A Self-Determination Theory-based Career Counseling Chatbot: Motivational Interactions to Address Career Decision-Making Difficulties and Enhance Engagement

Post-college unemployment represents a significant social problem, driven by graduates’ career decision-making difficulties. Many individuals seek career counseling, but most methods focus on information delivery rather than motivation. Without sufficient motivation, students often struggle to make informed decisions. We aim to demonstrate the effectiveness of a self-determination theory-based career counseling chatbot (SDT chatbot) by developing and comparing two chatbots: SDT chatbot and a general career counseling chatbot (non-SDT chatbot). An experiment with 20 university students revealed that the SDT chatbot was more effective in addressing career decision-making difficulties. Semi-structured interviews showed that integrating competence, relatedness, and autonomy into the chatbot design facilitated the resolution of career decision-making difficulties. However, no significant differences were observed in engagement between the two chatbots. The analysis identified four aspects of chatbot interaction (crystallization, self-reflection, revalidation, and epistemic curiosity) that promote engagement. Based on these findings, we propose an SDT chatbot design for career counseling.