Human-Computer Interaction Institute
School of Computer Science, Carnegie Mellon University


Supporting Learner Social Relationships
with Enculturated Pedagogical Agents

Amy Ogan

February 2011

Ph.D. Thesis


Keywords: Virtual agents, pedagogical agents, social relationships, social dialog, dialog modeling, serious games, simulation-based learning, educational technology, intercultural competence, interpersonal skills training, human-computer interaction.

Embodied conversational agents put a "human" touch on intelligent tutoring systems by using conversation to support learning. When considering instruction in interpersonal domains, such as intercultural negotiation, the development of an interpersonal relationship with one's pedagogical agent may play a significant role in learning. However, there is conflicting evidence in the literature both regarding the ability of agents to cultivate social relationships with humans, and their effect on learning. In this dissertation, I present a model of social dialog designed to affect learners' interpersonal relations with virtual agents, a development process for creating social dialog, and empirical studies showing that this dialog has significant effects on learners‚ perceptions of the agents and negotiation performance.

In early work, I explicitly prompted learners to have social goals for the interaction. I found that while students who reported social goals for interacting with the agents had significantly higher learning gains, explicit prompting was not effective at inducing these goals. I thus focused on implicit influence of learner goals, developing a model of social instructional dialog (SID) that integrates conversational strategies that are theorized to produce interpersonal effects on relationships. In two subsequent studies, an agent with the SID model engendered greater feelings of entitativity, shared perspective, and trust, suggesting that the model improved learner social relationships with the agent. Importantly, these effects transferred to other agents encountered later in the environment. The social dialog condition also made fewer errors and achieved more negotiation objectives in a subsequent negotiation than a control group, evidence that the improved social relationship lead to better negotiation performance. These findings regarding interpersonal relationships with agents contribute to the literature on learner-agent interactions, and can guide the future development of agents in social environments.

201 pages

Return to: SCS Technical Report Collection
School of Computer Science homepage

This page maintained by