Dataset DOI: 10.5061/dryad.2rbnzs836

Description of the data and file structure

In these data and the accompanying article, we, a cohort of eight graduate students with the United States Geological Survey Southwest Climate Adaptation Science Center 2022 - 2023 Natural Resource Workforce Development Fellowship, reflect on our experience learning and using community science skills as an interdisciplinary team through the lens of an experiential learning research project. As part of our fellowship, we conducted a post-fellowship survey to better understand if we, as a cohort of graduate students, gained or improved upon a set of skills necessary for community and co-produced science. The survey also included questions regarding challenges we anticipated (at the beginning of the fellowship) compared to the challenges we actually faced throughout the fellowship. The skills and challenges were adapted from Goolsby et al. (2023). The survey was created by the fellows and completed by seven of the eight fellows. The survey included five multiple choice questions and eight open-ended questions. The open-ended questions have been de-identified for publication. 

The 18 skills listed in Goolsby et al. (2023) fall within three categories: cognitive, interpersonal, and intrapersonal. Definitions for each of these skills (as defined by Goolsby et al. (2023)) are included in the supplemental material of the accompanying manuscript (Table S1). These skills are identified as necessary to build community science expertise and are coupled with 20 community science challenges (Goolsby et a1., 2023). Three additional challenges were added by the fellows to gain a better understanding of specific challenges that fall within two broad challenges identified in Goolsby et al. 20230. 

Goolsby, J., Cravens, A., & Rozance, M. (2023). Becoming an actionable scientist: Challenges, competency, and the development of expertise. Environmental Management, 72(6), 1128–1145. https://doi.org/10.1007/s00267-023-01863-4

Files and variables

File: Community_Science_Skills_Learned__McClure_et_al_2025_V2.xlsx

Description: Results from an internal survey created by eight graduate students who participated in a year-long fellowship on learning and implementing community and co-produced science. Seven of the eight graduate student fellows completed the survey. Of the eight graduate students in the fellowship program, six are co-authors on the accompanying manuscript, while two opted out of authorship on the manuscript. 

Tabs

Summary: The summary tab includes all questions included in the survey, broken into two categories: Multiple Choice Questions and Open-Ended Questions

Q1-Q5: Summary results from each of the multiple choice questions.

Variables

• Totals: Within each question tab 'total' represents the number of graduate students that reported gained or improving upon that skill, or facing that challenge. 

References

Goolsby, J., Cravens, A., & Rozance, M. (2023). Becoming an actionable scientist: Challenges, competency, and the development of expertise. Environmental Management, 72(6), 1128–1145. https://doi.org/10.1007/s00267-023-01863-4

Code/software

Microsoft Excel 

Access information

Other publicly accessible locations of the data:

• None

Data was derived from the following sources:

• None

Questions in the survey were adapted from:

Goolsby, J., Cravens, A., & Rozance, M. (2023). Becoming an actionable scientist: Challenges, competency, and the development of expertise. Environmental Management, 72(6), 1128–1145. https://doi.org/10.1007/s00267-023-01863-4

Human subjects data

There was no identifiable information collected for this survey. All results are from an internal survey (i.e., generated by and answered by the fellowship participants who are all authors on this paper) on an experience participating in a graduate student fellowship. Results from the survey include answers to multiple choice and open-ended questions. For the open-ended questions, any names that were mentioned have been removed. There is no other identifiable information included in these data.