HCApr 23, 2018

StreamBED: Training Citizen Scientists to Make Qualitative Judgments Using Embodied Virtual Reality Training

arXiv:1804.08732v19 citations
Originality Synthesis-oriented
AI Analysis

This addresses the challenge of enhancing qualitative assessment abilities in citizen scientists for environmental monitoring, though it is incremental as it builds on existing VR training methods.

The paper tackled the problem of training citizen scientists to make qualitative judgments in environmental monitoring by developing StreamBED, a VR-based training environment for water quality assessment, resulting in a preliminary design and evaluation that shows potential for improving volunteer skills.

Environmental citizen science frequently relies on experience-based assessment, however volunteers are not trained to make qualitative judgments. Embodied learning in virtual reality (VR) has been explored as a way to train behavior, but has not fully been considered as a way to train judgment. This preliminary research explores embodied learning in VR through the design, evaluation, and redesign of StreamBED, a water quality monitoring training environment that teaches volunteers to make qualitative assessments by exploring, assessing and comparing virtual watersheds.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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