Combining Visual and Verbal Data to Diagnose and Assess Modeling Competence

Abstract

The prominent role of verbal data in investigating modeling competence becomes obvious in the large number of studies that have used interviews and think-aloud methods to elicit conceptions about models and modeling, thus emphasizing the role of models as research tools. In this chapter, we discuss the characteristics, benefits, and drawbacks of these methods before presenting their broad application in modeling competence research. We furthermore discuss the role of visual data illuminating eye movements as a response to visual stimuli with respect to models and modeling. We thereby introduce eye-tracking technology as a way to expand insights in this field. In addition to providing an overview of how eye-tracking technology has been applied to date in science education, we suggest ways in which verbal and visual data can be triangulated to enrich perspectives on modeling competence.