Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Algorithms | 1 |
| Anatomy | 1 |
| Artificial Intelligence | 1 |
| College Science | 1 |
| Models | 1 |
| Multiple Choice Tests | 1 |
| Natural Language Processing | 1 |
| Physiology | 1 |
| Science Tests | 1 |
| Test Construction | 1 |
| Test Items | 1 |
| More ▼ | |
Source
| Grantee Submission | 1 |
Author
| Andrew M. Olney | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Andrew M. Olney – Grantee Submission, 2023
Multiple choice questions are traditionally expensive to produce. Recent advances in large language models (LLMs) have led to fine-tuned LLMs that generate questions competitive with human-authored questions. However, the relative capabilities of ChatGPT-family models have not yet been established for this task. We present a carefully-controlled…
Descriptors: Test Construction, Multiple Choice Tests, Test Items, Algorithms

Peer reviewed
