Addressing Enzyme‐Substrate Interaction Misconceptions with 3D Physical Models in an Undergraduate Biochemistry Course

Biochemistry is a visual discipline that requires students to understand a variety of representations containing diverse levels of abstraction to portray information. Visual literacy, however, is not achieved until the learner demonstrates fluency in deconstructing the disciplinary knowledge conveyed within the representation. In biochemistry, the enzyme‐substrate interactions concept not only employs many aspects of visual literacy, but also engenders many learner misconceptions. These previously identified misconceptions are categorized into three groups: the role of shape in substrate selectivity, the role of charge in substrate selectivity and the stereochemical nature of binding. These misconceptions are often held by undergraduate students that have developed previous schemas, which influence the way that they learn new information, as described by cognitive theory. This is compounded by the already high cognitive load in biochemistry, but new learning can be facilitated by simultaneously decreasing the cognitive while addressing misconceptions. In order for a learner to overcome a misconception he/she must confront the incorrect idea and re‐build his/her mental model with new, correct ideas. In one method, researchers utilize a four‐level framework cycle that classifies learner misconceptions, creates questions, gathers learner responses, analyzes the responses, and incorporates that data into helping students reduce and reclassify misconceptions. In this study, we hypothesize that the use of targeted 3D physical models will decrease identified learner enzyme‐substrate misconceptions in biochemistry. Previous research at University of Minnesota Rochester (UMR) indicates a statistically significant increase in enzyme‐substrate interaction conceptual understanding with respect to correct answers, and a corresponding decrease in misconceptions. The average post‐Enzyme‐Substrate Interaction Concept Inventory (ESICI) score (65.8%), however, indicates a need for intervention. We propose that 3D physical models will increase learner visual literacy, thus decreasing the cognitive load to reduce learner misconceptions. Students often find it difficult to extract information from 2D models of macromolecules in biochemistry courses, which are often oversimplified. Thus, presenting concise, appropriately challenging 3D physical models should break down the barriers between misconceptions and facilitate a more realistic experience. The 3D physical models in conjunction with the in‐class activities will challenge student's previous understandings of enzyme‐substrate interactions and be implemented during the fall semester of 2017 in hopes to further increase learner scores on the ESICI. Quantitative statistical analysis will be performed using JMP and Microsoft Excel to assess the intervention's effectiveness. Support or Funding Information This project is partially supported by the National Science Foundation under award number IUSE 1711402 to University of Minnesota, Rochester. This project is partially supported by the National Science Foundation under award number DUE1323414 to Milwaukee School of Engineering. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .