The influence of AI literacy on pre-service teachers’ learning motivation: the mediating role of basic psychological needs

Introduction The rapid integration of generative AI into higher education has raised critical questions about how learners’ intrinsic motivation is transformed. Pre-service teachers, as both current learners and future educators, represent a particularly important population for examining this issue. Methods This study employed an explanatory sequential mixed-methods design. A sample of 600 pre-service teachers completed questionnaires assessing four dimensions of AI literacy (awareness, application, evaluation, ethics), basic psychological needs (autonomy, competence, relatedness), and learning motivation. Structural equation modeling was used to test hypothesized relationships. Subsequently, semi-structured interviews were conducted with 36 pre-service teachers and 8 course instructors to provide qualitative elaboration. Results AI awareness and application negatively predicted autonomy ( β = –0.190 and –0.332, respectively), while AI evaluation and ethics positively predicted competence ( β = 0.315, 0.326) and relatedness ( β = 0.333, 0.419). All three psychological needs mediated the relationships between AI literacy dimensions and learning motivation, with competence showing the strongest indirect effects (0.135-0.143). Contrary to predictions from social comparison and technostress theories, AI awareness positively predicted competence ( β = 0.142) and relatedness ( β = 0.172). Discussion The findings reveal differentiated effects of AI literacy dimensions on basic psychological needs. An “identity-context dual boundary” framework is proposed to explain when AI awareness becomes empowering rather than threatening. These results extend self-determination theory to intelligent educational contexts and provide practical guidance for AI literacy curriculum design in teacher education.