New technologies providing more detailed accounts of learner behaviors require novel approaches to transcription. This study elicited data concerning learners’ cognitive / affective processes and related behaviors. Juxtaposing second-by-second psychometric variations against observable phenomenon required various non-standard transcriptions; their respective strengths and weakness becoming evident during transcription, analysis, and writing-up.
Responding to the issues of how and how much nonverbal data to make available during multimodal transcription requires researchers to experiment with variations in how social events and artifacts are registered for diverse readerships. This problem is likely to be amplified in the future as researchers develop new methodologies to access more sensitive levels of data concerning learner behaviors. Idiodynamic methodology is a novel, mixed methods approach to investigating the relationships between a learner's cognitive / affective processes and various behaviors and other phenomena in the classroom. Researchers use software to elicit psychometric factors quantitatively as well as qualitatively. This new source of data creates further challenges for transcribers. Firstly, how can various relationships between non-observable psychometric data and observable phenomenon be represented? Furthermore, access to internal processes draws into focus meaningful, but ambiguous, non-verbal signals such as pauses, ongoing silences, and contextual communication which can be reinterpreted pre-, during, and post-transcription; highlighting the subjective nature of the transcription. In the study described, participants watched a video of their own classroom participation, and used software to rate and subsequently describe their own intentions to participate. As changes in the ratings were a focus of the study and the basis of post-task stimulated recall interviews, during transcription, it was necessary to juxtapose second-by-second changes in this quantitative data against observable phenomenon. Various approaches to transcription and analysis were trialed during the study, and the strengths and weaknesses of these approaches, such as a loss of overall clarity and accessibility, reduced accuracy, increased sensitivity, and the opportunity to revisit observable data after considering research subject’s self-reported intentions, became evident during the transcribing, analysis, and writing up of the project.
