Transforming curriculum mapping
A human–AI hybrid approach
Bibliographic Data
| ID | 21518026 |
|---|---|
| Authors | Olivia Ng (0000-0001-7573-3725, corresponding author), Zheng Huan Tay (Nanyang Technological University), Lucy V E Wilding (0000-0002-9642-7521, Nanyang Technological University), Kian Bee Ng (0000-0001-7697-0909), Siew Ping Han (0000-0003-4429-9190) |
| Year | 2024 |
| Volume | 58 |
| Issue | 5 |
| Pages | 582-583 |
| Publication date | 2024-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Medical Education (JOURNAL) |
| Journal identifiers | ISSN: 0308-0110 • E-ISSN: 1365-2923 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/medu.15331 |
| PMID | 38409961 |
| OpenAlex | W4392194579 |
| Language | EN |
| Citations received | 3 |
| References cited | 1 |
Generative artificial intelligence (Gen-AI) has the potential to revolutionise medical education, for example by automating complex processes to improve productivity.A particularly time-consuming and resource-intensive task that could benefit from such automation is curriculum mapping, which requires alignment between often extensive lists of learning outcomes (LOs) and other curricular components.However, concerns remain about the accuracy and reliability of Gen-AI
Biology · Curriculum · Medical education · MEDLINE · Pedagogy · Computer Science · Medicine · Online Learning and Analytics · Psychology
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |