(Springer, 2021-07-15) Farias Gaytan, Silvia Catalina; Aguaded Gomez, Jose Ignacio; Ramírez Montoya, María Soledad; Instituto Tecnológico y de Estudios Superiores de MonterreyThe advancements of technology have allowed digital transformation to reach all productive sectors, including the education sector and its members. This transformation is linked to emerging technologies, the digitalization of processes and resources, and the demand for users to upgrade to the latest technological updates. This research aims to analyze digital transformation and media literacy publications that impact higher education. Its purpose is to identify the types of research and topics they address and explore the scope of digital transformation in higher education institutions. The systematic mapping method was used to analyze 298 articles published in two databases, Scopus and Web of Science (WoS). Inclusion and exclusion criteria were applied to select the articles that could be included in this research. The results show that the largest proportion of articles were found in Scopus, and used both qualitative and quantitative empirical research methods, followed by theoretical-conceptual methods and, to a lesser extent, mixed methods. Likewise, the publications originated in five continents, and the Journal of Adolescent and Adult Literacy had the largest number of publications, with 14. Forty-two percent of the studies were classified in the strategy category, with the most mentioned topic being digital pedagogies. This research provides a perspective on digital transformation studies in higher education institutions and their internalization approaches. This research may be of value to trainers, students, decision-makers, and researchers interested in transformation, educommunication, and educational innovation.
- Gamification: a new key for enhancing engagement in MOOCs on energy?(Springer, 2021-06-15) Mena, Juanjo; Rincón Flores, Elvira Guadalupe; Ramírez Montoya, María SoledadGamification is an innovative educational strategy that uses elements of games for educational purposes, including the completion of appealing challenges to increase student levels of engagement and learning. The objective of this research is to assess the effects of gamification as a teaching method used in a Massive Open Online Course (MOOC) about clean and conventional energy. This research is part of the project “Laboratorio Binacional para la Gestión Inteligente de la Sustentabilidad Energética y la Formación Tecnológica” [Binational Laboratory for the Intelligent Management of Sustainable Energy and Technological Formation]. A total of 4819 participants enrolled in the course, 621 passed the course, and 647 completed the gamified challenge. Results showthe impact of gamification on the cognitive, social, and emotional dimensions, where more than 90% of the participants agreed about feeling more motivated and challenged than when using traditional teaching methods. Therefore, the use of this methodology in online teaching could be very impactful in personalizing and enhancing the learning opportunities of massive, open online courses.