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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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- Adaptive evaluation for barriers elimination: The OpenEDR4C platform(IEEEXplore, 2024) Álvarez Icaza Longoria, Inés; Molina Espinosa, José Martín; Suárez Brito, Paloma; Alvarado Reyes, Ignacio; Tecnologico de Monterrey, Institute for the Future odf Education, Monterrey, Nuevo Leon; https://ror.org/03ayjn504The demands of contemporary work and education environments, embodied in Industry and Education 4.0 paradigms, have caused special attention to reducing the digital and educational gap among marginalized students and lifelong learners. Adaptive learning has become a relevant strategy to increase student engagement as it fosters better inclusion, equity, and learning outcome results. Sustainable Development Goal No. 4, Quality of Education, will be reached when every resource, platform, and program can be accessed by individuals regardless of their background, abilities, or capacities in every moment of their lives. The OpenEDR4C is a digital platform created to offer open educational resources (OERs) to scale up the Complex Thinking mega-competence through social, scientific, and technological entrepreneurship training. The platform is also designed to eliminate barriers in five dimensions across the learning path offered by each student according to a self-declared profile. The framework sets a differentiated pathway for the learning experience built with a decision tree and diverse multichannel educational resources. The pilot implementation of the platform allowed the final development stage to validate the functional platform launch. The findings of this study are a helpful contribution to digital education environment design and conceptualization, as they offer (1) a tool for inclusive and accessible platform conceptualization, (2) a profiling strategy framework for adaptive learning paths, and (3) the identification of classes or groups of users based on their needs and characteristics to offer the corresponding content.
- Forecasting gender in open education competencies: A machine learning approach(IEEEXplore, 2023-11-29) Ibarra Vázquez, Gerardo; Ramírez Montoya, María Soledad; https://ror.org/03ayjn504This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and attitudes or values related to open education and its sub-competencies from a 30-item questionnaire using machine learning models to forecast participants' gender, 2) validation of performance through cross-validation methods, 3) statistical analysis to find significant differences between machine learning models, and 4) an analysis from explainable machine learning models to find relevant features to forecast gender. The results confirm our hypothesis that the performance of machine learning models can effectively forecast gender based on the student's perceptions of knowledge, skills, and attitudes or values related to open education competency.
- Scenarios for student-centered learning: RFiD Pocket Lab and IoT Platform as teaching tools(IEEEXplore, 2022-05-11) Crespo Saucedo, Raúl; López Caudana, Edgar Omar; Romo Medrano Mora, Katya Eugenia; Mantilla Caeiros, Alfredo Victor; https://ror.org/03ayjn504This paper contributes to the realization of learner-centered learning scenarios. It is developing an IoT learning platform for different educational levels. On the other hand, the use of “Pocket Labs” is proposed as an effective tool in the meaningful learning of emerging technologies. The fact that these tools can guide the student towards the realization of projects using a set of technologies that are on the rise generate as advantages: an increase in personnel familiar with the IoT, which has an economic impact on the industry, or that the learning is long term, as students develop and improve their understanding. Furthermore, the intention is to develop Information and Communication Tools (ICT) disciplinary competencies, which aligns with the spirit of the Tecnologico de Monterrey’s educational model. Both strategies are a relatively new teaching concept that supports students’ creativity and initiative, allowing them to wear and experiment with actual equipment at any time and place of their choice. Both experiences result in significant long-term learning in fundamental technologies for Education 4.0 and Industry 4.0. These include IoT, RFID (Radio Frequency Identification), NFC (Near Field Communications), Cloud Services, Etc.