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All discussion codes were developed using an iterative process, building upon our experience coding advanced student discussions (Knight et al., 2013) and using a system based on Toulmin's characteristics of argumentation (Toulmin, 1958).
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KW and JC discussed the stereotypes that emerged from the data and, through discussion, coded them for how they related to different aspects of teaching and learning in the clinical environment.
The Green Chain Reaction was "Open Notebook Science" in that all discussions, code and results were publically viewable on the web at all stages.
No limit was set on the number of BOT discussions coded per video.
After considering other whole-discussion coding schemes (e.g., Osborne et al., 2004), we developed a scoring system to measure the quality of student reasoning (Exchange of Quality Reasoning; Table 3) based on exchanges of warrants (Toulmin, 1958).
Through an iterative process of coding and team discussion, superfluous codes were eliminated and overpopulated single themes were disaggregated as part of a second stage of coding.
Through discussion, the codes were reorganized, collapsed, and expanded in a reiterative process until a coding scheme for the set of interviews was developed.
After comparison and discussion of codes and understanding of the transcripts, there was a high degree of agreement on the major themes and sub themes.
A coding strategy was developed and modified through five rounds of coding, discussion, modification of the coding strategy and re-coding.
Pre-coding was undertaken separately by three of the authors and discussion of coding and further refining was undertaken.
Discussion on coding of a smaller initial set fostered a common approach prior to coding all reports.
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