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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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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 Soledad
The 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.
Reusable educational resources for developing complex thinking on open platforms
(Springer, 2023-12-01) Sanabria Zepeda, Jorge Carlos; Alfaro Ponce, Berenice; González Pérez, Laura Icela; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504; https://ror.org/01fh86n78
In the context of rapid technological advancements and the increasing availability of Open Educational Resources (OER), there is a growing need to foster complex thinking skills in higher education. The study aims to characterize OER platforms that facilitate the development of such skills, grounded in UNESCO’s recommendations and the evolving definitions of complex thinking. Utilizing a Systematic Literature Review (SLR), the research focuses on three key questions: the type of open license allowing 5R activities, the technical options based on the ALMS Framework, and the sub-competencies of complex thinking that can be nurtured through OER. The study identifies and categorizes key platforms conducive to the development of complex thinking skills, namely innovative, critical, scientific, and systemic thinking. These platforms are analyzed based on their licensing types and technical capabilities. Findings indicate that most of the platforms studied support 5R activities under Creative Commons licenses, require advanced editing skills, and more than half address multiple subcompetencies of complex thinking. The study concludes that the adaptation, reuse, and redistribution of OER can significantly contribute to fostering complex thinking skills, aligning educational practices with 21st-century demands. Recommendations include the development of frameworks by higher education institutions to normalize OER platforms and meet students’ needs, as well as future research to assess user behavior and sustainability of these platforms.
Digital transformation and digital literacy in the context of complexity within higher education institutions: a systematic literature review
(Springer, 2023-07-07) Farías Gaytán, Silvia Catalina; Aguaded Gomez, Jose Ignacio; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504
The incessant changes in technology generate new products and services, presenting multiple opportunities for the complex educational environment. Consequently, higher education institutions must be attentive to these changes to ensure that students have the knowledge and skills necessary for the work environment. This research aimed to identify studies related to digital transformation and digital literacy in higher education institutions through a systematic study of literature. The search resulted in 830 articles published in the Scopus and Web of Science databases from 2015 to 2022. Quality questions, inclusion and exclusion criteria were applied where 202 articles were selected for the study. The results show (a) interest of educational institutions in empirical studies where technologies are incorporated for didactic purposes, (b) challenges of opportunity in training programs to develop digital competences of teachers and students, (c) little interest in the development of media literacy, (d) the methodological aspects of the studies allow exploring new perspectives of digital transformation in higher education. This article may be of interest to academics, decision-makers and trainers of future professionals to introduce educational technology into learning processes in line with the complex demands of the world of work and society.
eComplex: validity and reliability of rubric for assessing reasoning for complexity competency
(Springer, 2023-06-29) Castillo Martínez, Isolda Margarita; Ramírez Montoya, María Soledad; Glasserman Morales, Leonardo David; Millán Arellano, Jorge Antonio; https://ror.org/03ayjn504
In the absence of available instruments that measure reasoning-for-complexity competency in higher education, we designed a rubric to measure university students' levels of mastery of that competency. This article presents the process to estimate the validity and reliability that led to the final version of the "eComplex" rubric, which consists of 27 items. This validation process considered experts' consultation, the internal consistency estimation using Cronbach's alpha coefficient, and correlation matrix analysis, there was also qualitative analysis by reviewing the experts' comments in detail and making the appropriate adjustments. The results were: (a) a high concordance index of the judges for the evaluated criteria of the items, (b) an instrument with high internal consistency and reliability, and (c) improvement in the wording of the items thanks to the observations and contributions of the experts, this was reinforced by conducting a second phase of expert validation using the Delphi Method to provide further support for the Clarity criterion. The instrument is expected to validate measuring the development and appropriation of reasoning-for-complexity competency in university students.
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/03ayjn504
This 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.
Active learning and education 4.0 for complex thinking training: analysis of two case studies in open education
(Springer, 2023-01-25) Ramírez Montoya, María Soledad; Patiño Zúñiga, Irma Azeneth; Buenestado Fernández, Mariana; Instituto Tecnológico y de Estudios Superiores de Monterrey
This article focuses on empirically analyzing the final products designed by 147 academics from 11 countries who participated in an international open education movement workshop by answering the research questions “What are the technopedagogical components of the products designed by the participants to encourage the open educational movement? and what practice of the open educational movement is being executed?” The article starts with a conceptual basis that describes the concepts of Active learning, Education 4.0, Complex Thinking and Open Education. It presents (1) the case study methodology on which this research is based, (2) two case studies on open education, (3) a game‑based intervention proposal to support instructors in training university students in complex thinking skills based on Education 4.0 technologies and game‑based learning principles, (4) and a discussion of the findings and opportunities for further work in the area. The findings of this study reveal that (A) the use of emerging and 4.0 technologies in initiatives of the open education movement continue to increase; (B) most of the open education initiatives designed by academics participating in the workshops were focused on the production of OER; and (C) inclusive access to education and continuing professional development of teachers is a constant concern addressed in open education initiatives. The results of this research suggest that training and development interventions implying the creation or design of open education initiatives should focus on encouraging all kinds of open education practices (i.e. use, production, dissemination and mobilization)
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 Monterrey
The 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.
Effects of the use of simulators and an online platform in logistics education
(Springer, 2022-01-04) Pacheco Velázquez, Ernesto Armando; https://ror.org/03ayjn504
During the last decade, Big Data, Cloud Computing, Artificial Intelligence, Internet of Things, Machine Learning, Simulators, Virtual Reality, Augmented Reality, and other innovations associated with the development of information and communication technologies (ICTs) have transformed the paradigms of all societies. As a consequence, are requesting new skills from workers and this has led to changes in educational processes. As a response to these new needs, the use of educational platforms and simulators has increased substantially in the last decade and a large amount of literature has been generated in relation to the critical success factors of these platforms. However, there is a very limited number of articles that attempt to explain how these factors are related to the development of other types of skills or motivational factors. The objective of this work is to evaluate the effectiveness of the "GOAL Project" platform (used to transmit logistics concepts) by exploring the opinion of students about the critical success factors of educational platforms and to determine how these elements influence motivation and development of skills such as student engagement, reflection on their learning and self-directed learning.
Spatial analysis of exposure to traffic‐related air pollution in Mexico: Implications for urban planning to improve public health
(Springer, 2021-08-08) Martínez Salgado, Hilda; Garnica Monroy, Ruben; Garibay Bravo, Veronica; Gonzalez Gonzalez, Alonso; Hernández Reyes, Malinalli; Tecnologico de Monterrey, Escuela de Arquitectura, Arte y Diseño; Instituto Tecnológico y de Estudios Superiores de Monterrey
In cities, traffic is one of the major determinants for air quality. Studies have shown that proximity to roadways with heavy traffic has been linked with increased incidence and prevalence of a range of health effects such as adverse birth outcomes, dementia, asthma, and increased risk of bronchitis, wheezing, deficits in lung function growth and airway inflammation, especially among children. In Mexico, 103 urban areas have air quality monitoring, whilst more than 2,000 cities lack any information and only 29 have monitoring systems that are robust enough to estimate exposure. This poses serious limitations for environmental and health authori- ties when aiming at assessing current exposure levels to Traffic-Related Air Pollution (TRAP) with the purpose of designing and implementing policies to reduce the impacts of poor air quality in the population. This study proposes an approach to estimate the population potentially exposed to TRAP using Space Syntax’s accessibility index as the urban form variable. We selected the ten most accessible roads of the five Mexican cities to estimate the proportion of vulnerable population (residents, employees, schoolchildren, hospital patients) with the highest potential expo- sure to TRAP at a distance of 500 m. Our findings show a similar proportion of the population continually exposed to TRAP due to the proximity to roads with heavy traffic than studies using more complex models. Finally, this study presents alternatives to reduce current population exposure to traffic emissions in Mexican cities.
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 Monterrey
The 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.

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