Using graph‐based assessments within socratic tutorials to reveal and refine students' analytical thinking about molecular networks

Abstract

Biological systems, from the molecular to the ecological, involve dynamic interaction networks. To examine student thinking about networks we used graphical responses, since they are easier to evaluate for implied, but unarticulated assumptions. Senior college level molecular biology students were presented with simple molecular level scenarios; surprisingly, most students failed to articulate the basic assumptions needed to generate reasonable graphical representations; their graphs often contradicted their explicit assumptions. We then developed a tiered Socratic tutorial based on leading questions designed to provoke metacognitive reflection. The activity is characterized by leading questions (prompts) designed to provoke meta-cognitive reflection. When applied in a group or individual setting, there was clear improvement in targeted areas. Our results highlight the promise of using graphical responses and Socratic prompts in a tutorial context as both a formative assessment for students and an informative feedback system for instructors, in part because graphical responses are relatively easy to evaluate for implied, but unarticulated assumptions.Keywords: Molecular networks, Socratic tutorials, graphing, undergraduate education.Dynamic interaction networks, whether at the molecular, cellular, developmental, physiological, or ecological level, are a universal feature of biological systems. These networks can be homeostatic, adaptive, evolving, or commonly a combination of all three. They typically involve a defined set of entities, i.e. molecules, genes, cells, tissues, organs, organisms, populations, etc. and a defined set of interactions. In molecular biology, these include activation, repression, assembly, modification, stabilization, degradation, and altered localization. Predicting the behavior of such networks and how they respond to perturbations is not a simple skill, yet this type of thinking lies at the heart of a robust understanding of what characterizes living systems and their behaviors. At the cellular and molecular levels, threshold effects, feed-back and feed-forward interactions, and redundant pathways, together with the stochastic nature molecular events, all make significant contributions to system behavior. The recent explosion in the number of direct observations [see 1, 2] and data-driven models of molecular level network behavior [see [3][4][5][6][7] has been followed by a growing recognition of the importance of understanding the behavior of regulatory circuits, particularly their emergent behaviors in the context of biological systems [8][9][10][11][12].The challenges involved in reaching an understanding of molecular level networks can be illustrated by considering the lac operon of E. coli [13] (Fig. 1). While often presented as a simple system, the lac operon is part of a complex network. The operon itself contains three genes, lacZ, lacY, and lacA. A distinct gene, lacI, encodes the lac repressor polypeptide. The functional lac repressor protein is a tetramer of LacI polypeptide...

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