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Completed

NCT Number: NCT06999447

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

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.

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Key information

Conditions

Nursing Education Research

Age range

18 year–25 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Yeditepe University

Istanbul, Atasehir, 34755, Turkey (Türkiye)

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

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

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

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.

Primary outcomes

  1. Clinical decision-making skills

    Time frame: From baseline (before intervention) to immediately after the intervention session (same day)

    This outcome measures clinical decision-making using the Clinical Decision-Making in Nursing Scale (CDMNS), developed by Jenkins (1983) and validated in Turkish by Durmaz (2012). The 40-item scale is rated on a 5-point Likert scale ("always" to "never") and includes four subdimensions: Search for Alternatives or Options (SAO), Canvassing of Objectives and Values (COV), Evaluation and Re-evaluation of Consequences (ERC), and Search for Information and Unbiased Assimilation of New Information (SIUANI). Each subdimension includes 10 items. Total scores range from 40 to 200; higher scores reflect stronger decision-making. Of the 40 items, 22 are positively worded and 18 are negatively worded (reverse-scored). Minimum and maximum scores for subdimensions are not explicitly defined in the original scale; instead, changes in subdimension scores were analyzed based on increase or decrease. The scale was applied at pretest and posttest.

Secondary outcomes

  1. Case-Specific Knowledge Test Score

    Time frame: Immediately after the intervention session (same day)

    This measure evaluates nursing students' knowledge in pediatric surgical emergency management using a researcher-developed, scenario-based test aligned with the NCSBN "Bowtie" model. The test includes 10 structured items (one with two parts) and one open-ended question, totaling 11 questions. Items combine multiple-choice and short-answer formats, requiring students to prioritize, analyze, and justify decisions. Partial credit is awarded for correct responses and justifications; incorrect answers do not deduct points. Scores range from 0 to 100, with higher scores indicating greater case-specific knowledge. No cutoff was defined; mean scores were compared between groups at posttest. This is not a previously validated measurement tool (scale); however, content validation was conducted by five independent nurse educators with expertise in pediatric and surgical nursing. The test was developed by two PhD nurse educators and administered digitally via QR code.

Sponsors and collaborators

Lead sponsor

Yeditepe University

Other

Registry information

Official study title

AI-Supported Teaching in Pediatric Surgical Emergency Case Management: Effects on Nursing Students' Knowledge and Clinical Decision-Making in a Randomized Controlled Study

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
May 31, 2025
Registry last updated
Jun 6, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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