The Effects of Gen‐AI on Situated and Future‐Driven Academic Writing Motivation

Despite the increasing use of Generative Artificial Intelligence (Gen‐AI) in education, there is still a significant gap in understanding its effects on the situated‐ and future‐driven motivation in academic writing. This longitudinal design‐based research sought to explore variations in academic writing motivation of 110 Chinese university English learners. It focused on two constructs: situated motivation, as conceptualised by self‐determination theory and future‐oriented motivation, through the L2 motivational self system. Data were collected at the beginning, middle and end of one semester through a combination of surveys, Motometer graphs, stimulated recall interviews and semi‐structured interviews. The analysis revealed three major findings. First, Gen‐AI use produced a significant change in identified regulation within situated motivation, while other components of situated motivation were not measurably affected. Second, Gen‐AI exerted a significant influence on future L2 selves within the future‐driven motivation. Third, the study underscores the critical role of basic psychological needs for autonomy and competence in bridging situated motivational experiences with the development of the ideal L2 self. Overall, the findings suggest that a pedagogically informed integration of Gen‐AI, designed to nurture autonomy and competence, is vital for fostering situated and future‐driven motivation in academic writing.