Learning chemistry requires both, mastery of abstract concepts and development of the ability to use representations to explain and communicate about concepts. The latter skill is known as representational competence, or a set of practices to reflectively use a variety of representations to support claims, draw inferences, and make predictions about chemical phenomena. Despite the important role that representational competence plays in student success in chemistry and the considerable number of investigations into student ability to reason with representations, little is known about instructors’ approaches toward helping students develop this set of skills. This case study provides the first characterization of organic chemistry instructors’ intensions and practices toward cultivating representational competence skills in their students. Three organic chemistry instructors participated in semi-structured interviews that explored their goals for developing student representational competence, as well as their Pedagogical Content Knowledge (PCK) for teaching this set of skills. The interview data were triangulated with course artifacts data including syllabi, lecture slides, and assessments. Various frameworks were used to deductively code the interviews and course artifacts data: Kozma and Russell’s representational competence framework, Geddis’ PCK framework, Ainsworth’s functional taxonomy, and Johnstone’s triplet. Triangulation of different sources of data and theories to characterize instructors’ approaches toward teaching with representations will be presented.

Multi-framework case study characterizing organic chemistry instructors’ approaches toward teaching with representations

ACS Spring 2022

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