A Deep Look into Designing a Task and Coding Scheme through the Lens of Causal Mechanistic Reasoning

The purpose of this paper is to share the iterative process we used to design a task that elicits causal mechanistic reasoning and how the subsequent student responses can be analyzed. Our goal in this task is to strike a balance between eliciting as much student knowledge as possible without providing so much structure that the answer becomes obvious. The task development was approached using (1) a resources perspective of learning, (2) principles of scaffolding, and (3) evidence-centered design, for which we specified evidence that would be considered a fully causal mechanistic explanation. That is, an explanation which pays explicit attention to the properties, interactions, and behaviors of entities that are involved at a scalar level below the phenomenon under consideration. Since our eventual goal is to characterize how students use knowledge across disciplinary boundaries, the phenomenon of protein-ligand binding was chosen as the context for this task, because it requires students to apply ideas learned in chemistry courses to a biological phenomenon. After three rounds of iterative refinement, a final task was developed. To characterize students' responses to this task, we developed a coding scheme which can be used to code explanations based on the presence or absence of three key ideas relevant to this phenomenon. In this paper, we share the detailed processes and approaches used in task development, which we hope will provide insight into instructors and researchers as they, too, develop such tasks to explore student reasoning.