Contributions of model-based learning to the restructuring of graduation students' mental models on natural hazards

7Citations
Citations of this article
34Readers
Mendeley users who have this article in their library.

Abstract

Model-Based learning is a methodology that facilitates students' construction of scientific knowledge, which, sometimes, includes restructuring their mental models. Taking into consideration students' learning process, its aim is to promote a deeper understanding of phenomena's dynamics through the manipulation of models. Our aim was to ascertain whether the use of three different types of models, integrated into an intervention program whose goal was to teach the "seismic effects on soils and buildings", would influence the learning process of graduation students or not. For a better understanding of the results, the data were collected and analyzed through a combination of methods using, simultaneously, quantitative and qualitative method. And results not only confirmed the importance of the use of models, but also led us to the conclusion that despite the potential and limitations of all three models, mixed models are better for restructuring students' mental models and the development of meaningful learning.

Cite

CITATION STYLE

APA

Moutinho, S., Moura, R., & Vasconcelos, C. (2017). Contributions of model-based learning to the restructuring of graduation students’ mental models on natural hazards. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 3043–3068. https://doi.org/10.12973/eurasia.2017.00704a

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free