Leveraging Large Language Models (LLM) to Enhance Research Competency Among Undergraduate Nursing Students: A Novel Approach to Research Education
NCT07540078 · Status: ENROLLING_BY_INVITATION · Phase: NA · Type: INTERVENTIONAL · Enrollment: 640
Last updated 2026-04-20
Summary
The goal of this mixed method interventional study is to develop and test the effectiveness of integrating ChatGPT into the nursing research course to improve research competency among third-year undergraduate nursing students. The main questions it aims to answer is:
Will participants who undergo the LLM-integrated curriculum show an increase in research competency and attitudes compared to participants who did not undergo this curriculum.
Researchers will compare a students assessment grades, as well as their research competency and attitude, measured via the Research Competence Scale (R-Comp) and Revised Attitudes Towards Research scale (R-ATR) respectively. Research will determine whether the LLM-integrated curriculum could improve students understanding and attitudes towards research.
Conditions
- Education
- AI (Artificial Intelligence)
Interventions
- OTHER
-
LLM-Integration
The curriculum for AY2026/2027 will have the following integrated into their lessons/ learning materials: 1. ChatGPT integrated curriculum, 2. tutor manual; 3. student manual; and 4. ChatGPT interactive platform.
Sponsors & Collaborators
-
Ministry of Education, Singapore
collaborator OTHER_GOV -
National University Health System, Singapore
lead OTHER
Study Design
- Allocation
- NON_RANDOMIZED
- Purpose
- OTHER
- Masking
- NONE
- Model
- PARALLEL
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2025-08-13
- Primary Completion
- 2026-11-30
- Completion
- 2026-12-31
Countries
- Singapore
Study Locations
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