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Research

Geo-STEM learning ecosystems: A transdisciplinary theory-based framework to establish and engage communities in the geosciences

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Received 23 Dec 2022, Accepted 30 Apr 2024, Published online: 16 May 2024
 

Abstract

The geological sciences, technology, engineering, and mathematics (geo-STEM) have the capacity to investigate and address geological and environmental challenges. Many of these challenges (e.g., pollution, flooding, and slope failure) unjustly impact lower socio-economic communities in urban and rural settings where there is limited access to geo-STEM expertise. Geo-STEM learning ecosystems (GLEs) integrate geo-STEM and social science research paradigms to broaden civic engagement in the geosciences. GLEs are communities of practice consisting of geo-STEM professionals, educators, and learners who address local issues through place-based STEM research and education. The purpose of this study was to connect the concept of GLEs with the extant literature on learning ecosystems. We conducted a thematic review of the literature evaluating how the term “learning ecosystem” is used in psychology, educational technology, and STEM education research. We categorized the learning ecosystem components described in the literature in terms of inputs (e.g., motivation, software, learning environment), processes (e.g., cognition, device development, curriculum), and outputs (e.g., creativity, innovation, engagement). This approach revealed themes aligned with GLE-relevant research on communities of practice, and place-based and problem-based education, connecting GLEs to a century of existing research. To demonstrate how to use a GLE framework, we analyze the attributes of three existing programs through the GLE lens. Based on our findings, we recommend that to build GLEs geo-STEM researchers should: engage in transdisciplinary collaborations to develop local geo-STEM solutions, use the GLE framework to assess geoscience education and outreach programs, evaluate the role of place in efforts to engage diverse communities, and leverage other fields of inquiry to broaden our theoretical understanding of GLEs.

Acknowledgments

Cheryl Manning and Nicole LaDue would like to acknowledge financial support from Illinois Innovations Network. Cheryl Manning would also like to acknowledge financial support from the Rhoten A. Smith Assistantship Program at Northern Illinois University. The authors would also like to acknowledge collaborations with Critical Interface Network researchers, especially Praveen Kumar (University of Illinois Urbana-Champaign) and Sarah Fisher and Jen Young (formerly of the National Great Rivers Research and Education Center). We are grateful for manuscript feedback from M. Brandon Jones (National Science Foundation) and Douglas Lombardi (University of Maryland). Due to the theoretical nature of this work, no new data was used.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded by a grant from the Illinois Innovations Network.

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