Abstract
Artificial intelligence (AI)-powered chatbots promised to streamline administrative tasks and offer just-in-time support within higher education institutions. However, many existing chatbots prioritised simple information delivery over the cultivation of deeper student engagement and intrinsic motivation. This paper argued that Self-Determination Theory (SDT), a prominent framework for understanding motivation, offered a robust model for designing chatbots that went beyond passive answering to become active facilitators of student agency. SDT emphasised three core psychological needs: autonomy, competence, and relatedness. This paper explored how the intentional integration of these needs into chatbot design could transform administrative support interactions into opportunities to empower students as self-directed learners.
Cite
CITATION STYLE
Sims, C., Moursounidis, J., Sheffield, R., Thompson, N., Singh, A., Bunn, A., & Sha, L. (2026). AI am Motivated: Leveraging Self-Determination Theory in Chatbots. Acta Pedagogia Asiana, 5(1), 65–72. https://doi.org/10.53623/apga.v5i1.950
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