Effect of Interactive Cardiovascular Scenario-Based Learning Using Artificial Intelligence on Nursing Students’ Achievement.

Document Type : Research articles

Authors

1 Assistant Lecturer Medical Surgical Nursing, Faculty of Nursing, Alexandria University

2 Professor Emeritus Medical Surgical Nursing, Faculty of Nursing, Alexandria University.

3 Professor Emeritus Medical Surgical Nursing, Faculty of Nursing, Alexandria University

4 Assistant Professor Nursing Education, Faculty of Nursing, Alexandria University.

5 Lecturer Computer Science, Faculty of Computer and Data Science, Alexandria University.

Abstract

Background: Cardiovascular disorders and conditions are a leading global health
challenge, requiring proficient skills of clinical decision-making. Applying traditional
teaching methods often lack the interaction and real-world application. Integrating of
artificial intelligence (AI) into scenario-based learning enhances critical thinking and
clinical decision-making by providing realistic, dynamic, and personalized simulations for
medical – surgical nursing students. Objective: To design an interactive cardiovascular
scenario-based learning using artificial intelligence for medical - surgical nursing
students at the Faculty of Nursing, Alexandria University. To determine the effect of
interactive cardiovascular scenario-based learning using artificial intelligence on medical
- surgical nursing students’ achievement. Settings: This study was conducted in the skill
laboratory of the Medical-Surgical Nursing department at the Faculty of Nursing,
Alexandria University. Lab accommodates approximately 80 students and is equipped with
an interactive panel. Subjects: Subjects of this study comprised a convenient sample of
150 Medical-Surgical Nursing students, who enrolled in the "Medical Surgical Nursing
course". Students randomly divided into two groups of equal size: the control and study
group. Tools: One tool was utilized for data collection in this study namely “Medical -
Surgical Nursing Students’ Achievement Questionnaire”. Results: The study and control
groups showed a statistically significant difference in relation to posttest knowledge level
in understanding across the domains of cardiovascular assessment and ECG, and Overall
Observational checklists in their performance levels. Conclusion: The study concluded
that there were statistically significant differences in post-test knowledge levels between
the control and study groups. Additionally, a comparison of the post-test scores of overall
observational checklists revealed significant differences in performance levels between the
two groups. Moreover, a significant relationship was identified between total knowledge
and variables such as CGPA and computer skills. Experience in using artificial
intelligence software was found to enhance these outcomes Recommendations: Encourage
collaboration between nursing educators, AI developers, and healthcare professionals to
design realistic and impactful simulations focused on nursing interventions


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