AI am Motivated: Leveraging Self-Determination Theory in Chatbots

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Authors: Craig Sims, Jack Moursounidis, Rachel Sarah Sheffield, Nik Thompson, Abhijeet Singh, Anna Bunn, Li Sha
Cited by: 0
References: 16

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.

Fields of Study & Subjects

AI in Service Interactions Artificial Intelligence in Education Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
Acta Pedagogia Asiana
Volume
5
Issue
1
Pages
65–72
Publication date
19 January 2026