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Analysis of Thin Online Interview Data

Toward a Sequential Hierarchical Language-Based Approach

University of Western Ontario, rjkitton{at}golden.net

John Barnett

University of Western Ontario

Despite the best of intentions, qualitative researchers can be faced, in some circumstances, with having to make meaning from thin, or less than optimal, data. Using a real study as context, the authors describe the ways that they made sense of their thin data on teachers' perceptions of a large-scale evaluation instrument. They propose a rigorous, sequential approach to e-mail interview analysis based on three hierarchical language levels—lexical, semantic, and pragmatic—to save, by analysis, meanings that might otherwise have been lost because of limited data availability. Researchers are, of course, cautioned to avoid making claims that cannot be substantiated by the data.

Key Words: online interviews • qualitative analysis • thin data

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