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,

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.

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.

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.

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.