At the end of a semester, a few lines in a course evaluation can travel far beyond the classroom. Those comments may shape how teaching is remembered, how faculty cases are discussed, and how institutions understand quality.
About Shawn S. Savage

In the lineage of his mother, Cynthia Griffiths Allen’s love, wisdom, and commitments to justice, Dr. Shawn S. Savage serves as Assistant Professor and Program Coordinator for the Curriculum and Instruction doctoral concentration in the Department of Educational Leadership at the University of North Carolina Wilmington. With over a decade of experience in K-12 and higher education, Dr. Savage is an interdisciplinary scholar investigating access and justice across K-12, teacher, and higher education. His research centers the experiences of Black youth and men, using justice-focused qualitative methodologies to showcase the brilliance, beauty, depth, and range of Black people and culture transnationally.
About the authors
- Michele A. Parker (Department of Educational Leadership, Watson College of Education, University of North Carolina Wilmington, USA)
- Shawn S. Savage (Department of Educational Leadership, Watson College of Education, University of North Carolina Wilmington, USA)
Read the article
Read the full research article, “A Troubleshoot Test of Student Evaluations of Teaching: Role Congruity, Gendered Language, and Educational (In)Equalities,” published in Education Sciences in 2026.
View the publicationWe are grateful to Parker and Savage for their contribution to research on student evaluations of teaching, gendered language, and educational equalities, and for referencing Evidano as part of their research process.
Related published research
Other published studies and evaluations that used Evidano on comparable material.
- Published research2024

UNICEF tested AI-assisted qualitative coding against manual coding on 160 evaluations
Same 160 management responses, AI and manual coding side by side. See where Evidano matched human analysts, where humans stayed essential, and what each approach cost.
160 management responses
UNICEF Office of Emergency Programmes review report, New York, November 2024
- Published research2026

UT Austin and Wichita State used AI thematic analysis to triangulate 224 survey responses
A peer-reviewed criminology study analysed its open-ended responses by hand, then used Evidano to triangulate the findings: 8 of 9 human themes were confirmed.
303 respondents in the conjoint survey
Journal of Experimental Criminology (Springer Nature), 2026, open access
- Published research2024

Monash University study trialled AI thematic analysis to cross-check its themes
See how doctoral education researchers trialled Evidano for thematic analysis, with human researchers leading every interpretation.
23 doctoral writers’ responses analysed, from 29 recruited
Studies in Educational Evaluation, vol. 83, 101379 (Elsevier, 2024), open access
Explore more evidence
The full case-study library, the wording researchers published when citing Evidano, and how its output compares with manual coding.
- Resource
Case studies in published research
Peer-reviewed studies, UN evaluations and university research where teams used Evidano for AI-assisted qualitative analysis — with the methods, the numbers and the published source for each.
- Resource
How Evidano was used, in published methods sections
Verbatim excerpts from 20 published studies describing what Evidano did in their analysis — as a thought partner, a second coder, for initial coding, or for synthesis.
- Resource
Methodology guides and research writing
Practical guides to qualitative methods — thematic analysis, grounded theory, evidence synthesis and more — alongside the wider Evidano article library.
- Resource
Human vs AI: validated accuracy benchmarks
Four head-to-head comparisons against expert human analysis — 371 interview transcripts with Arizona State and Penn State, 298 evaluation reports, 224 open-ended survey responses with UT Austin and Wichita State, and a 160-response manual-coding review.
