Writing Blog Articles using Generative AI: Quantitative Modelling of College Students' Attitude and Intention to Use

Abstract

Artificial Intelligence (AI) has reshaped the landscape of various sectors, including education and content creation. Understanding human and AI interactions has never been more important. This study investigates the behavioral factors influencing college multimedia arts students’ acceptance and attitude in integrating generative AI tools in their writing process for blog article writing. Using the Technology Acceptance Model (TAM), the research examines the connection among knowledge, perceived usefulness, perceived ease of use, attitude, and intention to use generative AI. A descriptive-correlational design was implemented, and data were collected from 141 multimedia arts students enrolled in a “Writing for New Media” subject, the core requirement course is to use generative AI in writing the contents of their blogsites. Confirmatory factor analysis (CFA) was employed to test the reliability and discriminant validity of the constructs, while covariance-based structural equation modeling (CB-SEM) was used to assess the relationships and model fit. Results revealed that knowledge significantly predicted both perceived ease of use (β = 0.529, p < 0.001) and perceived usefulness (β = 0.535, p < 0.001), Highlighting the role of AI literacy in facilitating adoption. Perceived usefulness emerged as the strongest predictor of attitude (β = 1.181, p < 0.001), while ease of use was not a significant determinant of attitude (β = 0.143, p = 0.070). Importantly, attitude strongly predicted intention to use AI (β = 0.859, p < 0.001). Findings suggest that strengthening student understanding of generative AI and emphasizing its practical benefits—such as improved writing quality and efficiency—are critical to building positive attitudes and sustained use. The study recommends developing an ecosystem to encourage AI literacy and incorporating it into curricula to promote ethical, confident, and informed use of AI tools in education. This research contributes to the growing knowledge of human and AI interaction.

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