Artificial Intelligence Supported Case Analysis on Nursing Education

TC Erciyes University188 enrolled

Overview

Background: Rapid developments in the field of artificial intelligence have begun to necessitate changes and transformations in nursing education. Objective: This study aimed to evaluate the impact of an artificial intelligence-supported case created in the in-class case analysis lecture for nursing students on students' case management performance and satisfaction. Design: This study was a randomized controlled trial. Method: The study involved 188 third-year nursing students who were randomly assigned to either the AI group (n=94) and control group (n=94). An information form, case evaluation form, knowledge test, and Mentimeter application were used to assess the students' case management performance and nursing diagnoses. The level of satisfaction with the case analysis lecture was evaluated using the VAS scale.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

OTHER

Masking

NONE

Enrollment

188

Conditions

Artificial Intelligence Nursing Education Nursing Students

Eligibility

Sex: ALLMin age: 20 YearsMax age: 25 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * having taken nursing process lecture before * having planned care for at least one surgical patient in clinical practice before * having a mobile phone with internet connection Exclusion Criteria: * not attending the case analysis lecture * not being an active student * incomplete completion of the data collection forms * not accepting to participate in the study

Outcomes

Primary Outcomes

Case management performance

The performances of all students included in this study regarding the case lesson were evaluated by means of a knowledge test consisting of 10 questions and a Mentimeter application in which they could indicate their nursing diagnoses. The students will solve the tests after the case lessons are completed. The scores that can be obtained from the tests are between 0-100. As the score of the students increases, it can be interpreted that the level of knowledge increases. In the Mentimeter application, students will be asked to write 5 nursing diagnoses. There is no scoring here, but the application creates a word cloud with the most given answer in a larger font size.

Time frame: 3 hours

Case Satisfaction

The level of satisfaction with the case analysis lecture was evaluated using the VAS scale. The VAS scale is scored between 1-10. Students indicate their satisfaction with the processing of the case lesson. High scores on the VAS indicate a high level of satisfaction.