Show Me How to Play: Exploring Self-Modeling for Onboarding in Virtual Reality Exergames

Honorable Mention
Social & Collaborative VRFitness Tracking & Physical Activity MonitoringFull-Body Interaction & Embodied InputGame Developers & DesignersAthletes & Fitness Enthusiasts

Paper Title

Show Me How to Play: Exploring Self-Modeling for Onboarding in Virtual Reality Exergames

Publication Info

  • Topic area: Virtual reality exergames and onboarding tutorials
  • Keywords: VR exergames, onboarding, self-modeling, trial-and-error, tutorials, player experience, learning theories, embodiment, physical activity, motivation

Background and Problem

  • Problem / challenge: Onboarding players in VR exergames to perform correct movements remains challenging, especially given the risks of collisions and injuries due to incorrect execution.
  • Significance: Proper onboarding can enhance player performance, reduce frustration, and improve safety in VR exergames, which are increasingly popular for promoting physical activity.
  • Motivation and related work: Previous studies have explored tutorial designs in VR games but have not compared exploratory (trial-and-error) and demonstration-based (observational learning) tutorials in VR exergames. The gap in understanding the effects of these approaches motivates this study.

Solution

  • Proposed approach: Development and evaluation of two onboarding tutorials for VR exergames: (i) trial-and-error tutorial (T&E) and (ii) self-model tutorial (GHOST), which temporarily disembodies players to observe their avatar performing correct movements.
  • Novelty:
    1. Introduction of a novel self-model tutorial (GHOST) leveraging transitional embodiment and observational learning.
    2. Empirical comparison of exploratory (T&E) and demonstration-based (GHOST) tutorials in VR exergames.
    3. Insights into the effects of tutorials on player experience, performance, and motivation.
  • Procedure and key techniques:
    • Design of a boxing-themed VR exergame (BoxPunchVR) with target-based tasks.
    • Implementation of T&E (trial-and-error learning) and GHOST (self-model observational learning) tutorials.
    • Between-participants study with 60 participants across three conditions: BASE (no tutorial), T&E, and GHOST.
    • Collection of psychometric, physiological, and performance metrics.

Results

  • Concrete findings:
    • GHOST significantly improved punch accuracy (median accuracy: 0.92) compared to T&E (0.85) and BASE (0.74).
    • GHOST increased perceived ease of control, progress feedback, and motivation compared to other conditions.
    • Both T&E and GHOST reduced frustration compared to BASE.
  • Advantage over baselines:
    • GHOST outperformed T&E and BASE in accuracy, ease of control, and perceived usefulness.
    • T&E improved accuracy and reduced frustration compared to BASE but was less effective than GHOST.
  • Experiments / evaluation:
    • Study with 60 participants (20 per condition), measuring punch accuracy, heart rate, player experience (PXI, IMI), workload (NASA-TLX), and perceived embodiment (VEQ, IPQ).
    • Qualitative feedback highlighted the importance of tutorials for understanding game mechanics.
  • Limitations and future work:
    • Limited to short-term gameplay; long-term learning retention was not assessed.
    • Results influenced by the specific design of BoxPunchVR; findings may vary for other VR exergames.
    • Need for further exploration of transitional embodiment and player-sensitive tutorials.

Summary

This study introduces and evaluates two onboarding tutorials for VR exergames: a trial-and-error approach (T&E) and a novel self-model tutorial (GHOST). The GHOST tutorial, leveraging observational learning and transitional embodiment, significantly improved player performance, ease of control, and motivation compared to T&E and BASE. Findings highlight the importance of tutorials for enhancing player experience and reducing frustration in VR exergames. The study proposes implications for future research, including exploring transitional embodiment, player-sensitive tutorials, and additional learning theories.

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https://hci.top/en/papers/chi/222602/2026

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DOI: https://doi.org/10.1145/3772318.3790333
At a Glance

Paper Snapshot

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Source
CHI
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Year
2026
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Award
Honorable Mention
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Authors
4 authors
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Subtopics
Social & Collaborative VR, Fitness Tracking & Physical Activity Monitoring, Full-Body Interaction & Embodied Input
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Professions
Game Developers & Designers, Athletes & Fitness Enthusiasts
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Content Status
Full text indexed
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