Abstract:

The rapid adoption of Generative Artificial Intelligence (GAI) tools such as ChatGPT, Gemini, and Claude is reshaping how students engage with academic writing and self-regulated learning in higher education. This study, drawn from an ongoing doctoral dissertation, uses a quantitative, correlational research design to examine how the frequency and duration of GAI use relate to college freshmen’s motivation to write. College freshmen are the focus due to their transitional academic writing demands and developing self-regulatory capacities.

The study is theoretically grounded in the Technology Acceptance Model (TAM), Self-Determination Theory (SDT), and Cognitive Load Theory (CLT), which together provide a framework for examining perceived usefulness, autonomy support, and cognitive processing in AI-supported writing contexts. Data are being collected using validated survey instruments, and multiple linear regression is planned to assess the extent to which frequency and duration of GAI use individually and in combination predict variance in writing motivation. Conceptual mediation constructs are used to guide interpretation of learner experiences rather than to test causal relationships.

As a study in progress, this research seeks to contribute empirical insight into the conditions under which GAI may support student motivation and writing engagement without undermining autonomy or increasing cognitive overload. The anticipated contribution of this work lies in advancing theoretical integration across motivation, technology acceptance, and cognitive load perspectives, while offering preliminary guidance for ethical and pedagogically grounded AI integration in higher education. The study aims to inform educators, instructional designers, and researchers navigating the evolving role of generative AI in academic writing instruction.

Keywords:

Technology, Education, Generative AI.