Citizen Science Research Design and Methods
Citizen Science Research Design and Methods introduces learners to various citizen science methodologies and
helps them determine the right fit for their research projects. The module
covers examples from data collection initiatives like eBird to data processing
platforms like Galaxy Zoo, demonstrating citizen science’s versatility. It
includes a decision framework to aid researchers in assessing whether citizen
science suits their project goals, considering the motivations and
participation levels of potential volunteers. An interactive component enables
learners to apply this framework to their ideas, fostering a deep
understanding of citizen science integration into research. The module
culminates with reflections on these insights, solidifying the learners'
capacity to implement citizen science methodologies effectively.
1. Citizen Science Methodologies
This module educates learners on the diverse methodologies
within citizen science, using terminology and real-world examples to illustrate
these concepts. By exploring case studies like eBird for data collection and
Galaxy Zoo for data processing, the module showcases the impact and breadth of
citizen science projects. It culminates by providing an overview of various
citizen science approaches, including crowdsourcing, curriculum-based projects,
and community science, to equip learners with the knowledge to apply these
methods in their work.
Module description:
|
What? |
How? |
Why? |
|
Introduction to CS |
Explaining how we are going to cover the topic of citizen science research methodologies through examples of different types of citizen science projects |
Explaining to the learner why it is worth following the course |
|
Example one - eBird (data collection) |
The story of eBird and how it became the world’s largest biodiversity-related science projects, with more than 100 million bird sightings contributed annually by eBirders around the world and an average participation growth rate of approximately 20% year on year |
Demonstration of what can be achieved with crowdsourcing of data collection |
|
Example two – Galaxy Zoo and Zooniverse (data processing) |
The story of Galaxy Zoo and how it has mobilised volunteers to perform millions of classifications of galaxies and resulted in over 450 publications |
Demonstration of what can be achieved with crowdsourcing of data processing |
|
Example three - FoldIt (data processing through gamification) |
The story of FoldIt and how players have contributed to advanced research on human health, cutting-edge bioengineering, and the inner workings of biology |
Demonstration of what can be achieved with curriculum-based citizen science projects |
|
Example four - the Give Youth a Voice project and the Mass Experiment in Denmark |
The story of two projects in Denmark – one about mental health and young people and one about plastic pollution involving 57.000 school children |
Demonstration of what can be achieved with citizen science projects that involve young people/school children |
|
Overview of citizen science methodologies and what they accomplish: crowdsourcing (data collection and/or data processing), curriculum-based projects, and community science |
Bringing the stories together and elaborating on key terms for citizen science methodology: crowdsourcing and volunteered thinking/computing (data collection and/or data processing), curriculum-based citizen science (formal and informal science education), and community science |
Helping participants to organise information about individual examples and enabling them to use relevant terminology |
Overview slide (available in the slide deck):
