VIRTUAL NURSING DIAGNOSIS AS AN E-MOBILE LEARNING STRATEGY TO IMPROVE MEDICAL-SURGICAL NURSING COMPETENCY EXAMINATION OUTCOMES

Abstract

Medical-Surgical Nursing is a core competency in nursing education that is directly related to mastery of clinical reasoning, the nursing process, and case-based decision-making. Student competency test performance still faces challenges, particularly in clinical vignette-based questions that require accuracy in identifying data, establishing nursing diagnoses, and prioritizing interventions. The integration of Virtual Nursing Diagnosis based on e-mobile learning has the potential to be a learning innovation that supports strengthening students' understanding of nursing diagnoses and preparing them for the Medical-Surgical Nursing competency test. This study aimed to analyze the effect of Virtual Nursing Diagnosis as an Augmented Reality-based e-mobile learning strategy on Medical-Surgical Nursing competency examination outcomes among Diploma III nursing students. This quasi-experimental study involved 80 final-year Diploma III nursing students selected using purposive sampling, consisting of 40 students in the intervention group and 40 students in the control group. The intervention group received Virtual Nursing Diagnosis using Augmented Reality-based e-mobile learning via smartphone, while the control group received intensive conventional learning. The instrument used was a 20-question Medical-Surgical Nursing competency exam, then the data were analyzed using the Mann-Whitney test. The intervention group achieved higher post-test scores than the control group, with median scores of 85.00 and 60.00, respectively. The Mann-Whitney test showed a significant difference between the two groups with a p-value of 0.000 (<0.05) and an effect size of 0.84. Virtual Nursing Diagnosis as an Augmented Reality-based e-mobile learning strategy effectively improved students’ Medical-Surgical Nursing competency examination outcomes.