PhD Thesis Defence - Mint Tanprasert

Name: Mint Tanprasert

Date: March 12

Time: 9 am - 12 pm

Location: ICCS 238

Supervisor: Dongwook Yoon

Title: Agent Persona Design for Engagement in Virtual Dialogic Learning Environments

Abstract:
Asynchronous online learning (AOL) (e.g., online courses, video-sharing platforms) has become popular for its variety, accessibility, and flexibility. However, AOL often lacks the rich social interactions of traditional classrooms, lowering learners’ engagement and, consequently, their evaluative performance. The recent advancement of Large-language Models (LLMs) illuminates a potential solution of using AI agents for real-time dialogic learning---a pedagogical approach involving dialogues, which has been shown to enhance learners’ behavioral, emotional, and cognitive engagement. This approach is closely intertwined with the characteristics and perception of the interactors (learners, educators, etc.), so the design of the agent's persona (behaviors, appearances, and identity cues) is crucial. However, although many persona attributes can be simulated with AI, designing agents’ persona presents two challenges: (1) humans respond to the same trait in human and AI agents differently, so existing frameworks of human-human interactions cannot be applied directly; and (2) LLM-based agent's behaviors may fluctuate due to learners’ input, necessitating a new conceptualization of behaviors in empirical studies. In this thesis, I aim to address these challenges and show that persona design of educational agents in dialogic learning environments improves learning engagement for asynchronous, online learners.

I demonstrate this via three research projects, which cover three social learning experiences. The first project focuses on debates (learners argue with agents with the opposite stance from them) and how the agent's social identity and rhetorical styles impact their influence. The second project concerns collaborative activities (learners work with peer agents with different values from theirs towards the same goal) and the impacts of the agent’s collaborative strategies and the disclosure of their strategies to learners. The third project is about vicarious dialogues (learners observe conversations between multiple characters) and the design of virtual group dynamics. The findings demonstrate that theoretically grounded and learner-centric persona designs of agents improve learning engagement. They also highlight the importance of contextual factors (e.g., activity types, learners’ values) when applying social learning theories to agents, generate design implications for agent persona design beyond AOL contexts, and raise ethical and pedagogical considerations for the upcoming era of AI-powered education.