Assessing Learners' Understanding of Conceptual Models and its Relationship with Causal Reasoning Skills

Model-based reasoning, such as causal reasoning, is one of the most important cognitive skills in science education, although model-based teaching, especially computer models, have a positive effect on reasoning, but model understanding can also affect its application and usefulness. The purpose of this research is to investigate the relationship between students' models' understanding and the level of causal reasoning skills. This relationship was investigated when performing bifocal modeling with the subject of mechanics. A sample of 85 secondary high school students in Ahvaz was selected, and were asked to answer four questions related to mechanic descriptively during modeling and write their reasoning. Codes were first defined and answers were scored based on the codes. After modeling, the students answered the model understanding questionnaire and based on that, with the cluster analysis, they were classified into two categories: "model ideal understanding" and "model raw understanding". The findings showed that the students who had a good understanding of the model and the modeling process, except in the reasoning identifying the elements, which all performed similarly, were more successful in other dimensions of causal reasoning than the students who had a raw model understanding  Researchers have found that paying more attention to scientific modeling in official curricula, informing teachers about the models' nature, and encouraging them to teach based on models in the classroom are effective in improving students' models' understanding, and it strengthens thinking, including scientific reasoning.