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Permanent URI for this collectionhttps://hdl.handle.net/11285/636173
Parte de documentos que muestran resultados de investigación, no arbitrados, con fines de informar a una comunidad u obtener apoyo, tales como resultados de reportes estadísticos, reportes de avance, etc.
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- Appendix 7. Design the platform with Industry 4.0 features. Technical report stage 1. Project S4L: Simulating for learning(Institute for the Future of Education, 2023-05-31) Alcántar Nieblas, Carolina; https://ror.org/03ayjn504Appendix 7. Design the platform with Industry 4.0 features. Technical report stage 1. Project S4L: Simulating for Learning
- Appendix 1. Instructional Design. Technical report stage 1. Project E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity(Institute for the Future of Education) Ramírez Montoya, María Soledad; https://ror.org/03ayjn504Objective 1: Design and development. Design and develop a platform hosting a digital ecosystem that integrates (i) instructional procedures for understanding computational problem solving with various degrees of complexity and (ii) automated tools based on learning analytics, artificial intelligence, games, machine learning, and data science that allow to extract data to analyze behaviors and scale up reasoning for complexity and computational thinking.
- Diseño del instrumento PCM-Complexity(Institute for the Future of Education) Tenorio Sepulveda, Gloria Concepción; https://ror.org/03ayjn504Evidencia de actividades del proyecto de investigación E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity
- Appendix 5. Instructional procedures for understanding computational problem solving. Technical report stage 1. Project E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity(Institute for the Future of Education) Ibarra Vazquez, Gerardo; Pirzado, Farman Ali; https://ror.org/03ayjn504Objective: The instructional procedures for understanding computational problem solving with various degrees of complexity and the quality of the automated tools based on learning analytics, artificial intelligence, machine learning, and data science to analyze behaviors and scale up reasoning for complexity and computational thinking will be evaluated with internal focus group processes (indicators of collaboration indexes and results)
- Diseño de instrumento CTC4(Institute for the Future of Education) Patiño Zúñiga, Irma Azeneth; https://ror.org/03ayjn504Evidencia de actividades realizadas en el marco del proyecto E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity
- Designing automated tools for computational thinking analysis(Institute for the Future of Education) Pirzado, Farman AliEvidence of research project activities. Project name: E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity.
- Appendix 15: Stays. Technical report stage 1. Project E4C&CT Project report(Institute for the Future of Education) Glasserman Morales, Leonardo David; https://ror.org/03ayjn504Appendix 15. Stays
- Appendix 3. Design of the digital ecosystem. Technical report stage 1. Project E4C&CT Project report(Institute for the Future of Education) Terashima Marín, Hugo; Mendoza Urdiales, Román Alejandro; Ibarra Vazquez, Gerardo; https://ror.org/03ayjn504Objective 1: Design. Design a platform hosting a digital ecosystem that integrates (i) instructional procedures for understanding computational problem solving with various degrees of complexity and (ii) automated tools based on learning analytics, artificial intelligence, games, machine learning, and data science that allow to extract data to analyze behaviors and scale up reasoning for complexity and computational thinking.
- Appendix 9. Total SCOPUS articles. Technical report stage 1. E4C&CT Project report(Institute for the Future of Education) Vázquez Parra, José Carlos; https://ror.org/03ayjn504Total SCOPUS articles: List of articles.
- Appendix 2. Automated tool design. Technical report stage 1. Project E4C&CT: Ecosystem for scaling up computational thinking and reasoning for complexity(Institute for the Future of Education) López Caudana, Edgar Omar; https://ror.org/03ayjn504Objective 1: Design and development. Design and develop a platform hosting a digital ecosystem that integrates (i) instructional procedures for understanding computational problem solving with various degrees of complexity and (ii) automated tools based on learning analytics, artificial intelligence, games, machine learning, and data science that allow to extract data to analyze behaviors and scale up reasoning for complexity and computational thinking.