Place-based education through immersive virtual experiences — preparing biology students for the field

Virtual field trips are transforming education in biology and other place-based disciplines – and not just since Covid-19 has imposed social distancing constraints. Efficient methods for content creation, combined with affordable immersive technology, provide the opportunity to integrate immersive experiences into ever-larger classes. However, many aspects of how immersive experiences can enrich and improve learning in place-based education are still not well understood. We present an empirical study, conducted in a large undergraduate ecology class, comparing students, that experienced an immersive virtual version of a field trip to a biological preserve as preparation for a later actual field trip to the site, with a control group that visited the real site but without having had the virtual experience. Within the virtual experience group, we also varied the quality of the headset. The VR field trip was well received for raising spatial awareness and also motivation and interest. Students ranked it higher than any traditional means with regard to achieving a high level of preparedness for the actual field trip. In contrast, no statistically significant evidence was found for differences in perceived learning outcome and enjoyment of the actual field trip. [ FROM AUTHOR] Copyright of Journal of Biological Education (Routledge) is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative.

OBJECTIVE: In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. MATERIALS AND METHODS: We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. RESULTS: Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. DISCUSSION: We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. CONCLUSION: By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.