Learning Natural Selection Through Computational Models in a High School A.P. Biology Classroom

Abstract

Science education communities understand the importance of computational thinking but lack empirically tested learning materials. We report the implementation of a computationally driven natural selection unit in an A.P. high school biology classroom. Epistemic network analyses of student responses indicate that computational tools can facilitate learning of natural selection, and to varying degrees. We interpret these results to show that attention should be given to the fit between computational tools and natural selection concepts.