Research Papers


Conversational agents (CAs), defined as software with which users interact through natural language, have gained increasing interest in education due to their potential to support individual learning on a large scale. With improved capabilities driven by advances in machine learning and natural language processing, these agents pave the way for a new generation of tutoring systems that offer an intuitive learning experience and can automatically tailor to individual learning styles and needs. A particular characteristic of CAs is their potential for anthropomorphic design, which can facilitate the feeling of a human contact in technology-enabled individual learning and contribute to a learner’s motivation. While recent studies provide valuable prescriptive knowledge on how to design pedagogical CAs, we still lack an understanding of the impact of a human-like design on individual motivational regulations and perceived inclusiveness. In this study, we contribute to closing this research gap by investigating individual learner’s perception of a CA by means of a 3x1 experiment with 149 participants. Drawing on Social Response Theory and Self-Determination Theory, we find empirical evidence that anthropomorphic design and associated perceptions of humanness contribute to individual intrinsic motivation of learners and discover a positive effect on inclusiveness.



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