From Code to Character: Investigating Personality in Generative AI-Driven Educational Avatars

Abstract

As generative artificial intelligence (GAI) continues to shape digital learning environments, AI-driven conversational agents are emerging as effective tools for enhancing student engagement and motivation. These avatars often functioning as virtual tutors or learning companions can be imbued with distinct personality traits, significantly influencing user experience and educational outcomes. This study investigates the role of personality in AI avatars used for learning, with a focus on six positive traits intelligent, sincere, sociable, approachable, creative, and joyful and two negative traits offensive and artificial. We developed a digital prototype consisting of eight unique personality profiles. The prototype takes the form of a chatbot powered by a large language model, enhanced with personality-driven responses. A formative user test was conducted with 15 engineering students, aiming to explore how personality traits influence students' willingness to engage in conversations with AI avatars. The learning objectives aimed to equip students with practical insights into how avatar personality shapes user interaction, develop their skills in conducting technical evaluations collaboratively, and encourage critical reflection on communication strategies used in large language models. During the test, participants interacted with four of the eight personality types. The results indicate that students spent significantly more time interacting with the avatars than anticipated, to the extent that the sessions had to be concluded after 40 minutes. This suggests that personality-rich avatars are highly engaging, new and inspiring for this target group. Students reported increased motivation and a sense of connection during the interactions, highlighting the potential of personality-driven AI in educational settings. Future research directions include refining real-time personality adaptation mechanisms, investigating cross-cultural differences in avatar perception, and examining the long-term effects of avatar personality on learner behaviour and academic performance. This paper contributes to the growing body of research on AI in education by emphasizing the psychological and pedagogical importance of avatar design. The findings offer practical implications for educators, instructional designers, and AI developers seeking to harness the motivational potential of AI-driven learning companions.