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Interaction analysis is a valuable method and approach to study knowledge in use in the learning sciences and CSCL communities. Central to interaction analysis is the creation of transcripts to selectively encode and represent audio and video data. However, current transcription techniques used in interaction analysis, including multimodal transcription techniques, have yet to explore the strengths and weaknesses of interactive visualization to selectively encode and represent people’s interaction in context. Drawing from our recent efforts to amplify, not automate, transcription in qualitative research, this paper interactively visualizes one video dataset in five different ways using contemporary interactive visualization techniques. Findings and discussion characterize these visualizations as interactive transcripts that demonstrate techniques valuable to interaction analysis, but also highlight the need to expand how people, things, and context are represented through visualization mediums such as visualization programming languages to align with work more meaningfully in the learning sciences and CSCL communities.
Mathur, Arpit and Shapiro, Benjamin R., "Interactive Transcription Techniques for Interaction Analysis" (2022). Learning Sciences Faculty Publications. 46.