“Qualitative data from student journals and interviews were analyzed using reflexive thematic analysis guided by an abductive analytic approach, involving iterative movement between inductive (data-driven) and deductive (theory-informed) coding (Braun & Clarke, 2022; Finlay, 2002). To support this process, I used Evidano, an AI-assisted qualitative analysis tool, to facilitate initial coding and theme generation based on structured analytic prompts. These prompts directed the software to attend to both emergent patterns in participants’ language and sensitizing concepts drawn from the eight dimensions of holistic wellbeing and contemplative education frameworks (Norozi, 2023; Swarbrick, 2006).”

“I used Evidano, an AI-assisted qualitative analysis platform, to support the coding process by organizing large volumes of text data, identifying preliminary patterns, and generating initial thematic structures (Evidano, Inc., 2026). I conducted three separate analyses: one for student journals, one for interview transcripts, and one combining both data sources with overarching themes. I uploaded each dataset into the platform and analyzed them independently to preserve the context of each source.”

“Through our thought partnership with Evidano, we identified comparative distinctions in how the SET converged or differed, based on perceptions of the instructional roles played by instructors, particularly in relation to gender.”

“These AI-assisted affordances helped ensure the robustness and quality of our analysis, not as substitutes, but as a complement to our human intelligence analyses.”

“Rather than relying on keyword matching, Evidano identifies conceptual patterns based on contextual meaning, clustering related passages even when they do not share identical vocabulary.”

“This design ensured that AI augmented rather than replaced expert qualitative judgment, limiting automation bias while preserving analytical rigor.”

“Next, we analyzed our qualitative data using the online AI-powered qualitative analysis software Evidano to triangulate the findings from our thematic analysis and to “help identify oversights, alternative frames, and personal biases” (Hamilton et al., 2023, p. 13). Evidano was selected because recent qualitative studies (Farrand & Jung, 2025; Gamlem et al., 2025; Knippen et al., 2025; Lirasan et al., 2025; Rillero et al., 2025) have demonstrated its ability to support accurate, low-bias qualitative analysis, particularly when used with human oversight. Accordingly, all coding and thematic interpretations were reviewed and validated by the research team. Other strengths of Evidano are that it only trains its models on permissible data only, its methods are grounded in seminal scholarship, user data are confidential and never used to train models, and the software “uses an inductive approach to theme identification by analyzing the entire dataset, which helps avoid the limitations of traditional coding methods that focus on single responses and may overlook broader themes or complex discussions.””

“The first four themes from the human-coded analysis: (1) ‘Accreditation from CALEA Signals Going Above and Beyond,’ (2) ‘Rigor versus Lacking Rigor,’ (3) ‘CALEA Signals Prestige,’ and (4) ‘Accreditation from CALEA Signals Longer and Broader Leadership Experience’ were supported by the AI-assisted analysis with only minor differences in wording. Theme five, ‘No Difference or Little Difference Between the Two,’ was not featured as a theme in the AI-assisted analysis, but was used to highlight countervailing perspectives within the themes related to ‘Rigor versus Lacking Rigor’ and ‘CALEA Signals Prestige.’ The AI-assisted analysis included a theme that was not highlighted in the human-coded analysis, ‘Community Perception and Trust.’ Central to this theme was the perception that accreditation provides a superior, objective, third-party seal of approval that facilitates trust.”

“The AI qualitative research tool Evidano has been used in other qualitative studies to identify themes from interview transcripts… supporting the qualitative data analysis process. Evidano was used to identify themes by research questions in the initial stage and to review alignment with the first authors themes and sub-themes. All AI-generated content was reviewed, revised, and validated by the first author to ensure accuracy, relevance, consistency, and alignment with the research objectives. The transcripts were compared with the AI-generated thematic coding and the first author’s coding to identify alignment with major themes, as well as sub-themes throughout the coding process to inform the different phases of the thematic analysis… AI technology was used as a thought partner to confirm and refine codes identified by the first author.”

“The methodological rigour of our study is a key strength of our research design. We established the trustworthiness of the data analyses through researcher reflexivity, agreement between co-researchers, triangulation between different participants and multiple data sources, thick descriptions of the data, and the provision of quotes from the participants’ and the editors’ stories. We also trialled the use of the new AI thematic analysis software Evidano to see a different perspective on the key ideas mentioned in the editors’ reflections. Our AI analysis further helped to demonstrate the trustworthiness of our coding strategy, as it highlighted key ideas similar to those of the themes we had constructed.”

“…remarkable, especially given its price point.”

“Evidano did a very good job in identifying key themes in the data and also in summarizing these key themes in prose for a human to review, verify, and adapt.”

“We identified one for which we could find no reports of the problems commonly associated with AI, such as bias and hallucinations.”

“…it seems artificial and human intelligence would agree on the determination Evidano reached…”