Methodological challenges for identifying and coding diverse knowledge elements in interview data
Victor R. Lee, Moshe Krakowski, Bruce L. Sherin, Megan Bang, Gregory Dam · Digital Commons - USU (Utah State University) · 2006
This paper, as part of a symposium on the analysis of clinical interview data and the development of a framework for analyzing students' intuitive science knowledge, identifies and discusses methodological challenges encountered when specifying the knowledge elements and resources are invoked dynamically during a clinical interview. Drawing from interviews with middle school students about the seasons and an analysis of knowledge in terms of 'nodes', two classes of problems are identified: those associated with identification of nodes and those associated with their application as codes to a transcript-based data corpus. We posit that these challenges are common ones associated with any form of fine-grained knowledge analysis and describe some analytical decisions we made in light of these challenges.