Date of Award

10-13-2025

Degree Type

Thesis

Degree Name

MSc in Nursing

Department

School of Nursing and Midwifery, Pakistan

Abstract

Background: Artificial intelligence (AI) has emerged as a transformative tool in education, offering personalized and adaptive learning experiences that enhance student engagement and outcomes. Despite its growing use in various academic fields, the integration of AI in nursing education remains limited. Understanding undergraduate nursing students’ perceptions, intentions, and engagement with AI is essential for its effective implementation in nursing curricula.  
Purpose: Using the Technology Acceptance Model (TAM), this study aimed to assess nursing students’ perceptions, intentions, and engagement regarding the use of AI in their learning. It also examined socio-demographic factors influencing these dimensions to enhance understanding of AI adoption. 
Methods: This analytical cross-sectional study was conducted in two nursing colleges in Lahore, Pakistan, which is a low- and middle-income country. From these colleges, 268 undergraduate nursing students were enrolled through a convenience non-probability sampling technique, and data were collected using a structured questionnaire based on the Technology Acceptance Model. This model is based on the idea that perceived usefulness and perceived ease of use are the two main factors determining an individual’s intention to use technology. Before using the questionnaire, its validity was ensured through content validity index (CVI) testing, showing high values for both clearance (0.90) and relevance (0.91). Data was analyzed using Statistical Package for Social Sciences (SPSS) version 22, employing descriptive statistics such as frequencies and percentages, along with inferential analysis using the Chi-square test. A p-value < 0.05 is considered statistically significant. 
Findings: Students had positive perceptions, intentions, and engagement regarding the use of AI in their learning. Across socio-demographic variables, three significant associations were found: internet availability with perceived ease of use (p = 0.017), sexual identity with intention to use (p = 0.042), and place of residence with engagement (p = 0.040). Perceived usefulness and perceived ease of use had a statistically significant association (p <  0.001) with intention to adopt AI.  
Conclusion: Nursing students showed overall positive perceptions, intentions, and engagement toward AI in learning. Limited demographic influences were observed; perceived usefulness and perceived ease of use significantly predicted the intention to adopt AI. These findings suggest integrating AI literacy into nursing curricula, training faculty in its effective use, and establishing clear ethical guidelines for the integration of AI.

Comments

Advisor's name not mentioned.

First Page

1

Last Page

119

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