Oral Assessment in the AI Era—Equity, Validity, and Scale
Bibliographic Data
| ID | 9734734 |
|---|---|
| Authors | Hengzhi Hu (0000-0001-5232-913X, Universiti Kebangsaan Malaysia, Bangi, Selangor, corresponding author), Harwati Hashim (0000-0002-8817-427X, Universiti Kebangsaan Malaysia, Bangi, Selangor) |
| Year | 2026 |
| Publication date | 2026-03-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Educational Researcher (JOURNAL) |
| Journal identifiers | ISSN: 0013-189X • E-ISSN: 1935-102X |
| Publisher | American Educational Research Association (AERA) (PUBLISHER) |
| DOI | 10.3102/0013189x261426370 |
| OpenAlex | W7139046371 |
| Language | EN |
| References cited | 1 |
Fenton’s article, “Reconsidering the Use of Oral Exams and Assessments: An Old Way to Move Into a New Future,” argues that oral assessment can restore authenticity and support academic integrity in the generative artificial intelligence era. Drawing on this synthesis, this letter offers three refinements to enable adoption at scale: operationalize equity by separating language production from disciplinary reasoning and providing targeted accommodations; bolster validity and reliability by constraining examiner behavior through standardization, recording, and interrater checks; and enhance feasibility via a scalable “viva-lite” oral verification appended to selected tasks
Discipline · Generative grammar · Inter-rater reliability · Interpretability · Operationalization · Reliability (semiconductor · Scale (ratio · Test validity · Academic integrity and plagiarism · Psychometric Methodologies and Testing · Student Assessment and Feedback
| Citation velocity | historical |
|---|---|
| Highly cited | No |