17112-4 Integration of Self-Determination Theory and Implicit Theories in Understanding Intentions for AI Adoption

Abstract

The accelerated integration of Artificial Intelligence (AI) into global education systems necessitates a deep understanding of the psychological drivers and barriers influencing its adoption. This is particularly critical in Indonesia, where rapid digital transformation coexists with significant variations in technology access and infrastructure, creating unique adoption challenges. Despite AI’s potential to enhance learning quality, a substantial research gap exists regarding the interplay between motivational frameworks (Self-Determination Theory - SDT) and cognitive beliefs (Implicit Theories of mindset) in predicting AI usage intentions within this context. The objective of this study is to evaluate the combination of Self-Determination Theory (SDT) and Implicit Theories to analyse the interaction between fundamental psychological needs (autonomy, competence, relatedness) and mindset (fixed vs growth mindset) in the context of predicting AI usage intentions. The integration of these two theories is expected to contribute to a holistic model that explains how intrinsic motivation and beliefs about one's ability to develop influence the acceptance of AI technology. The proposed method employs a quantitative, regression. This approach will test the main effects of needs and mindset, their interaction effects on usage intention, and the model's overall predictive power. This research is expected to provide a deeper understanding of how basic psychological factors influence individuals' decisions to adopt AI technology and how educational institutions and policymakers can design strategies that support the ethical and effective use of AI.