AI-SUPPORTED FLIPPED LEARNING IN NURSING EDUCATION

NCT07705152 · Status: ENROLLING_BY_INVITATION · Phase: NA · Type: INTERVENTIONAL · Enrollment: 52

Last updated 2026-07-15

No results posted yet for this study

Summary

The increasing complexity of healthcare services and the diversification of patient needs require nurses to be equipped not only with clinical knowledge and technical skills, but also with effective communication, critical thinking, and self-directed learning competencies. Nurses continuously interact with multidisciplinary teams throughout the processes of planning, implementing, and evaluating patient care. Therefore, communication skills are among the fundamental determinants of patient safety and quality of care. However, traditional educational methods are largely based on passive learning and may be insufficient in developing students' professional communication and self-directed learning skills. This limitation can reduce students' learning motivation and negatively affect their ability to make independent decisions and communicate effectively in clinical practice.

Digital technologies and artificial intelligence (AI)-supported applications provide opportunities to strengthen student-centered approaches in education. AI-supported systems offer personalized feedback, enabling targeted support according to students' individual learning needs. The flipped learning approach, on the other hand, is based on acquiring theoretical knowledge before class, while class time is devoted to practice, discussion, and problem-solving activities. This approach enhances students' active participation and supports the development of critical thinking and communication skills.

AI-supported flipped learning combines technological opportunities with pedagogical strategies to create a more interactive and personalized learning experience. This method encourages students to take responsibility for their own learning and strengthens their self-directed learning skills. Nevertheless, studies examining the effects of this approach on learning motivation and self-directed learning in nursing education remain limited. Therefore, this study aims to evaluate the effects of professional communication skills training based on an AI-supported flipped learning approach on nursing students' learning motivation and self-directed learning levels.

Conditions

  • Self-Directed Learning
  • Professional Communication Skills
  • Nursing Education

Interventions

OTHER

Artificial Intelligence-Supported Flipped Learning Approach

This intervention is distinguished from other educational approaches by integrating artificial intelligence (AI)-supported tools with the flipped learning model to provide a personalized, interactive, and student-centered learning experience. Unlike traditional nursing education methods, this approach enables students to access learning materials before class, analyze clinical scenarios, and receive AI-generated feedback according to their individual learning needs. The intervention combines pre-class preparation, in-class case-based discussions, role-playing, and simulation activities to enhance professional communication skills. AI-assisted activities and feedback mechanisms support students' self-directed learning processes by encouraging reflection, continuous assessment, and individualized improvement. The training specifically focuses on professional communication scenarios frequently encountered in nursing practice, including interactions with patients experiencing anxiety, ange

Sponsors & Collaborators

  • Selcuk University

    lead OTHER

Study Design

Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Months
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-15
Primary Completion
2026-08-15
Completion
2026-09-15

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07705152 on ClinicalTrials.gov