Thinking like a scientist: Strategies to measure and improve knowledge structures of biology students

Learners categorize information differently depending on whether they are “experts”, “novices”, or somewhere in between. Expert learners have complex knowledge structures (many connections between concepts, hierarchical categorization) compared to novice learners, facilitating expert learners’ ability to transfer knowledge or skills to new scenarios. Complex knowledge structures can therefore help undergraduates “think like scientists,” facilitating their ability to integrate concepts in complex ways, and apply knowledge learned in courses to new questions and situations. However, even senior undergraduates in upper level courses seem to struggle with applying their knowledge appropriately, and we hypothesize that this stems from underdeveloped knowledge structures. In this presentation, we discuss our development of a sorting task tool to assess the knowledge structures of Biology students at XX University. This type of tool has been used previously in science education research to determine the depth of knowledge structure based on how learners categorize statements. Our biology-specific tool distinguishes between first year undergraduates, upper year undergraduates, and graduate students enrolled in Biology programs, suggesting increased knowledge structure complexity as students progress through post-secondary education. We also observe changes in sorting task performance during a single semester third-year animal physiology course. By the end of the presentation, participants will be able to explain how a sorting task can be administered and analyzed to determine the extent to which learners are “novices” or “experts”, and the limitations of this tool for assessing knowledge structure. We will also discuss interventions that instructors can use to accelerate increasing complexity of knowledge structures