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Research Spotlights

How researchers at leading universities and institutes used Evidano in their published work — in their own words.

Cornell University · Malcolm Knowles Award 2023
Annalisa Raymer, Senior Lecturer at Cornell University and Director of CLASP

Annalisa Raymer

Senior Lecturer & Director of CLASP
Cornell University

Dr. Raymer uploaded the transcript of an in-house CLASP film into Evidano to summarize four stakeholder groups’ perspectives and run a thematic analysis, then compared the AI’s reading with feedback from adult-education colleagues at the AAACE conference.

With Evidano, I feel that I have a straightforward thinking partner, rather than an internet pet eager to please.

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Distinguished Professor
Cheng-Ta Wu, Distinguished Professor in the College of Education at National Chengchi University

Cheng-Ta Wu

Distinguished Professor, College of Education
National Chengchi University, Taiwan

His team’s published article is itself a case study of Evidano: the authors demonstrate its full qualitative workflow — summaries, themes, codebook, frequency analysis, and key quotes — on elementary-school leadership interview data. They propose a human–AI collaborative model for qualitative research.

A powerful assistant that not only enhances the efficiency of qualitative data processing but also empowers researchers to concentrate on higher-level interpretation, theory construction, and nuanced analysis.

From the published article
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Published in Educational Psychology
Siv M. Gamlem, Professor at Volda University College

Siv M. Gamlem

Professor of Education
Volda University College, Norway

After two researchers completed the initial inductive thematic analysis of 11 interviews, Professor Gamlem’s team ran the anonymised transcripts through Evidano and compared the results with their manual analysis for triangulation and validation.

Evidano supported our research process by offering an additional lens on the interview data, helping us identify patterns that could be compared with our initial manual analysis. Its value was not in replacing interpretation, but in strengthening the transparency and robustness of our analytic decisions.

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Published in Education Sciences
Shawn S. Savage, Assistant Professor in the Watson College of Education at UNC Wilmington

Shawn S. Savage

Assistant Professor
University of North Carolina Wilmington

After multiple rounds of human coding of narrative student evaluations, Dr. Savage and Dr. Parker used Evidano to interrogate the data from a different analytic vantage point, surfacing gendered comparative distinctions they then verified through collaborative analysis.

Evidano was most helpful because it encouraged Dr. Parker and me to revisit the data from a different analytic vantage point. It didn’t replace our interpretation; it expanded the kinds of questions we asked.

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Published in Frontiers in Education
Lawrence Meda, Director of Research and Associate Professor at Sharjah Education Academy

Lawrence Meda

Director of Research & Associate Professor
Sharjah Education Academy, UAE

After translating, transcribing, and manually coding nine teacher interviews, Professor Meda’s team used Evidano to categorize participant quotes into researcher-defined themes — with every allocation manually verified by the research team.

AI-supported tools like Evidano can enhance qualitative research when used carefully and transparently.

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Published in Cambridge Prisms: Plastics
Adriana Cunha Neves, researcher at South East Technological University, Carlow

Adriana Cunha Neves

Researcher, Department of Applied Science
South East Technological University, Ireland

Her team used Evidano for AI-assisted thematic analysis of focus group discussions about starch-protein bioplastics, helping mitigate unintentional researcher bias during interpretation.

Evidano is particularly valuable for researchers who lack extensive experience in qualitative data analysis, offering an efficient way to organize large datasets while minimizing the influence of pre-existing knowledge and researcher bias.

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Published at IEEE ACDSA 2026
Munn Hong Lam, researcher at Universiti Tunku Abdul Rahman

Munn Hong Lam

Researcher, Faculty of Accountancy and Management
Universiti Tunku Abdul Rahman, Malaysia

In a sequential mixed-methods pilot on AI literacy and employment prospects, his team entered the qualitative interview data into Evidano and interpreted it thematically to add depth to their survey results.

The qualitative element of our research was supported by Evidano through assistance with thematic organisation and interpretation of interview data. This was helpful in our research workflow, particularly in identifying patterns within the responses received during the interviews.

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