Evalution of the Effectiveness of a Shoulder Dystocia Training Program Designed With Inverted Learning Supported by Generative Artificial Intelligence

April 13, 2026 updated by: Melek Isik, Fenerbahce University
With the ongoing digital transformation in health education, the importance of learner-centered and technology-integrated approaches has been increasing. Particularly in teaching complex and unpredictable clinical situations in healthcare, the limited effectiveness of traditional methods has led to a growing need for innovative approaches such as flipped learning and self-directed learning. Generative artificial intelligence (GAI)-supported educational applications have the potential to enhance academic achievement by making the learning process more interactive. However, research evaluating the effectiveness of these technologies in education remains limited. In this context, GAI-supported flipped learning enables students to gain individualized learning experiences through simulated classroom or clinical environments and to be better prepared for clinical encounters and specific clinical skill training. One of the critical clinical topics that should be addressed within this framework is shoulder dystocia. Shoulder dystocia is an obstetric emergency, most cases of which are unpredictable and unavoidable. Accordingly, this study aims to evaluate the effects of a GAI-supported flipped learning approach applied to shoulder dystocia training on midwifery students' knowledge levels and self-directed learning skills through effective use of technology.

Study Overview

Status

Not yet recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

114

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

  • Name: Melek Kılıç, PhD Candidate
  • Phone Number: +905447324244
  • Email: mlekisik@gmail.com

Study Locations

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

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Probability Sample

Study Population

A total of 114 third-year students who meet the inclusion criteria will be administered the "Student Information Form" and the "Shoulder Dystocia Management Knowledge Test." To determine baseline levels, participants will be stratified into three layers based on their shoulder dystocia management knowledge test scores and then assigned to G1, G2, and G3 groups using simple randomization in a 1:1:1 ratio. The randomization list will be generated by an individual independent of the researcher in order to reduce selection bias, using the randomizer.org website. Random group assignments will be performed on a stratified basis (stratification criteria: institutions and shoulder dystocia management knowledge test scores). Using this method, 114 third-year students will be randomized equally into three groups, with 38 students assigned to G1, 38 to G2, and 38 to G3.

Description

Inclusion Criteria:

  • -Being a 3rd year student in the Midwifery Department of Fenerbahçe University and Istanbul-Cerrahpaşa Faculty of Health Sciences.
  • Having sufficient or unlimited internet access.

Exclusion Criteria:

  • Having previously taken a course on shoulder dystocia
  • Student's absence from class/sick leave

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

Cohorts and Interventions

Group / Cohort
Generative AI-supported flipped learning
Midwifery students receiving shoulder dystocia training through a generative AI-supported flipped learning approach with interactive and scenario-based activities.
Standard flipped learning
Midwifery students receiving shoulder dystocia training through a standard flipped learning approach without AI support.
Traditional learning
Midwifery students receiving shoulder dystocia training through traditional lecture-based teaching methods.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Knowledge level on shoulder dystocia management
Time Frame: Before the intervention and immediately after the intervention
The knowledge level of midwifery students regarding shoulder dystocia management will be assessed using a structured knowledge test developed by the researcher.
Before the intervention and immediately after the intervention

Collaborators and Investigators

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

Sponsor

Fenerbahce University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

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)

April 1, 2026

Primary Completion (Estimated)

June 1, 2026

Study Completion (Estimated)

June 1, 2027

Study Registration Dates

First Submitted

March 31, 2026

First Submitted That Met QC Criteria

March 31, 2026

First Posted (Actual)

April 7, 2026

Study Record Updates

Last Update Posted (Actual)

April 16, 2026

Last Update Submitted That Met QC Criteria

April 13, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2025/756

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Individual participant data (IPD) underlying the results reported in this study will be available upon reasonable request from the corresponding author, following publication. Data will be de-identified to protect participant confidentiality. Access to data will be granted to researchers who provide a methodologically sound proposal, subject to approval by the research team.

IPD Sharing Time Frame

De-identified individual participant data (IPD) and supporting documents (study protocol, statistical analysis plan, and informed consent form) will be available beginning 6 months after publication of the study results and will remain available for a period of 5 years. Data access will be provided upon reasonable request to the corresponding author, subject to approval by the research team.

IPD Sharing Access Criteria

Access to de-identified individual participant data (IPD) and supporting documents (study protocol, statistical analysis plan, and informed consent form) will be granted to qualified researchers who provide a methodologically sound research proposal. Requests should be directed to the corresponding author. Data will be shared after approval by the research team and, where applicable, the institutional ethics committee. Data will be provided in a secure format, and users will be required to agree to terms that ensure confidentiality and appropriate use of the data.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ICF

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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