Filling the Silence: Educating Users During Long-Latency Tasks in Conversational Procedural Generation

Abstract

Natural interaction plays a crucial role in keeping users immersed in virtual reality, particularly when embodied conversational agents (ECAs) serve as expert guides. This becomes especially important during procedural generation, as it often involves disruptive waiting periods. This paper investigates how waiting time in virtual reality can be meaningfully filled by using an ECA for educational purposes. We present a framework that enables the ECA to manipulate procedural generation parameters and initiate the process through natural conversation. During the generation period, the ECA interacts with users to deliver educational content, effectively utilizing the waiting time. We conducted a user study to evaluate three agent behaviors during procedural generation waiting periods: topic-restricted conversation, unrestricted conversation, and topicrestricted conversation with active turn-taking. We examined how the different conversational strategies impact user motivation, time perception, and subjectively-rated learning outcomes during procedural generation waiting periods. Results suggest that topic-restricted conversations significantly enhance users' learning outcomes about circularity in the building lifecycle, while unrestricted conversations lead to a significant decrease in self-reported general learning outcomes. Additionally, active turn-taking alone did not significantly influence motivation or alter users' perception of time. These findings suggest that allowing unrestricted conversations may result in off-topic or uninformative exchanges, reducing the learning benefit. In contrast, keeping conversations focused on a specific topic enhances perceived learning outcomes.