A conceptual representation and modeling to support ecosystem learning
The use of conceptual representations specially with modeling tasks has been shown to help students organize their thinking about complex systems. In this talk, I will discuss the refinement and use of a conceptual representation developed to help students reason about ecosystems. In this study, the PMC (Phenomena Mechanisms Components) conceptual representation was paired with an interactive modeling tool that enabled learners to create and support explanations using evidence. Using pre-post drawing task assessments, my co-authors and I tested the hypothesis that after completing a PMC-evidence and explanation rich ecology curriculum, students would create more mechanistic explanatory models.
We found that post-intervention, students incorporated more mechanisms into their models. More specifically, we found that pre- to post-instruction models contained an increase in accounting for phenomena using causal explanations. Progressing from their initial models, students provided more sophisticated (i.e., mechanistic and data driven) models with time. The models developed by students earlier in the instruction tended to feature a 1 to 1 or linear narrative to support explanations for the phenomena. The later models tended to be either linear as described above or more dynamic to support explanations. In these models, we found embedded cycles and feedback loops. Our post-hoc analysis found that model sophistication correlated with course achievement, even though models and modeling were not a significant part of the course grade. In conclusion, we suggest that cognitive tools such as PMC may enable students to transfer ideas. Because individuals using PMC create generic mechanisms to explain ideas, learning transfer to novel ecosystems may occur.