Moser et al. (2017): ficha de referencia
Referencia (APA 7): Moser, S., Zumbach, J., & Deibl, I. (2017). The effect of metacognitive training and prompting on learning success in simulation‐based physics learning. Science Education, 101(6), 944–967. https://doi.org/10.1002/sce.21295
Capítulo: Cap. 1 – Antecedentes · Subcategorías: A2 Misma herramienta, distinta mediación (guía y andamiaje) · Mapa: MOC - Mapa de contenidos
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Aporte a la tesis
Entrenamiento metacognitivo y prompts en aprendizaje con simulaciones de física
Resumen del autor
Resumen tomado de OpenAlex, en el idioma original.
Abstract Computer‐based simulations are of particular interest to physics learning because they allow learners to actively manipulate graphical visualizations of complex phenomena. However, learning with simulations requires supportive elements to scaffold learners’ activities. Thus, our motivation was to investigate whether direct or indirect metacognitive scaffolding (i.e., training and prompting, respectively) or a combination of both during simulation‐based learning leads to better learning outcomes compared to simulation‐based learning alone. Employing a 2 × 2 factorial design ( N = 99 Austrian secondary school students), we explored the role of metacognitive training prior to the use of simulations and the role of metacognitive prompting during the learning phase. Four different conditions were compared in relation to knowledge about the principle of energy conservation. A pre‐ and posttest assessing knowledge acquisition, metacognitive behavior, cognitive load, and mental effort was applied. At first glance, the results indicate no main effects for training and prompting, and no interaction effect. A closer look at the actual use of prompting after the empirical data were obtained, however, reveals a significant impact of the metacognitive strategies employed on performance in the posttest, with higher scores in the condition where appropriate prompting was used. This result emphasizes the importance of guidance during simulation‐based learning.