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Conducting online virtual environment experiments with uncompensated, unsupervised samples.

Bernd HuberKrzysztof Z Gajos
Published in: PloS one (2020)
Web-based experimentation with uncompensated and unsupervised samples allows for a larger and more diverse sample population, more generalizable results, and faster theory to experiment cycle. Given that participants are unsupervised, it is still unknown whether the data collected in such settings would be of sufficiently high quality to support robust conclusions. Therefore, we investigated the feasibility of conducting such experiments online using virtual environment technologies. We conducted a conceptual replication of two prior experiments that have been conducted in virtual environments. Our results replicate findings previously obtained in conventional laboratory settings. These results hold across different device types of participants (ranging from desktop, through mobile devices to immersive virtual reality headsets), suggesting that experiments can be conducted online with uncompensated samples in virtual environments.
Keyphrases
  • virtual reality
  • machine learning
  • social media
  • health information
  • healthcare
  • electronic health record
  • artificial intelligence
  • mass spectrometry
  • deep learning
  • data analysis