Identifying aspects of complex and technological systems in the mental models of students who constructed computational models of electric circuits

Electricity, especially the flow of current, is a challenging topic for students of all ages. This study conceptualizes students' explanation of electric current as a cluster of knowledge elements. These clusters, in turn, represent students' mental models of electric circuits. Thus, this study aims to identify and characterize students' mental models of electric circuits and to determine, through these mental models, how the students' perception of electric circuits changed as they constructed and explored micro-level computational models. Using clustering methods, we identified five mental models, ranging between a naive technology perspective model and a more advanced complex systems perspective model. We employed a quasi-experimental, pretest-intervention-posttest-comparison-group design, comparing the mental model development of 33 students who constructed models of electric conductors using the Much.Matter.in.Motion (MMM) modeling platform, with that of 23 students who learned in a normative curriculum. Both groups completed identical pre- and posttest questionnaires, and three students from the experimental group were interviewed before and after the intervention. As expected, we found that students who learned by constructing computational models with the MMM platform exhibited greater shifts in the sophistication of their mental models compared with students who experienced the normative teaching approach.