Artificial Intelligence (AI), Nursing Students
Conditions
Keywords
nursing student, airtificial intelligence, nursing education
Brief summary
This study aims to determine the effects of AI-supported oncology case analysis on nursing students' knowledge, learning satisfaction, and clinical decision-making skills.
Detailed description
The literature on the use of AI in nursing education remains limited. This study aims to determine the effects of AI-supported oncology case analysis on nursing students' knowledge, learning satisfaction, and clinical decision-making skills. This study was conducted as a single-blind randomized controlled trial. The study population consisted of second-year nursing students enrolled in the elective Oncology Nursing course in the Department of Nursing at a public university. During the spring semester of the 2025-2026 academic year, a total of 42 second-year nursing students were actively enrolled in the Oncology Nursing course. The students were randomly assigned to either the traditional teaching group or the AI-supported group. Data were collected using a participant information form, a knowledge test, a learning satisfaction scale, a clinical decision-making scale, and a semi-structured interview form.
Interventions
OTHERAI-supported case
AI-supported case: In the artificial intelligence supported case analysis course, students will listen to the audio video prepared by artificial intelligence.
The case analysis for this group will be conducted by the course instructor.
Sponsors
TC Erciyes University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
In this study, nursing students were randomly assigned to either the traditional teaching group or the AI-supported group.
Eligibility
Sex/Gender
ALL
Age
18 Years to 35 Years
Healthy volunteers
Yes
Inclusion criteria
* Second-year nursing students actively enrolled during the spring semester of the 2025-2026 academic year. Having previously completed the theoretical Nursing Process course. Owning a smartphone with internet access. Having previously prepared at least one individualized nursing care plan for a patient hospitalized in an internal medicine clinical setting.
Exclusion criteria
* Students who had not previously provided planned nursing care for hospitalized patients in internal medicine clinical settings during their clinical placements. Students who did not agree to participate in the study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Knowledge level | Baseline and immediately after completion of the intervention (same day) | Knowledge level: Knowledge level will be assessed using a researcher-developed 10-item multiple-choice knowledge test. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Learning satisfaction | Learning satisfaction: Immediately after completion of the intervention (same day) | Learning satisfaction: Learning satisfaction was assessed using a 0-10 numeric rating scale. |
| Clinical decision-making | Immediately after completion of the intervention (same day) | Clinical decision-making: Clinical decision-making was assessed using the 40-item Clinical Decision-Making in Nursing Scale (CDMNS). The scale measures nursing students' clinical decision-making abilities, with higher scores indicating better clinical decision-making skills. |
Countries
Turkey (Türkiye)
Outcome results
None listed