Affiliation:
1. Purdue University, USA
2. University of the Aegean & University of the Peloponnese, Greece
3. Clemson University, USA
Abstract
Although researchers have explored how humans perceive the intelligence of virtual characters, few studies have focused on the ability of intelligent virtual characters to fix their mistakes. Thus, we explored the self-correction behavior of a virtual character with different intelligence capabilities in a within-group design (
\(N=23\)
) study. For this study, we developed a virtual character that can solve a jigsaw puzzle whose self-correction behavior is controlled by two parameters, namely,
Intelligence
and
Accuracy of Self-correction
. Then, we integrated the virtual character into our virtual reality experience and asked participants to co-solve a jigsaw puzzle. During the study, our participants were exposed to five experimental conditions resulting from combinations of the
Intelligence
and
Accuracy of Self-correction
parameters. In each condition, we asked our participants to respond to a survey examining their perceptions of the virtual character's intelligence and awareness (private, public, and surroundings awareness) and user experiences, including trust, enjoyment, performance, frustration, and desire for future interaction. We also collected application logs, including participants’ dwell gaze data, completion times, and the number of puzzle pieces they placed to co-solve the jigsaw puzzle. The results of all the survey ratings and the completion time were statistically significant. Our results indicated that higher levels of
Intelligence
and
Accuracy of Self-correction
enhanced not only our participants’ perceptions of the virtual character's intelligence, awareness (private, public, and surroundings), trustworthiness, and performance but also increased their enjoyment and desire for future interaction with the virtual character while reducing their frustration and completion time. Moreover, we found that as the
Intelligence
and
Accuracy of Self-correction
increased, participants had to place fewer puzzle pieces and needed less time to complete the jigsaw puzzle. Lastly, regardless of the experimental condition to which we exposed our participants, they gazed at the virtual character for more time compared to the puzzle pieces and puzzle goal in the virtual environment.
Publisher
Association for Computing Machinery (ACM)
Reference101 articles.
1. Pedro Acevedo, Alejandra Magana, Christos Mousas, Yoselyn Walsh, Hector Will Pinto, and Bedrich Benes. Effects of tactile feedback on conceptual understanding of electromagnetism in a virtual reality experience. In 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), pages 588–593. IEEE, 2022.
2. Sean Andrist, Michael Gleicher, and Bilge Mutlu. Looking coordinated: Bidirectional gaze mechanisms for collaborative interaction with virtual characters. In Proceedings of the 2017 CHI conference on human factors in computing systems, pages 2571–2582, 2017.
3. A fast, iterative solver for the inverse kinematics problem;Aristidou Andreas;Graphical Models,2011
4. Automation-induced complacency for monitoring highly reliable systems: the role of task complexity, system experience, and operator trust;Bailey Nathan R;Theoretical Issues in Ergonomics Science,2007
5. Bowen Baker, Ingmar Kanitscheider, Todor Markov, Yi Wu, Glenn Powell, Bob McGrew, and Igor Mordatch. Emergent tool use from multi-agent autocurricula. arXiv preprint arXiv:1909.07528, 2019.