The study aim is to investigate how a combination of methods (such as data analysis, computational or quantitative methods) could be applied to gather CS projects information to support teacher’s practice and inspire them.
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The study aim is to investigate how a combination of methods (such as data analysis, computational or quantitative methods) could be applied to gather CS projects information to support teacher’s practice and inspire them.
Understanding what motivates people to take part in Citizen Science activities is important. While the reasons people give for getting involved vary greatly, research is starting to show interesting connections between the different drivers and demographics.
Engaging a wide range of participants over time, is key to the successful operation of citizen science projects. But how can projects accomplish this? The short and perhaps simplistic answer is “know your audience” – The whole range of potential audiences your project may have.
Examining the role of economic considerations in Citizen Science projects may yield some surprising conclusions, for example that those considerations may not be deemed by those involved in a project as important as could be expected. Greater attention seems to be paid to non-economic factors (e.g., educational gains).
Assessments of impact in citizen science projects are rarely linked to specific indicators like impact on policies. MICS have created an impact assessment framework which is being used to underpin a software development involving both handcrafting and machine learning
Research into Citizen Science projects in the field of environmental epidemiology highlights the need for more effort in sharing information about collaborative processes
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