Teaching Metabolism in Upper-Division Undergraduate Biochemistry Courses using Online Computational Systems and Dynamical Models Improves Student Performance.

Understanding metabolic function requires knowledge of the dynamics, interdependence, and regulation of metabolic networks. However, multiple professional societies have recognized that most undergraduate biochemistry students acquire only a surface-level understanding of metabolism. We hypothesized that guiding students through interactive computer simulations of metabolic systems would increase their ability to recognize how individual interactions between components affect the behavior of a system under different conditions. The computer simulations were designed with an interactive activity (i.e., module) that used the predict-observe-explain model of instruction to guide students through a process in which they iteratively predict outcomes, test their predictions, modify the interactions of the system, and then retest the outcomes. We found that biochemistry students using modules performed better on metabolism questions compared with students who did not use the modules. The average learning gain was 8% with modules and 0% without modules, a small to medium effect size. We also confirmed that the modules did not create or reinforce a gender bias. Our modules provide instructors with a dynamic, systems-driven approach to help students learn about metabolic regulation and equip students with important cognitive skills, such as interpreting and analyzing simulation results, and technical skills, such as building and simulating computer-based models.

Interactive learning modules with 3D printed models improve student understanding of protein structure-function relationships.

Ensuring undergraduate students become proficient in relating protein structure to biological function has important implications. With current two-dimensional (2D) methods of teaching, students frequently develop misconceptions, including that proteins contain a lot of empty space, that bond angles for different amino acids can rotate equally, and that product inhibition is equivalent to allostery. To help students translate 2D images to 3D molecules and assign biochemical meaning to physical structures, we designed three 3D learning modules consisting of interactive activities with 3D printed models for amino acids, proteins, and allosteric regulation with coordinating pre- and post-assessments. Module implementation resulted in normalized learning gains on module-based assessments of 30% compared to 17% in a no-module course and normalized learning gains on a comprehensive assessment of 19% compared to 3% in a no-module course. This suggests that interacting with these modules helps students develop an improved ability to visualize and retain molecular structure and function.

Student Understanding of DNA Structure-Function Relationships Improves from Using 3D Learning Modules with Dynamic 3D Printed Models.

Understanding the relationship between molecular structure and function represents an important goal of undergraduate life sciences. Although evidence suggests that handling physical models supports gains in student understanding of structure-function relationships, such models have not been widely implemented in biochemistry classrooms. Three-dimensional (3D) printing represents an emerging cost-effective means of producing molecular models to help students investigate structure-function concepts. We developed three interactive learning modules with dynamic 3D printed models to help biochemistry students visualize biomolecular structures and address particular misconceptions. These modules targeted specific learning objectives related to DNA and RNA structure, transcription factor-DNA interactions, and DNA supercoiling dynamics. We also designed accompanying assessments to gauge student learning. Students responded favorably to the modules and showed normalized learning gains of 49% with respect to their ability to understand and relate molecular structures to biochemical functions. By incorporating accurate 3D printed structures, these modules represent a novel advance in instructional design for biomolecular visualization. We provide instructors with the materials necessary to incorporate each module in the classroom, including instructions for acquiring and distributing the models, activities, and assessments. © 2019 International Union of Biochemistry and Molecular Biology, 47(3):303-317, 2019.

Digital Image Analysis for DETCHIP® Code Determination.

DETECHIP® is a molecular sensing array used for identification of a large variety of substances. Previous methodology for the analysis of DETECHIP® used human vision to distinguish color changes induced by the presence of the analyte of interest. This paper describes several analysis techniques using digital images of DETECHIP®. Both a digital camera and flatbed desktop photo scanner were used to obtain Jpeg images. Color information within these digital images was obtained through the measurement of red-green-blue (RGB) values using software such as GIMP, Photoshop and ImageJ. Several different techniques were used to evaluate these color changes. It was determined that the flatbed scanner produced in the clearest and more reproducible images. Furthermore, codes obtained using a macro written for use within ImageJ showed improved consistency versus pervious methods.