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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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- Apéndice 2. Reseña de participación en congreso en el cual se difunda acciones del proyecto(2024-11-04) Alcántar Nieblas, Carolina; Rodés Paragarino, Virginia; https://ror.org/03ayjn504Apéndice 2. Reseña de participación en congreso en el cual se difunda acciones del proyecto.
- Apéndice 5. Documento de formulación conceptual del mockup para portal CREA y mejores prácticas de portales educativos abiertos(2024-02-10) Rodés Paragarino, Virginia; Torres Hernández, Joel; https://ror.org/02thjp576Apéndice 5. Documento de formulación conceptual del mockup para portal CREA y mejores prácticas de portales educativos abiertos.
- Appendix 8-S4L- Stage 1 Research activities: Analysis of the data collected with qualitative instruments, an axial coding process will be followed with ATLAS.ti.(Unidad de Tecnología Educativa, IFE, 2023-05-16) Rodés Paragarino, Virginia; Instituto para el Futuro de la Educación; https://ror.org/03ayjn504For the analysis of the data collected with qualitative instruments, an axial coding process will be followed with ATLAS.ti. For quantitative data, correlation and inferential analysis will be employed with SPSS statistical software. For the final analysis, data triangulation will be performed with quantitative and qualitative inputs. Throughout the process, care will be taken to follow ethical guidelines by ensuring the confidentiality of the data provided by the participants and the signing of letters of acceptance to participate in the research, emphasizing that it is a voluntary participation.
- Challenge Simulating for Learning (S4L) deliverable 2 phase 1 - activity 3: Design and architecture of the platform(Unidad de Tecnología Educativa, IFE, 2023-05-15) Rodés Paragarino, Virginia; Instituto para el Futuro de la Educación; https://ror.org/03ayjn504Matching the design and architecture of a platform with the characteristics of the participants involves a user-centered approach. First, it is essential to understand the participants by gathering demographic information and assessing their technical expertise. Next, identify their needs and goals through user research to tailor the design accordingly. The platform should prioritize usability, accessibility, and personalization, allowing participants to customize their experience. It should be scalable, flexible, and seamlessly integrate with existing systems while ensuring security and data privacy. Optimizing performance and continuously gathering participant feedback for improvement are also crucial. In summary, matching the platform's design and architecture with participant characteristics requires understanding their needs, goals, and technical expertise. It involves prioritizing usability, accessibility, and personalization while ensuring scalability, integration, security, and performance optimization. Continuous improvement through participant feedback ensures the platform remains aligned with their evolving requirements.
- Challenge Simulating for Learning (S4L) deliverable 2 phase 1 - activity 2: Characteristics design report(Unidad de Tecnología Educativa, IFE, 2023-05-15) Rodés Paragarino, Virginia; Instituto para el Futuro de la Educación; https://ror.org/03ayjn504To design an efficient and effective logistics simulation platform, several characteristics should be considered. Firstly, the design architecture should be modular and scalable, allowing for easy modifications and expansion as the needs of the users and the platform evolve. The architecture should be flexible enough to accommodate different types of users, from students to entrepreneurs and researchers, and allow for the customization of user profiles and interfaces. It should also support the integration of open educational resources (OERs) and other educational materials. Secondly, the information flow within the platform should be smooth and transparent. Users should be able to access the data they need quickly and easily, and the platform should provide real-time feedback and support to users during the simulation process. The platform should also be able to generate data and reports on user performance, decision-making, and other key metrics to aid in assessment and evaluation. Thirdly, the programming particularities of the platform should prioritize the use of realistic and relevant logistics scenarios and data. The platform should incorporate demand forecasting and other relevant metrics, as well as allow for the simulation of different supply chain scenarios and logistics network designs. The platform should also incorporate features that promote complexity, systemic thinking, and problem-solving, such as randomized labyrinth structures and decision-making assistant tools. Overall, the ideal characteristics for the design architecture, information flow, and programming particularities of the platform should prioritize flexibility, scalability, and relevance to real-world logistics scenarios. The platform should also prioritize user experience and engagement, incorporating features such as microlearning videos and gamification elements to enhance learning outcomes.
- Challenge simulating for learning (S4L) deliverable 1 phase 1 - activity 1:interdisciplinary team(Unidad de Tecnología Educativa, IFE, 2023-05-15) Rodés Paragarino, Virginia; Instituto para el Futuro de la Educación; https://ror.org/03ayjn504To form an interdisciplinary team for the selection of features to be considered in the creation of the LCMS platform, individuals from various disciplines will need to come together and collaborate. This team should ideally include professionals from fields such as education, information technology, instructional design, and content development, among others, to ensure that all aspects of the platform's development are considered. The interdisciplinary team's primary objective will be to determine the essential features that the LCMS platform, including the simulator, should possess to meet the needs of its intended users. They will need to evaluate the current platform's functionalities, including its architecture, information flow, and programming specificities, to ensure that the platform is both efficient and effective. This interdisciplinary team will play a crucial role in the success of the LCMS platform by bringing together diverse perspectives and expertise to create a comprehensive and user-friendly product. Through close collaboration, the team will be able to identify the features that are essential to the platform's success and work together to ensure that they are seamlessly integrated into the platform's design.
