Considering the nature of scientific problems when designing science curricula

A recurring theme of science education reform has been the creation of classroom opportunities that allow students to develop insights into the professional practice of scientists. The posing and solving of problems of a variety of types, a process central to scientific practice, provides a useful framework for structuring such opportunities for students. Most problems that students encounter can be characterized as model–data fit problems, in which solvers fit available data to an appropriate explanatory model. Although these problems are important, we argue that it is essential to expand the range of problems students encounter to include those that require solvers to confront the conceptual coherence of their explanatory models and to examine the relationship of those models to other scientific models, methodological norms, and common worldviews. In this article, we describe the nature and existence of both model–data fit and conceptual problems in science and then examine two curricular projects, one in genetics and one in evolutionary biology, that attempt to integrate these problems into classroom instruction.