LEARNING TO BUILD SCIENTIFIC MODELS THROUGH INDUCTIVE GENERALIZATION

Modeling is an important scientific practice in the Framework for K-12 Science Education (NRC, 2012) and the Next Generation Science Standards (NRC, 2013). Developing, testing, evaluating, and revising models are not only important scientific skills; they also comprise an effective way to learn scientific principles. Modeling is also a central form of inquiry in the geosciences. An important issue for science education is that there are many possible approaches to modeling and learning through models, few of which are well developed.

In this empirical study, we describe a novel approach to modeling instruction conducted during a teacher professional development (PD) session in which the objective was to build a generalized scientific model by combining two or more models of different phenomena which shared a common essential structure. We refer to this approach as modeling through inductive generalization. The learners in the study were middle and high school teachers engaged in a modeling unit designed for high school students. Data sources include pre and post-assessments, artifacts collected during the PD session, and videotape and audiotape data recorded as teachers developed and revised models.

The data show how the teachers reasoned across two related models to identify similarities and differences and eventually constructed a generalized model reflecting the deeper, underlying structure. The data also show how teachers came to appreciate key attributes of a good generalized model, and what it took to learn generalized models. Future work will be conducted as teachers enact the modeling unit in their classrooms to understand the ways teachers enact model-based inquiry and to understand how students reason across related models to construct generalized models.