Impact of AI-Based Research Training on Nursing Students

February 11, 2026 updated by: Sogand Sarmadi, Shahid Beheshti University of Medical Sciences

The Impact of Artificial Intelligence-Powered Research Training Course on Nursing Students' Research Literacy, Attitude, and Readiness to Use Artificial Intelligence

The goal of this clinical trial is to find out whether an artificial intelligence (AI)-powered research training course can improve nursing students' research skills, attitudes toward artificial intelligence, and readiness to use AI in research and education.

The main questions this study aims to answer are:

Does AI-powered research training improve nursing students' understanding of research methods?

Does this training improve nursing students' attitudes toward artificial intelligence?

Does the course increase nursing students' readiness and confidence to use artificial intelligence in research-related activities?

Researchers will compare nursing students who take an AI-powered research training course with students who receive usual education without AI-based training.

Participants will:

Be randomly assigned to either the AI-powered research training group or the usual education group

Complete online questionnaires about research skills, attitudes toward artificial intelligence, and readiness to use AI

Attend assessments at three time points: before the course, immediately after the course, and three months later

The AI-powered research training course includes structured sessions on research methods and the responsible use of artificial intelligence tools for literature review, research design, data analysis support, and academic writing. The results of this study may help improve research education and support the safe and effective use of artificial intelligence in nursing education and research.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

104

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  1. Enrolled in a nursing program (bachelor's, master's, or doctoral level) at one of the participating universities during the study term.
  2. Completion of at least one course in research methodology in their program curriculum.
  3. Willingness to participate and to provide written informed consent.

Exclusion Criteria:

  1. Prior completion of advanced courses specifically on research-oriented AI or formal AI certification programs.
  2. Inability to attend the scheduled intervention sessions or to access the online learning platform.
  3. Not complete the study questionnaires at all required time points
  4. Withdrawal of consent or failure to complete baseline assessments.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-Powered Research Training Course

Participants in the intervention group will take part in an artificial intelligence (AI)-powered research training course. The course includes eight structured sessions delivered over approximately four weeks and combines core research methods with practical use of AI tools to support research activities.

The training covers key stages of the research process, including selecting a research topic, reviewing scientific literature, developing research questions, choosing study designs, understanding research ethics, managing references, and preparing research reports. Participants will learn how AI tools can support tasks such as literature searching, organizing information, drafting research text, and critically reviewing research outputs, while emphasizing responsible and ethical use of AI.

Sessions include short lectures, hands-on exercises, and practical workshops using commonly available AI-based research tools. Course materials are delivered through an online learning platform,
Other: AI-Powered Research Training Course

The intervention is an artificial intelligence (AI)-powered research training course designed to integrate core research methodology with the practical and responsible use of AI tools. The course consists of eight structured sessions delivered over approximately four weeks and targets nursing students with prior exposure to basic research methods.

Unlike traditional research courses, this intervention embeds AI as a supportive research tool across all stages of the research process rather than as a standalone technical subject. Participants learn how AI can assist with selecting research topics, searching and organizing scientific literature, developing research questions, supporting study design decisions, managing references, and drafting research reports, while maintaining critical judgment and methodological rigor.

The training emphasizes ethical and responsible use of AI, including issues related to data privacy, transparency, plagiarism prevention, and algorithmic bias.
No Intervention: Standard education

Participants in the control group will continue with their usual academic education and will not receive any artificial intelligence (AI)-based research training during the study period. They will complete the same outcome assessments as the intervention group at baseline, immediately after the intervention period, and three months later.

After completion of the final follow-up assessment, participants in the control group will be given full access to the AI-powered research training course materials and recorded sessions to ensure ethical fairness and equal access to educational resources.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Readiness to use artificial intelligence: Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS)
Time Frame: baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).
Readiness to use AI will be conceptualized as technical expertise, positive attitudes, and self-confidence in adopting AI tools for research and clinical tasks (29). It will be assessed using the Persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS), a validated 20-item, 4-domain tool (Cognition, Ability, Vision, Ethics) with 5-point Likert items (total score 20-100). Higher scores will indicate greater readiness. The instrument will have demonstrated acceptable reliability (Cronbach's α ≥ 0.80) and structural validity in prior Iranian studies (24,25). Domain and total scores will be calculated for all participants.
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Research literacy: a researcher-developed Research Literacy Questionnaire
Time Frame: baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).
Research literacy will be defined as the knowledge and skills in research methodology, study design, data collection, and analysis that will enable researchers to conduct valid studies (5). It will be measured using a researcher-developed 20-item true/false/don't-know questionnaire adapted from Brody et al. (27). Responses will be scored as correct if they match the statement's truth, with a total score of 0-20; higher scores will indicate greater research literacy. The questionnaire will be developed based on the literature, will undergo face and content validation by experts (CVI/CVR), and will be pilot-tested with 50-100 participants to assess item properties, internal consistency (Cronbach's alpha), and 10-14-day test-retest reliability. All participants will complete the questionnaire at each time point, and all data will be included in the intention-to-treat analysis.
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).
Attitude toward artificial intelligence: AI Attitude Scale (AIAS-4)
Time Frame: baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).
Attitudes toward artificial intelligence (AI) will be characterized by an individual's beliefs and affective dispositions regarding the applications and implications of AI (26). The evaluation of this attitude will employ the AI Attitude Scale (AIAS-4), a unidimensional instrument consisting of four items, each rated on a scale from 1 to 10, thereby resulting in a total score that ranges from 4 to 40; higher scores indicate more favorable attitudes toward AI. In the absence of a Persian version of the psychometric AIAS-4, the scale will be translated and culturally adapted through a standard forward-backward translation process, supplemented by cognitive interviews with 10 nursing students, and reviewed by an expert panel. Content validity will be assessed through the Content Validity Index (CVI) and the Content Validity Ratio (CVR). The translated instrument will be pilot-tested with 20 participants, and internal consistency will be evaluated using Cronbach's alpha.
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shahid Beheshti University of Medical Sciences

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

March 1, 2026

Primary Completion (Estimated)

May 1, 2026

Study Completion (Estimated)

July 1, 2026

Study Registration Dates

First Submitted

February 6, 2026

First Submitted That Met QC Criteria

February 11, 2026

First Posted (Actual)

February 13, 2026

Study Record Updates

Last Update Posted (Actual)

February 13, 2026

Last Update Submitted That Met QC Criteria

February 11, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • IR.TUMS.FNM.REC.1404.257

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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