This study details and reflects on the modifications made to the Framework Method for qualitative data analysis (QDA) of large-scale triadic interviews with education stakeholders. The QDA is part of the early assessment and impact evaluation of a curriculum revision that employed a mixed-methods design, including a teacher survey, key informant interviews, and focus group discussions. Participants were selected from schools sampled for the assessment using a cluster randomized design, which assigned schools to either the treatment or control curriculum. Given the volume of interview data and the diversity of the team, high intercoder and intracoder reliability (ICR) was aimed for when creating and applying the analytical framework, or coding tree, during data condensation and analysis. Clearly defining codes with inclusion and exclusion boundaries, segmenting the transcripts, and memoing were key processes that enhanced ICR. Evaluating the application and performance of the codes using Fleiss Kappa improved the communicability, consistency, and transparency of the working analytical framework. Memoing also helped trace points of interpretive divergence among the coding team. After coding, the segmented data was indexed in a framework matrix, utilizing relatively accessible or free tools to organize, display, and interpret the data. Through these procedures, the aim was to meet the consolidated standards for reporting qualitative data (COREQ).
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