This article details a correction to: Craig, A., Panda, N., Palapu, R., Oku, G., Lifoia, C., Tatalu, J., Beebe, N., Kelly, G., Kama Jr, N., Iro’ofa, C. and Bugoro, H. (2024) ‘Citizen Science for Enhanced Dengue Vector Surveillance in Solomon Islands: A Methods Paper’, Citizen Science: Theory and Practice, 9(1), p. 3. DOI: https://doi.org/10.5334/cstp.679
Schools are important places for citizen science (CS) as they can be valuable in ensuring that participation better represents the broader population, and they provide opportunities for students to experience authentic science practices. We present results from a study in eight Hong Kong schools with 187 secondary students (ages 11–19) who participated in CS activities in the 2020–2021 academic year. An adapted behaviour psychology framework underpinned the construction of the survey instrument, and a pretest-posttest research design was used to examine the effects of environmental CS activities on student values, attitudes, knowledge, and behaviours. We find that short one-time experiences of nature-based environmental CS projects have a small positive effect on knowledge, and the frequency and range of pro-environmental behaviours, while also having a small negative effect on preservation values and confidence in one’s self-efficacy. After CS project experiences, the environmental behaviour psychology factors that most influence pro-environmental behaviours are: (i) time in nature and environmental centres, (ii) nature preservation values, (iii) household environmental actions, (iv) exposure to positive news about environmental actions, and (v) values about nature as a resource. We argue that providing opportunities for students to engage in nature-based citizen science-embedded experiential education can lead to greater frequency and range of pro-environmental actions. We share practical implications for educators and CS project organisers who want to apply citizen science approaches as part of their school environmental education programme.
Online archives host millions of scanned historical documents. However, images of old handwriting remain unsearchable and largely inaccessible without transcription. These limitations can now be mitigated by advances in Handwritten Text Recognition (HTR), which uses machine learning to convert images of handwriting into text data. In the HTR and Citizen Humanities project The Detective Section, the Swedish National Archives invited volunteers to build and refine a large, high-quality training dataset for an HTR application. This qualitative interview study explores how participants in The Detective Section perceived their involvement in the project in terms of learning and knowledge development. By applying a typology for understanding multifaceted learning and drawing on conceptual resources from science and technology studies (STS), the study highlights how participants perceived themselves as developing into epistemic subjects within an epistemic culture. We found that participants learn both individually and collectively, often in unexpected ways, through and beyond predefined goals and protocols. Their strong emotional investment and interest in local history leads to additional activities, which in turn result in more accurate transcriptions. We conclude by discussing refinements to participatory practices within the GLAM sector that can support volunteer learning and help democratize access to archival collections.
Marine litter (ML) citizen science projects are widespread. Many of these projects are contributory in design, involving participants collecting data for the primary benefit of the scientist. Participant benefits are underexplored. This work provides a qualitative exploration of participant experiences in and outcomes from a collaborative and place-based ML citizen science project called Coast Watchers in North West England. The collaborative citizen approach enabled participant input in most stages of the citizen science research process, including project design, question identification, method development, and data collection. Post-project interviews to qualitatively explore participant experiences in ML citizen science surveys highlighted positive outcomes, including increased awareness of litter types and amounts, changed pre-conceptions that beach users are the main source of litter, and heightened environmental consciousness. However, many participants did not identify as citizen scientists. The work demonstrates the range of participant-focussed outcomes that citizen science can achieve beyond its traditional focus on data collection, and argues for further research to explore how citizen science projects can be designed effectively to maximise participant outcomes.
