The Effects of Embodiment and Personality Expression on Learning in LLM-based Educational Agents

Understand

This work investigates how personality expression and embodiment affect personality perception and learning in educational conversational agents.

• We extend an existing personality-driven conversational agent framework by integrating LLM-based conversation support tailored to an educational application.
• We describe a user study built on this system to evaluate two distinct personality styles: high extroversion and agreeableness and low extroversion and agreeableness.
• For each personality style, we assess three models: (1) a dialogue-only model that conveys personality through dialogue, (2) an animated human model that expresses personality solely through dialogue, and (3) an animated human model that expresses personality through both dialogue and body and facial animations.