Leveraging public data to offer online inquiry opportunities

Research output: Contribution to journalArticlepeer-review

Abstract

Inquiry activities have become increasingly common in Ecology and Evolution courses, but the rapid shift to remote instruction for many faculty members in response to the COVID-19 pandemic has created new challenges for maintaining these student-centered activities in a distance learning format. Moving forward, many instructors will be asked to create flexible course structures that allow for a mix of different teaching modalities and will be looking for resources to support student inquiry in both online and in-person settings. Here, we propose the use of data-driven inquiry activities as a flexible option for offering students experiences to build career-relevant skills and learn fundamental ecological concepts. We share lessons learned from our experiences teaching a two-semester course-based research experience in global change ecology that leverages publicly available datasets to engage students in broadly relevant scientific inquiry.

Original languageEnglish (US)
Pages (from-to)12555-12560
Number of pages6
JournalEcology and Evolution
Volume10
Issue number22
DOIs
StatePublished - Nov 2020

Bibliographical note

Funding Information:
We would like to thank the numerous students and teaching assistants that have helped us revise the global change ecology course over the past 3?years. In particular, we would like to acknowledge Tonya Ward for helping to develop the assignment in Appendix S4. We would also like to acknowledge the 4 teaching assistants from Spring 2020; Janine Mistrick, Mallorie Lynn, Mara DeMers, and Jennifer Hamann for their willingness to work under a high degree of uncertainty and quickly adjust to support their students. This work was supported in part by a National Science Foundation IUSE grant (Integrated Science Education for Discovery in Introductory Biology, proposal no. 1432414), awarded to S.C. and C.K., Department of Biology Teaching and Learning, University of Minnesota. Any opinions, findings, conclusions, and recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Keywords

  • data-driven inquiry
  • distance learning
  • global change ecology
  • remote instruction

PubMed: MeSH publication types

  • Journal Article

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