Nursing Education Research
Conditions
Keywords
Clinical decision-making, Artificial intelligence, Case-based learning, Surgical nursing, Pediatric nursing
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.
Interventions
OTHERChatGPT-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.
OTHERStandard 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.
Sponsors
Yeditepe University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
This study used a parallel assignment model in which participants were randomly assigned to either an experimental group receiving AI-supported case-based education (C-CASE) using ChatGPT-4 or a control group receiving standard case-based instruction. Each participant remained in their assigned group throughout the study, and both groups completed pretest and posttest evaluations.
Eligibility
Sex/Gender
ALL
Age
18 Years to 25 Years
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Clinical decision-making skills | 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
| Measure | Time frame | Description |
|---|---|---|
| Case-Specific Knowledge Test Score | 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. |
Countries
Turkey (Türkiye)
Outcome results
None listed