Project overview
Our recent VR dyad study found substantial heterogeneity between dyads: a population model of body-cue decoding transferred well to some held-out pairs and poorly to others, and this was not explained by how readable the Sender’s body was. One candidate explanation is familiarity: partners who know each other may share idiosyncratic decoding conventions. In the study sample, 11 of 17 analyzed dyads were acquaintances and 6 were strangers, which provides pilot contrasts but was never designed as a manipulation. This project makes familiarity the independent variable.
Project motivation
If shared attention is partly a learned, dyad-specific convention, stranger pairs should decode worse initially and improve with joint exposure, and models trained on one pair should transfer better within friend pairs than across them. This bears on both theory (is the body-to-attention mapping universal or negotiated? [1]) and practice: avatar systems for ad-hoc collaboration between strangers may need stronger explicit cues than systems for established teams.
Project goals
- Secondary analysis (starter). Using the existing 17-dyad dataset and its acquaintance labels, compare decoding error, cue weighting, and model transfer between friend and stranger dyads.
- Familiarity experiment. Recruit stranger and friend dyads in equal numbers, run the established decoding task, and measure learning across blocks: do stranger dyads converge toward friend-dyad performance within a session?
You will
- Perform a literature review on familiarity effects in nonverbal communication
- Run a secondary analysis on the existing dataset (Python, mixed models)
- Conduct a dyad study with the existing VR environment and pipeline
- Analyze group differences and within-session learning curves
- Summarize your findings in a thesis and present them to an audience
- (Optional) co-write a research paper
You need
- Strong communication skills in English
- Basic Python and statistics
- Care and reliability when running participant studies
References
- Stephenson, L. J., Edwards, S. G., & Bayliss, A. P. (2021). From gaze perception to social cognition: The shared-attention system. Perspectives on Psychological Science.
- Rivu, R., Zhou, Y., Welsch, R., Mäkelä, V., & Alt, F. (2021). When Friends Become Strangers: Understanding the Influence of Avatar Gender on Interpersonal Distance in Virtual Reality. INTERACT 2021. https://doi.org/10.1007/978-3-030-85607-6_16
- Kendon, A. (1967). Some functions of gaze-direction in social interaction. Acta Psychologica, 26.
- The parent study on avatar-mediated shared attention in virtual reality; details are available from the advisor on request.
Keywords: VR, Familiarity, Dyads, Individual Differences, Shared Attention