AI generated context for teaching robotics to improve Computational Thinking in Early Childhood Education
There is a growing need to develop methods to teach Computational Thinking (CT) to Early Childhood Education children, given the challenges at these ages. A key goal is to equip future teachers with effective approaches for better learning outcomes. This project introduces a methodology for teaching...
| Autores: | , , , |
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| Tipo de recurso: | conjunto de datos |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consorcio Madroño |
| Repositorio: | e-cienciaDatos, Repositorio de Datos del Consorcio Madroño |
| OAI Identifier: | doi:10.21950/KJNKMM |
| Acceso en línea: | https://doi.org/10.21950/KJNKMM |
| Access Level: | acceso abierto |
| Palabra clave: | Computer and Information Science Early Childhood Education Robotics Computational Thinking Generative AIs Preservice Teachers |
| Sumario: | There is a growing need to develop methods to teach Computational Thinking (CT) to Early Childhood Education children, given the challenges at these ages. A key goal is to equip future teachers with effective approaches for better learning outcomes. This project introduces a methodology for teaching robotics, using AI-generated contexts to enhance CT. An experiment was conducted with 120 preservice teachers (aged 18-19) in a Computer Science and Digital Competence course. The experimental group used AI-generated practical assignments, while the control group did not. Results show significantly higher gains in CT and learning attitudes in the experimental group, proving the methodology's effectiveness. The sample for this study: Students of Universidad Rey Juan Carlos (URJC) in Madrid, Spain -> Early Child-hood Education degree programme. |
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