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MENTAL MODELS ABOUT NATURAL HAZARDS: A STUDY WITH GRADUATION STUDENTS

PhD Student Sara Moutinho, Assoc. Prof. Dr. Rui Moura, Assoc Prof. Dr. Clara Vasconcelos

Abstract

According to Johnson LairdsпїЅ Mental Models Theory, people develop internal representations of the natural world пїЅ mental models пїЅ that they use to interact with the world and understand the phenomena around them. Having this in mind, we could understand that students develop their knowledge through the construction of mental models, which help them to develop scientific reasoning and make decisions, being the basis of individual behaviors. In this context, it is assume that the use of methodologies that enable students to restructure their mental models to make them more consistent with the scientific models. Model-Based Learning is a methodology that allows students to construct their knowledge, through the manipulation of models that promote an autonomous, dynamic, motivating and meaningful learning. Based on Model-Based Learning it was developed an intervention program which included the manipulation of three types of models пїЅ computational model, physical model and a mixed model пїЅ that allows the study of the seismic effects on soils and buildings. This intervention program was applied to 20 graduation students from a public university in Portugal. This work aimed to analyze the development of 20 graduation studentsпїЅ knowledge about the natural hazards trough their answers in a pre and post-test, applied before and after the intervention program, where they could manipulate the three types of models to solve some problems related to seismological hazards. The analysis of the results led us to conclude that the post-test, applied after the intervention program, allows seeing a significant increase in studentsпїЅ knowledge, related to natural hazards. As so, the authors argue that the use of models should be more explored in science education, because they are important in the learning process, since they help students in the restructure of their mental models, to make them more congruent with the scientific models.

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DOI resolver: doi.org/10.5593/sgem2017/54/s22.014

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