Leveraging Large Language Models (LLM) to Enhance Research Competency Among Undergraduate Nursing Students: A Novel Approach to Research Education
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: LLM-Integration.
- Who it may be relevant to
- Registry conditions: Education, AI (Artificial Intelligence). Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Singapore
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
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.
Primary outcome measures
- Research Competence questionnaire [Time frame: Once at baseline (week 0), once at Week 10]
- Revised Attitudes Toward Research scale [Time frame: Once at baseline (week 0), once at Week 10]
- Grades of research proposal [Time frame: Week 15]
Eligibility criteria
Inclusion criteria
- All year-three students in cohort years AY2025/26 and AY2026/27 who are enrolled in mandatory research course titled "NUR3202C: Research and Evidence-Based Healthcare"
Exclusion criteria
- NIL
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Non-randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Other
Study locations
Singapore · 1 center
- National University of Singapore, Yong Loo Lin School of Medicine, Singapore, Singapore 11 — Singapore
Identifiers
NCT: NCT07540078 · NUS-IRB-2025-136