The CS Track team has released a new report entitled Models to identify background factors associated with the CS activity. It introduces how the CS Track team created 6 models with the aim of developing a deeper understanding of how different factors (e.g. gender, age, roles in CS) are associated with different forms of participation in CS activities.
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The COVID-19 pandemic exposed an opportunity to improve the outcomes of citizen science in response to emerging challenges.
How do citizen science activities develop and work? Computational analysis techniques can help us find out
A cornerstone of the CS Track project’s approach to investigating how citizen science (CS) activities develop and work is the use of computational analysis techniques applied to digital sources and traces to characterise and analyse these activities in terms of interactions within certain projects, the interplay with “official” science and their interaction with society.
Identifying who takes part in citizen science projects and understanding what motivates them are key aspects in building our understanding of citizen science. These aspects are at the heart of a recent White Paper published by the CS Track project which highlights interest in the theme, contributing to scientific research and opportunities to learn as key factors when it comes to motivation.
Citizen Science is changing and evolving as highlighted in the recent CS Track White Paper on Themes, Objectives and Participants. This white paper draws on the initial results of a large scale CS Track survey carried out in early 2021 which highlights an increasing use of technology, diversification in terms of themes and a re-assessment of the value that citizen science can bring to the individual as well as society as a whole.
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