The paper reviewed research from the past 20 years to identify best practices for object selection and manipulation in Virtual Reality (VR) environments.
The authors extracted 48 studies that used immersive VR technology and included user studies to measure performance in object selection or manipulation tasks from 39 papers presented at major VR/Human-Computer Interaction (HCI) conferences between 2000 and 2019.
Based on the review, the paper provides 10 recommendations for researchers planning VR object selection/manipulation studies. These recommendations cover aspects such as defining research objectives, estimating sample sizes, experimental design, task design, target characteristics, and control of physical/virtual environments. The aim is to enhance reproducibility, leverage previous studies, and facilitate inter-study comparisons.
Additionally, the paper includes a checklist of questions to consider when planning and reporting VR object selection/manipulation studies. It covers details to report regarding methods, participants, design, tasks, targets, materials, results, and analysis.
The paper discusses the need for accumulating insights through multimodal technology, manipulation techniques, depth issues, long-term studies, replication, meta-analysis, and performance modeling in VR research.
Overall, the paper serves as a valuable reference for researchers studying object selection and manipulation interactions in VR, providing systematically derived best practice guidelines. The recommendations and checklist aim to promote rigorous methodology and comprehensive reporting, enhancing research reproducibility and comparability.