Artificial Intelligence Supported Case Analysis and Nursing Students

NCT07087288 | Completed

• 1 other identifier: Erciyessbfhem
• Study Type: interventional
• Target: 93
• Locations: 1 country
• Sites: 1

Brief Summary

In this study, it was aimed to evaluate the effect of artificial intelligence-supported case analysis method on nursing students' knowledge, case management performances and nursing diagnosis determination skills.This study was conducted in a single-blind randomised controlled trial design. Students were randomly assigned to the traditional teaching group, the case analysis group and the artificial intelligence group.

Conditions

Nursing Students; Artificial Intelligence (AI)

Keywords

nursing student; airtificial intelligence; nursing education

Outcome Measures

Primary Outcomes (2)

• Case Management Performance

  In this study, nursing students' interest, focus, satisfaction and motivation levels in the evaluation of traditional teaching method, case analysis method and artificial intelligence supported case analysis method courses were evaluated with Visual Analogue Scale (VAS) over 10 points using Mentimeter application.

  3 hours

• Nursing Diagnosis Determination Skills

  With the Mentimeter application, students were asked to identify 5 prioritised nursing diagnoses related to the case. There is no scoring here, but the application creates a word cloud where the most common answer is shown in a larger font.

  3 hours

Study Arms (3)

Traditional teaching group

NO INTERVENTION

The students in this group will be analysed by the responsible lecturer of the course.

Case Analysis Group

ACTIVE COMPARATOR

Students in this group will present the case of their choice from the clinic.

Other: Case Analysis

Artificial Intelligence Group

EXPERIMENTAL

Students in this group will take artificial intelligence supported case analysis course.

Other: AI-supported case

Interventions

AI-supported case OTHER

In the artificial intelligence supported case analysis course, students will listen to the audio video prepared by artificial intelligence.

Artificial Intelligence Group

Case Analysis OTHER

The case analysis will be made through the presentation prepared by the students in the group.

Case Analysis Group

Eligibility Criteria

• Age: 18 Years - 35 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• Active fourth year nursing students in the spring term of the 2024-2025 academic year in which the study was conducted,
• Having taken the nursing process theoretical course before,
• Having a mobile phone with an internet connection,
• Students who have previously prepared a care plan specific to their inpatients in at least one internal medicine clinic

You may not qualify if:

• Students who do not take the Integrated Health Practices III course,
• Have not planned care for inpatients in internal medicine clinics in previous clinical practice,
• Students who did not agree to participate in the study

Sponsors & Collaborators

• TC Erciyes University: lead

Study Sites (1)

Erciyes University

Kayseri, Türkiye, 38039, Turkey (Türkiye)

Location

Study Officials

• AYSER DÖNER

  TC Erciyes University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Research Assistant

Model Details: In this study, nursing students were divided into three groups as traditional teaching group, case analysis group and artificial intelligence group.

Study Record Dates

• First Submitted: July 9, 2025
• First Posted: July 25, 2025
• Study Start: April 1, 2025
• Primary Completion: June 30, 2025
• Study Completion: June 30, 2025
• Last Updated: July 25, 2025

Record last verified: 2025-07

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)