How Four Research Scientists Integrate Methods, Mechanisms, Context, Analogies, and Theory to Communicate Explanations about Protein Folding and Dynamics

Abstract

Biochemistry textbooks often provide a disconnected, highly mathematical, and de‐contextualized treatment of thermodynamics and kinetics. However, science students must be prepared to address real‐world research problems, such as neurodegenerative diseases and the development of protein drugs, where an integrated explanation of the energetics and kinetics behind protein folding and dynamics is critical. There is a paucity of research regarding student ideas about these concepts in biochemistry, and research has also shown that constructing scientific explanations is difficult for students given the complex and abstract nature of many phenomena. Therefore, in order to prepare students to engage in explanatory practices like experts, we must explicitly understand what the explanatory practices are, and how they occur. Previous research into expert biologists' explanations of molecular mechanisms led to the development of the MACH model in which experts integrate research methods and data (M), use analogies (A), provide social or biological context (C), and discuss the activities and organization of entities (H) in their explanations. The present research uses the MACH model as a guiding framework to explore how four expert scientists explain and use representations to communicate models of protein folding and dynamics in their research. The following two research questions were addressed: how do experts apply conceptual knowledge to their methods, data, and representations to generate explanations? (RQ1); and how does experts' conceptual knowledge relate to the practical methods they use in their research process? (RQ2). Interviews informed by the MACH model were conducted with four researchers, selected for their research focus on protein folding and dynamics. Interview transcripts were used to develop ‘expert research profiles.’ A constant comparison method combined with MACH coding was used to analyze excerpts of the four experts' explanations. We found a common pattern of integration and fluid movement between components in the explanations (RQ1); that external and mathematical representations were consistently connected to physical meaning (RQ1/RQ2); and that the explanation of abstract concepts was closely aligned with experts' research methods (RQ2). The results of this study indicate that abstract concepts, as well as mathematical equations, of protein folding and dynamics can be explained in multiple ways. Future research will investigate the ways in which these experts reason with external representations during their explanations. In the long term, the goal is to use these findings to inform the design of educational materials to scaffold the development of students' explanatory skills in this cutting‐edge area of biochemistry.