Leveraging Large Language Models (LLM) to Enhance Research Competency Among Undergraduate Nursing Students: A Novel Approach to Research Education

N/AEnrolling By InvitationNCT07540078

National University Health System, Singapore640 enrolled

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.

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

OTHER

Masking

NONE

Enrollment

640

Conditions

Education AI (Artificial Intelligence)

Interventions

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.

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

Locations (1)

National University of Singapore, Yong Loo Lin School of Medicine, Singapore, Singapore 117599

Singapore, Singapore

Outcomes

Primary Outcomes

Research Competence questionnaire

A 32-item, 5-point Likert scale assessing participants perceived research competency. The minimum and maximum score one can attain on this measure is 32 and 160 respectively, with a higher score indicating higher perceived competence in research

Time frame: Once at baseline (week 0), once at Week 10

Revised Attitudes Toward Research scale

A 13-item, 7-point Likert scale assessing participants' own attitudes towards research. The minimum and maximum score one can attain on this measure is 13 and 91 respectively, with a higher score indicating a more positive attitude towards research.

Time frame: Once at baseline (week 0), once at Week 10

Grades of research proposal

Grades from the research proposal will also be used as an objective measure of the student's research competency for triangulation of data. This research proposal is an existing assessment in NUR3202C it will be assessed using a structured rubric that grades students based on the content, organization, delivery and collaboration.

Time frame: Week 15

Data from ClinicalTrials.gov

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