SIMULATING REALITY: TRAINING CITIZEN SCIENTISTS TO JUDGE STREAM HABITATS IN MULTISENSORY VIRTUAL REALITY
Striner, Alina Goldman
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Citizen science is a form of crowdsourcing that allows volunteers to participate in scientific data collection and analysis. Many citizen scientists are engaged and motivated by science-based learning and discovery, but high training costs and limited resources often result in volunteers participating in unskilled work, leading to boredom and disengagement. Advances in immersive virtual reality (VR) have created opportunities to recreate physical environments with minimal cost, making it possible to train citizen scientists to make qualitative experiential judgments usually reserved for domain experts. This research trains citizen scientists to assess outdoor stream habitats using StreamBED VR, a multisensory VR training platform. This research offers the following contributions: 1. A study of how expert and novice water monitors make qualitative assessments of outdoor stream habitats using an EPA qualitative protocol. The research found that experts develop intuitive judgments of quality, use multisensory environmental information to make judgments, and construct past and future narratives of streams using environmental characteristics. 2. Iterative design of the Ambient Holodeck multisensory system, and a study of how ambient sensory information impacts observation skills. The research found that multisensory information increased the number of observations participants made, and positively affected engagement and immersion. 3. Iterative design of the StreamBED VR training platform, and two studies; the former explores how qualitative assessment skills can be taught in VR, and the latter considers how training in VR, with and without Multisensory cues, compares to a PowerPoint (PPT) baseline. Study results found although VR participants were more excited to continue training than PPT participants, Standard VR and PPT participants scored closest to an expert gold standard, performing significantly better than Multisensory VR participants. This research concludes that VR has the potential to train qualitative assessment tasks, but qualifies that training design is multifaceted and complex, full of theoretical learning considerations and practical challenges. Further, VR realism can be a powerful tool for training, but is only effective when training cues clearly parallel assessment tasks.