The Effects of Depth of Knowledge of a Virtual Agent

We explored the impact of depth of knowledge on conversational agents and human perceptions in a virtual reality (VR) environment. We designed experimental conditions with low, medium, and high depths of knowledge in the domain of game development and tested them among 27 game development students. We aimed to understand how the agent's predefined knowledge levels affected the participants' perceptions of the agent and its knowledge. Our findings showed that participants could distinguish between different knowledge levels of the virtual agent. Moreover, the agent's depth of knowledge significantly impacted participants' perceptions of intelligence, rapport, factuality, the uncanny valley effect, anthropomorphism, and willingness for future interaction. We also found strong correlations between perceived knowledge, perceived intelligence, factuality, and willingness for future interactions. We developed design guidelines for creating conversational agents from our data and observations. This study contributes to the human-agent interaction field in VR settings by providing empirical evidence on the importance of tailoring virtual agents' depth of knowledge to improve user experience, offering insights into designing more engaging and effective conversational agents.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2024-09-10
DOI
https://doi.org/10.1109/tvcg.2024.3456148
Citations
16
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
12.47
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article

The Effects of Depth of Knowledge of a Virtual Agent

Fu‐Chia Yang, Christos Mousas, Kevin Duque
16 citations
IEEE Transactions on Visualization and Computer Graphics
Education and Learning Interventions
12.47
article

The Effects of Depth of Knowledge of a Virtual Agent

Fu‐Chia Yang, Christos Mousas, Kevin Duque
article en
16 citations

Abstract

We explored the impact of depth of knowledge on conversational agents and human perceptions in a virtual reality (VR) environment. We designed experimental conditions with low, medium, and high depths of knowledge in the domain of game development and tested them among 27 game development students. We aimed to understand how the agent's predefined knowledge levels affected the participants' perceptions of the agent and its knowledge. Our findings showed that participants could distinguish between different knowledge levels of the virtual agent. Moreover, the agent's depth of knowledge significantly impacted participants' perceptions of intelligence, rapport, factuality, the uncanny valley effect, anthropomorphism, and willingness for future interaction. We also found strong correlations between perceived knowledge, perceived intelligence, factuality, and willingness for future interactions. We developed design guidelines for creating conversational agents from our data and observations. This study contributes to the human-agent interaction field in VR settings by providing empirical evidence on the importance of tailoring virtual agents' depth of knowledge to improve user experience, offering insights into designing more engaging and effective conversational agents.

IEEE Transactions on Visualization and Computer GraphicsVol. 30(11)
Purdue University West Lafayette (US), Tecnológico de Monterrey (MX)
Reduced inequalities
Openalex Percentile: Top 1%
Education and Learning Interventions
12.47
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