What the study examined
A study of doctoral writing groups and collaborative peer feedback, set within a constructivist design. The qualitative data came from open-ended survey responses from PhD students at a research-intensive Australian university, interwoven with the two editors’ reflections. The analysis used Braun and Clarke’s reflexive thematic analysis, and the study was approved by the Monash University Human Research Ethics Committee.
Where Evidano fit in
The authors trialled Evidano to view the key ideas in the editors’ reflections from a different perspective. Researchers constructed the themes themselves; the AI analysis served as a complementary check that supported the study’s trustworthiness, alongside reflexivity, co-researcher agreement, triangulation, and thick description.
How Evidano fit the workflow
- 1Editors’ written reflections
Qualitative text gathered through reflective prompts.
- 2AI thematic analysis with Evidano
Surfaced key ideas from a different perspective.
- 3Compared with researcher-constructed themes
Human coding and interpretation stayed central.
- 4Strengthened trustworthiness
The AI highlighted ideas similar to the constructed themes.
“We also trialled the use of the new AI thematic analysis software Ailyze (https://www.ailyze.com/) 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.”
AI use was named and disclosed in the data analysis section, with a link to the tool.
The AI highlighted key ideas similar to the themes the researchers had constructed.
Humans led coding and interpretation. Evidano supported the work, it did not replace judgment.
Evidano sat alongside reflexivity, triangulation, and co-researcher agreement.