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

NCT ID: NCT06999447

Last Updated: 2025-06-06

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 66 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-03-26
• Study Completion Date: 2025-03-26

Brief Summary

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.

Conditions

Nursing Education Research

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

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

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.

Group Type: EXPERIMENTAL

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

Intervention Type: OTHER

In the intervention group (C-CASE), after informed consent and pretest completion (including a sociodemographic form and CDMNS), the case scenario was introduced by the course instructor. Students were divided into small groups, and each group selected a representative who accessed ChatGPT-4.0 Premium via credentials provided by the research team. Using a collaborative problem-solving format, each group worked through a structured case scenario involving pediatric surgical emergencies. Questions were distributed sequentially, with 5-minute intervals allocated per question. Students used ChatGPT to support reasoning and clinical decision-making within their group. After each interval, responses were submitted, and the next question was handed out. Sessions were proctored by research assistants, and the full implementation, including discussion, lasted approximately two hours. The intervention aimed to foster decision-making, teamwork, and AI literacy in a clinical nursing education.

Standard Education Group (Traditional Case-Based Learning)

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.

Group Type: ACTIVE_COMPARATOR

Standard Education

Intervention Type: OTHER

In the control group (Standard Education), students followed the same structured case-based learning session as the intervention group, without access to AI tools. After providing informed consent and completing the pretest (sociodemographic form and CDMNS), the case scenario was introduced by the instructor. Students were divided into small groups and selected a representative to use a personal computer during the session. To ensure no access to AI-based tools, the Mobile Guardian app was installed to block websites such as ChatGPT. Students were allowed to use only academic databases and the university's online library. Each group answered a series of timed case questions (5 minutes per item), submitting responses before receiving the next question. Research assistants monitored the session in both classrooms to ensure standardization and prevent external support. The session concluded with a class-wide case discussion, led by the course instructor.

Interventions

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

In the intervention group (C-CASE), after informed consent and pretest completion (including a sociodemographic form and CDMNS), the case scenario was introduced by the course instructor. Students were divided into small groups, and each group selected a representative who accessed ChatGPT-4.0 Premium via credentials provided by the research team. Using a collaborative problem-solving format, each group worked through a structured case scenario involving pediatric surgical emergencies. Questions were distributed sequentially, with 5-minute intervals allocated per question. Students used ChatGPT to support reasoning and clinical decision-making within their group. After each interval, responses were submitted, and the next question was handed out. Sessions were proctored by research assistants, and the full implementation, including discussion, lasted approximately two hours. The intervention aimed to foster decision-making, teamwork, and AI literacy in a clinical nursing education.

Intervention Type: OTHER

Standard Education

In the control group (Standard Education), students followed the same structured case-based learning session as the intervention group, without access to AI tools. After providing informed consent and completing the pretest (sociodemographic form and CDMNS), the case scenario was introduced by the instructor. Students were divided into small groups and selected a representative to use a personal computer during the session. To ensure no access to AI-based tools, the Mobile Guardian app was installed to block websites such as ChatGPT. Students were allowed to use only academic databases and the university's online library. Each group answered a series of timed case questions (5 minutes per item), submitting responses before receiving the next question. Research assistants monitored the session in both classrooms to ensure standardization and prevent external support. The session concluded with a class-wide case discussion, led by the course instructor.

Intervention Type: OTHER

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 25 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Yeditepe University

OTHER

Sponsor Role: lead

Responsible Party

Gokce Naz Cakir

Graduate Research Assistant

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Yeditepe University

Istanbul, Atasehir, Turkey (Türkiye)

Countries

Turkey (Türkiye)

Other Identifiers

202312Y0718

Identifier Type: -

Identifier Source: org_study_id