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NCT07872969
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Kolb-Based AI-Powered Neonatal Simulation Training

Sponsor: Maltepe University

View on ClinicalTrials.gov

Summary

This quasi-experimental study aims to evaluate the multidimensional effects of an artificial intelligence-supported newborn simulation training program based on Kolb's Experiential Learning Theory on nursing students' self-efficacy, knowledge, health literacy, satisfaction, and confidence in learning. The study will be conducted with third-year nursing students at Maltepe University during the Fall semester. The design incorporates a single-group, three-time measurement model: pre-test (baseline before training), mid-test (after simulation observation/demonstration), and post-test (after individual application and reflection). The intervention spans a total of 12 weeks. Data will be collected using an introductory information form, the Multidimensional Assessment Scale for Assessment and Care of Newborns, and the Student Satisfaction and Self-Confidence in Learning Scale. Statistical analyses will include descriptive statistics, repeated measures ANOVA or Friedman tests, and correlation analyses.

Official title: Multidimensional Effects of an Artificial Intelligence-Assisted Neonatal Simulation Training Based on Kolb's Experiential Learning Theory on Nursing Students: A Quasi-Experimental Study

Key Details

Gender

All

Age Range

Any - Any

Study Type

INTERVENTIONAL

Enrollment

34

Start Date

2026-11-10

Completion Date

2027-01-30

Last Updated

2026-10-14

Healthy Volunteers

Yes

Interventions

BEHAVIORAL

Kolb-Based Artificial Intelligence-Supported Neonatal Simulation Training

Participants will receive AI-supported neonatal care simulation training based on Kolb's Experiential Learning Cycle (concrete experience-reflective observation-abstract conceptualization-active experience). The training consists of (1) brief theoretical background information, (2) simulation application with neonatal clinical scenarios, (3) structured debriefing/reflection session, and (4) AI-supported feedback and personalized learning recommendations. The AI component provides real-time/post-session feedback, error/deficiency analysis, and individualized study recommendations for the next session based on performance checklist inputs and/or simulation recordings. The intervention lasts a total of 12 weeks, with each session structured according to Kolb's Experiential Learning Cycle. All participants receive the same content and scenarios; there is no control arm. Measurements are taken at time points T0 (pre-test), T1 (mid-test), and T2 (post-test).

Locations (1)

Maltepe University

Istanbul, Maltepe, Turkey (Türkiye)