Parallel Surveys of GenAI and Writing
Students’ Perspectives and Instructors’ Perception of Student Perspectives in Writing-Intensive Courses
Bibliographic Data
| ID | 21560496 |
|---|---|
| Authors | Hooman Saeli (0000-0003-2904-2119, University of Tennessee, Knoxville, USA), Jeff Ringer (0009-0008-7801-7298, University of Tennessee, Knoxville, USA, corresponding author), Chris Mayer (0000-0001-5746-0356, University of Tennessee, Knoxville, USA), Matt Bryant Cheney (0000-0001-8237-6295, University of Tennessee, Knoxville, USA), Grace Duncan (University of Tennessee, Knoxville, USA) |
| Year | 2026 |
| Volume | 43 |
| Issue | 1 |
| Pages | 196-224 |
| Publication date | 2026-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Written Communication (JOURNAL) |
| Journal identifiers | ISSN: 0741-0883 • E-ISSN: 1552-8472 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/07410883251372207 |
| OpenAlex | W7107877930 |
| Language | EN |
| References cited | 39 |
Our questionnaire-based study explored the perceptions and reported practices of students about using GenAI in writing-intensive (WI) courses and instructors’ perceptions of those student-held perceptions and reported practices. The data were collected from a large state university in the Southeastern United States. We administered two parallel versions of a questionnaire to 6,000 student emails and 390 instructor emails across two semesters. Using SPSS 29, we analyzed the data to calculate descriptive statistics, multivariate analyses of variance, post hoc analyses, and factor analyses. Our analysis revealed numerous significant differences between the students and instructors in how students use GenAI as a writing assistance tool and as a source of feedback, among others. Our results provide important insights into the divergent perspectives students and instructors hold about the role of GenAI in writing-intensive classes and recommend increased communication between instructors and students to achieve common understanding about GenAI’s applicability to writing processes
Computer-mediated communication · Descriptive statistics · Higher education · Multimethodology · Multivariate analysis · Perception · Post hoc · Qualitative research · Semi-structured interview · Discourse Analysis in Language Studies · Literacy, Media, and Education · Writing and Handwriting Education
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| Highly cited | No |
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