Learning and the transformative potential of citizen science. Issue 5 (24th June 2016)

• Record Type: Journal Article
• Authors: Bela, Györgyi; Peltola, Taru; Young, Juliette C.; Balázs, Bálint; Arpin, Isabelle; Pataki, György; Hauck, Jennifer; Kelemen, Eszter; Kopperoinen, Leena; Van Herzele, Ann; Keune, Hans; Hecker, Susanne; Suškevičs, Monika; Roy, Helen E.; Itkonen, Pekka; Külvik, Mart; László, Miklós; Basnou, Corina; Pino, Joan; Bonn, Aletta
• Is Part Of: Conservation biology. Volume 30:Issue 5(2016:Oct.)
• Page Start: 990
• Page End: 999
• Publication Date: 2016-06-24
• Subjects: biodiversity -- collaborative assessment -- participation -- science–society–policy interactions -- transformative learning -- aprendizaje transformador -- biodiversidad -- interacciones -- participación -- política ciencia‐sociedad -- valoración colaborativa; Conservation biology -- Periodicals; 333.9516
• DOI: 10.1111/cobi.12762
• Languages: English
• ISSNs: 0888-8892

Abstract

Abstract: The number of collaborative initiatives between scientists and volunteers (i.e., citizen science) is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS) in the policy domain. We examined the transformative capacity of citizen science in particular learning through environmental CS as conservation tool. We reviewed the CS and social‐learning literature and examined 14 conservation projects across Europe that involved collaborative CS. We also developed a template that can be used to explore learning arrangements (i.e., learning events and materials) in CS projects and to explain how the desired outcomes can be achieved through CS learning. We found that recent studies aiming to define CS for analytical purposes often fail to improve the conceptual clarity of CS; CS programs may have transformative potential, especially for the development of individual skills, but such transformation is not necessarily occurring at the organizational and institutional levels; empirical evidence on simple learning outcomes, but the assertion of transformative effects of CS learning is often based on assumptions rather than empirical observation; and it is unanimous that learning in CS is considered important, but in practice it often goes unreported or unevaluated. In conclusion, we point to the need for reliable and transparent measurement of transformative effects for democratization of knowledge production.