My dissertation abstract

Training citizen scientists: A qualitative, comparative, multiple case study to identify theoretical and instructional design themes in current citizen science training initiatives

Abstract

This dissertation inquiry investigates citizen science training and its perceived effectiveness.  Citizen scientists are volunteers who participate in scientific activities under the guidance of professional scientists and organizations.  The work of citizen scientists greatly expands the data collection possibilities in natural resource management and increases science literacy among participants and their social communities.  Citizen scientists are increasingly important to the on-going assessment of ecological restoration, species identification, and monitoring on natural lands.  The general problem is data collected by citizen scientists is often viewed as unreliable by the scientists and land managers who might use it.  The specific problem is the absence of educational training measurement in citizen science program design and analysis with which to ascertain the learning gains of trained citizen scientists.  To address this problem, this dissertation lays the observational groundwork for developing training themes in citizen science that may lead to improved training programs for citizen scientists and improved data collection procedures.

For this qualitative multiple case study research design, organizational users of the CitSci.org database, based anywhere in the world, who task citizen scientists with field-based ecological data collection will comprise a purposive sample for this investigation.  This sequential investigation includes case identification, training document analysis, an organizational survey, and follow-up semi-structured interviews with training leaders to identify theoretical and instructional design themes in current citizen science training initiatives.

Key words: citizen science, informal science education, public participation in scientific research, training, data reliability

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