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Abstract
BackgroundComputational modeling is an increasingly common practice for disciplinary experts and therefore necessitates integration into science curricula. Computational models afford an opportunity for students to investigate the dynamics of biological systems, but there is significant gap in our knowledge of how these activities impact student knowledge of the structures, relationships, and dynamics of the system. We investigated how a computational modeling activity affected introductory biology students’ mental models of a prokaryotic gene regulatory system (lac operon) by analyzing conceptual models created before and after the activity.ResultsStudents’ pre-lesson conceptual models consisted of provided, system-general structures (e.g., activator, repressor) connected with predominantly incorrect relationships, representing an incomplete mental model of gene regulation. Students’ post-lesson conceptual models included more context-specific structures (e.g., cAMP, lac repressor) and increased in total number of structures and relationships. Student conceptual models also included higher quality relationships among structures, indicating they learned about these context-specific structures through integration with their expanding mental model rather than in isolation.ConclusionsStudent mental models meshed structures in a manner indicative of knowledge accretion while they were productively re-constructing their understanding of gene regulation. Conceptual models can inform instructors about how students are relating system structures and whether students are developing more sophisticated models of system-general and system-specific dynamics.
Highlights
Modeling and model-based reasoning are important scientific processes that encompass the way scientists interact with phenomena
We investigated changes in students’ conceptual models and asked two research questions: (1) what do conceptual models reveal about changes in students’ mental models of gene regulation and (2) how do students apply this mental model during a computational modeling activity? We hypothesized that completing computational modeling activities would improve students’ knowledge of the structures and relationships of gene regulation by reinforcing, replacing, removing, and improving quality of the relationships within the system
We assume that students enhanced their understanding of the system functionality by first creating a conceptual model, using a computational model to simulate the dynamics, because students would have engaged their mental model of gene regulation before conducting thought experiments to predict and explain the dynamics
Summary
Modeling and model-based reasoning are important scientific processes that encompass the way scientists interact with phenomena There are different types of modeling practices that fall under the umbrella of model-based reasoning, including visual modeling and thought-experiments (Nersessian 1999; Seel 2017). Because modeling is so intricately tied to scientists’ work, it follows that modeling should be reflected in classroom practices where students can develop skills necessary to reveal the mechanisms of phenomena, like scientists. Creating a model is part of the modeling process that includes practices like making predictions, evaluating data outcomes, and revising the model (Brewe 2008; Fretz et al 2002; Sins et al 2005). We investigated how a computational modeling activity affected introductory biology students’ mental models of a prokaryotic gene regulatory system (lac operon) by analyzing conceptual models created before and after the activity
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