Impact of AI-Supported Teaching on Clinical Decision-Making in Nursing Students

Yeditepe University

Status: Completed

Conditions: Nursing Education Research

Treatments: Other: ChatGPT-Supported Case-Based AI Education (C-CASE); Other: Standard Education

Study type: Interventional

Funder types: Other

Identifiers

NCT06999447

202312Y0718

Details and patient eligibility

About

This clinical trial aims to explore whether an AI-supported teaching method can help nursing students improve their clinical decision-making skills and knowledge during case-based learning. The study focuses on third-year nursing students enrolled in an emergency care course. Participants are divided into two groups: one group receives traditional case-based instruction, while the other uses ChatGPT (an AI language model developed by OpenAI- (Chat Generative Pre-trained Transformer)) to support their case-solving activities. All students complete a pretest and posttest to assess their knowledge and perceptions of clinical decision-making. The main goals are to find out whether the AI-supported group performs better than the traditional group and to evaluate the relationship between students' knowledge and their clinical decision-making scores. By comparing these two teaching methods, researchers aim to understand whether integrating AI tools into nursing education can enhance learning outcomes.

Enrollment: 66 patients

Sex: All

Ages: 18 to 25 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Successful completion of prerequisite courses (Fundamentals of Nursing I-II,
• Medical-Surgical Diseases Nursing, and Pediatric Nursing) along with associated clinical internships
• Enrollment in the Emergency Care course during the study period
• Volunteering to participate and providing written informed consent
• Must be a third-year undergraduate nursing student.
• Must be enrolled in the "Emergency Care Nursing" course during the 2024-2025 spring semester.
• Must be attending the Faculty of Health Sciences, Department of Nursing, at Yeditepe University.
• Completion of all data collection forms

Exclusion criteria

• Failure to complete prerequisite courses or required clinical internships
• Irregular attendance in the Emergency Care course
• Declining to participate or failure to provide written informed consent
• Submission of incomplete data collection forms

Trial design

Primary purpose: Other

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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66 participants in 2 patient groups

C-CASE Group (AI-Supported Case-Based Education)

Experimental group

Description:

In this arm, participants received a behavioral intervention involving AI-supported education during a structured, classroom-based case-solving session. After informed consent and a pretest, students were divided into groups of six. Each group selected a representative with access to ChatGPT-4 Premium via researcher-provided credentials. These representatives interacted directly with the AI while others collaborated in real time to solve a pediatric surgical emergency case. The case included 10 structured questions and one open-ended item, based on the Bowtie model used in NCLEX. Each question was addressed in 5-minute intervals through team-based discussion. The intervention aimed to enhance clinical decision-making and case-specific knowledge. No drug, device, or clinical procedure was used; the AI-supported education was conducted entirely in an academic classroom setting using digital tools.

Treatment:

Other: ChatGPT-Supported Case-Based AI Education (C-CASE)

Standard Education Group (Traditional Case-Based Learning)

Active Comparator group

Description:

Participants in this group engaged in traditional, instructor-led case-solving sessions without access to AI tools. Students were divided into groups of six and analyzed the same pediatric surgical emergency case used in the intervention group. To ensure no use of AI platforms like ChatGPT, a classroom monitoring application was implemented. Instead, students used institutional academic databases and library resources. The activity's structure, including group size, timing, question sequence, and classroom setup, mirrored the AI-supported group's experience to ensure consistency. This arm served as the control condition to compare traditional education with AI-assisted learning in terms of clinical decision-making and knowledge development. No drug, device, or clinical procedure was used; this was a classroom-based educational activity only.

Treatment:

Other: Standard Education