Building community with rural and underrepresented groups has been a challenge in the field of citizen science. At the University of Alaska Fairbanks, a team of scientists, educators, Extension professionals, and evaluators have joined efforts to take on this challenge across Alaska. The goals for Arctic Harvest-Public Participation in Scientific Research are to: 1) investigate how shifts in environmental conditions affect the fate of subsistence berries and timing of berry loss from plants in fall and winter across Alaska; and 2) improve the participation in and effectiveness of citizen science across diverse audiences, particularly at high latitudes where a high proportion of communities have populations underrepresented in STEM. We present the assets that collaboration across a land grant university brought to the table, and the Winterberry Citizen Science program design elements we have developed to engage our 1080+ volunteer berry citizen scientists ages three through elder across urban and rural, Indigenous and non-Indigenous, and formal and informal learning settings. Our interdisciplinary team developed and implemented a program that provides in-person or online support for berry monitoring and data collection, and accommodates different age levels and settings. We also developed and tested an innovative program model that weaves storytelling throughout the citizen science learning cycle, from berries stories from the larger community, to stories of the citizen science process, to stories developed from berry data being collected and applied to future scenarios in a changing climate. The variety of program modifications we created have been highly effective helping reach a variety of settings and age levels. In both informal and formal learning environments in our first two years of the program we have had 568 pre-K and elementary-aged (age 3-12), 424 secondary-aged (age 12-18) youth participants and 107 adults (ages 18+), with 44% of participants coming from groups underrepresented in STEM, and 100% of groups completing berry monitoring throughout the fall. These results highlight the importance of designing the citizen science program with cultural relevance, program delivery options, and relationships between participants and scientists, while remaining committed to making a substantial scientific contribution.
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The Village: Infrastructuring Community-based Mentoring to Support Adults Experiencing Poverty
Mentorship and other social and relational support have been vital to poverty alleviation and transformative change. It is crucial to understand the underlying factors in the success of mentoring models and subsequent programs to support them. Thus, we conducted a mixed-methods study consisting of longitudinal surveys of community participants followed by semi-structured interviews with 28 community members, eight mentors, and two coaches participating in a community-based mentorship program. Drawing from community-based participatory research in partnership with a non-profit located in a Midwestern United States (U.S.) city, we unpack how the program supported self-sufficiency and economic mobility among adults experiencing financial hardships. Through an infrastructural lens, we attend to individuals’ infrastructuring work in social support, flexibility, and trust to support a “village” model of community-based mentorship. Our results show how the village model differs from traditional mentorship models that assume dyadic, one-to-one, often didactic, and hierarchical relationships (e.g., expert and protégé, adult and child) and are used primarily in the workplace and educational settings. The village mentorship model advocates for less hierarchical and more balanced relationships in non-institutional settings and flexible communication and technological needs. We discuss new research opportunities and design strategies for rethinking technology-mediated mentorship to support poverty-stricken adults in the U.S.
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- Award ID(s):
- 1901171
- NSF-PAR ID:
- 10346600
- Date Published:
- Journal Name:
- CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1 to 17
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3491102.3501949
