The role of learning in citizen science
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Transcript of The role of learning in citizen science
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The role of learning in citizen science
Muki Haklay, Extreme Citizen Science groupDepartment of Geography, UCL
Twitter: @mhaklay / @ucl_excites
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• Typologies and goals in citizen science
• Aspects of learning and examples from contributory and collegial projects
• Learning in co-created projects at the Extreme Citizen Science group projects
Overview
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• Action oriented - encourage participant intervention in local concerns, using scientific research as a tool to support civic agendas.
• Conservation- support stewardship and natural resource management goals, primarily in the area of ecology.
• Investigation - focused on scientific research goals requiring data collection from the physical environment.
• Virtual - all project activities are ICT-mediated with no physical elements whatsoever.
• Education - education and outreach primary goals, all of which include relevant aspects of place.
Primary goals and physical environment
Wiggins & Crowston (2011). From conservation to crowdsourcing: A typology of citizen science. In System Sciences (HICSS)
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• Contractual - communities ask professional researchers to conduct a specific scientific investigation and report on the results;
• Contributory - generally designed by scientists and members of the public primarily contribute data;
• Collaborative - generally designed by scientists and members of the public contribute data, refine project design, analyse data, disseminate findings;
• Co-Created - designed by scientists and members of the public working together, some of the public participants are actively involved in most aspects of the research process; and
• Collegial - non-credentialed individuals conduct research independently with varying degrees of expected recognition by institutionalised science.
The 5 Cs classification
Shirk et al. (2012). Public participation in scientific research: a framework for deliberate design. Ecology and Society, 17(2).
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After Cooper, Dickinson, Phillips & Bonney (2007) Citizen Science as tool for conservation in residential ecosystems. Ecology and Society 12(2)
Question
Study Design
Data Collection
Data Analysis and
Interpretation
Understanding
results
Management Action
Geographic scope
of project
Nature of people
taking action
Research priority
Education priority
Traditional
Science
Scientific
Consulting*Contributory
Citizen
Science
Collaborative
Citizen
Science
Collegial
Citizen
Science /
Participatory
Action
Research
Variable Narrow NarrowBroad Broad
ManagersCommunity
Groups Managers IndividualsCommunity
Groups
Highest Medium High High Medium
Low Medium High High High
*often called Science Shops
Community Science
Co-created
Citizen
Science
Narrow
High
High
All
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√
√
√
√
√
√
√ √
√
√
√
√
√
√
√
√
√
√ √
√
√
√Public Scientists
√
√
√
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• Collaborative science – problem definition, data collection and analysisLevel 4 ‘Extreme’
• Participation in problem definition and data collection
Level 3 ‘Participatory
science’
• Citizens as basic interpreters Level 2 ‘Distributed intelligence’
• Citizens as sensors Level 1 ‘Crowdsourcing’
Haklay (2013). Citizen Science and volunteered geographic information: Overview and typology of participation, Crowdsourcing Geographic Knowledge
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• Analysing:– Environment (physical/online), – Technology (web/mobile/pen & paper), – Engagement (levels of control over the project), and– Relationships with professional science
• Aspects of learning and creativity are not explicit
Core typologies of citizen science
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Citizen Science
Awareness to environmental
or scientific issue
Producing scientific outputs
Achieving temporal and geographical
coverage
Achieving inclusiveness
Increasing scientific literacy
Accessing resources
Creating enjoyable & engaging
experiences
Balancing Citizen Science goals
• Each citizen science project is a balancing act between the scientific goals, scale and depth of engagement, benefits to different stakeholders (scientists, participants, project funders)
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• Who is learning and what are they learning?
• Is the learning aspects designed into the project?
• Which goals are addressed through the learning process and tools?
• Is the learning evaluated and inform the project? How?
Some questions on learning
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1. Task/game mechanics
2. Pattern recognition
3. On topic learning
5. Off topic knowledgeand skills
4. Scientific process
6. Personal development
Participationas volunteer
Source: Laure Kloetzer, University of Geneva
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A taxonomy on learning outcomes in citizen science projects. 3 mains categories:
1. personal development, 2. generic knowledge &
skills, 3. project-specific
knowledge and skills
Source: Laure Kloetzer, University of Geneva
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Bioblitz etc.
Participating in Big Garden
Bridwatch (source: RSPB)
Participating in BioBlitz (source: OPAL, Esri)
Kerski. (2016) Mapping BioBlitz Field Data in ArcGIS Online Esri GIS Education Community Blog
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• Community Collaborative Rain, Hail & Snow Network
Rebecca Jacobson
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Volunteer computing
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Volunteer thinking
Hanny van Arkel. “The Dutch schoolteacher and Queen admirer who discovered Hanny’s Voorwerp”.
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• Data collection process and protocols • Details about the issues (e.g. bird feeding in winter)• Organisational skills• Familiarity with systems and procedures
(CoCoRHaS)• New patterns or discoveries
Learning in contributory projects
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DIY Sensing
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More information at http://publiclaboratory.org
DIY/Civic Science
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• New tools and social learning (sensors development)
• Problem solving skills• Issue specific (what is being measured and how)• Organisational skills• Communication and political action
Learning in collegial projects
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Regalado. (2017) Unwrapping DIY enquiry: The study of ‘enquiry’ in DIY practice at individual, community & place levels, PhD Thesis UCL
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• Most of the focus is on the participants – what they learn and how
• Little research on the scientists:– Shirk, J. (2014) Push The Edge Of Science Forward.
Expanding Considerations Of Expertise Through Scientists' Citizen Science Work In Conservation, PhD dissertation, Cornell University
Issues with learning
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Extreme Citizen Science (ExCiteS) is a situated, bottom-up practice that takes into account local needs, practices and culture and works with broad networks of people to design and build new devices and knowledge creation processes that can transform the world.
Creating technologies that are designed to be embedded within participatory processes.
Extreme Citizen Science
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Pepys estate air quality study
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Diffusion Tubes Pros Cons
Comparable to Local Authority data Not real time
Only need a step ladder and diffusion
tube
Active involvement
Easy to use Measurement in one location
Uses local knowledge
Low cost
Inclusive
Integrates with mobile apps to record
location & other details
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Widely distributed press release targeted at politicians and media
Follow-up with Wandsworth Council, TfL and Mayor’s Office
Key achievement: persuading TfL to introduce hybrid and retrofitted buses
Putney: Air Quality Monitoring outcome
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Ellul, Francis, and Haklay (2012), Engaging with local communities: A review of three years of community mapping. Urban and Regional Data Management, UDMS Annual
2011 - Proceedings of the Urban Data Management Society Symposium
Exploring the results
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• Identifying the most suitable tools (diffusion tubes)
• Identifying the role of technology and mapping in documenting the activities and sharing the results
• Using both local knowledge and scientific knowledge
Community & researchers learning
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Source: Mapping for ChangeEveryAware website at http://www.everyaware.eu
Participatory Sensing
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• Sharing limitations and potential application of monitoring
• Developing representations that express community view and wishes for utilisation of the information
• Developing new initiatives – progressing from contributory, through co-design, to collegial
Community & researchers learning
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Earthquake preparedness
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• Different types of communities: community of practice, interest, and place
• Adapting tools and activities to different life stages and shared priorities – mutual learning
• Development of general training and learning resource
Community & researchers learning
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64M UK population
8.5M BBC Attenborough & the Giant Dinosaur
520,000 in RSPB Big Garden Birdwatch
40,000 in British Trust of Ornithology surveys
500 in BioHacking & DIY Science
60,000 in Oxford ClimatePrediction.net
UK Engagement Escalator
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General interest in popular science
Science blog reader + Galaxy Zoo classifier
Galaxy Zoo forum moderator
Community manager ExCiteS
Citizen science research
Galaxy Zoo / citizen science ambassador
...as well as Alice’s journey
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Everyone
Consumption of science (passive/active)
Opportunistic or highly limited participation
Data collection and analysis
High engagement in DIY science
Joining volunteer computing or thinking
7 Levels of Engagement
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• Learning is integral to citizen science
• It happen at all modes of citizen science, though in different ways and in different areas
• There is a need to pay attention to the learning by those who run and develop citizen science and not only the participant
Summary
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• New course: Introduction to Citizen Science and Scientific Crowdsourcing
• Part of OPENER and DITOs projects
• MOOC + face to face course at UCL, aimed at MSc students and practitioners
Coming in January 2018
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Follow us:– http://www.ucl.ac.uk/excites– Twitter: @UCL_ExCiteS– Blog:
http://uclexcites.wordpress.com
The work of ExCiteS is supported by EPSRC, ERC, EU FP7, EU H2020, RGS, Esri, Forest People Program, Forests Monitor, WRI and all the people in communities that we’ve worked with over the years