Content area
Abstract
This thesis explores the impact of generative AI, such as ChatGPT, on education. Specifically, it examines the factors influencing the adoption of generative AI and its potential impact on student engagement, performance, and upskilling. Recognizing the evolving nature of this field, there is a pressing need to explore its complexities further. As a result, the study not only identifies key variables that shape the adoption of generative AI in education but also addresses gaps in the existing literature. The thesis presents a theoretical model to explore the topic, utilizing a structural equation model (PLS-SEM) and employing empirical testing through a survey. The findings indicate that 46.5% of generative AI adoption can be explained by educational level, performance expectancy, social influence, and trust. Additionally, the model highlights the explanatory power of generative AI in influencing student engagement (25.4%), student performance (47.9%), and upskilling (28.8%). The research provides significant novel insights into the evolving role of generative AI in reshaping education, offering a nuanced perspective crucial for guiding future initiatives and policies in this dynamic field.