<p> This dissertation characterized trainings designed to prepare citizen scientists to collect ecological data in natural outdoor settings. 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. The general problem is that some scientists and land managers view the data collected by citizen scientists as unreliable. 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. </p><p> Through a sequenced methodology of data analysis, survey, and semi-structured interviews, deductive descriptors and codes guided a directed content analysis of data collected. The analysis indicated strong alignment between citizen science, andragogy, and social learning theory. The sample revealed a bimodal distribution related to the type of data collected and the subsequent training design. Little training existed when data collection involved photography only. Citizen scientists brought prior skills to the task but did not need to gain new procedural learning to complete their data collection task. When citizen scientists collected more complex measurements, classroom and field mentoring facilitated learning. </p><p> Citizen science leaders described their perception of the reliability of their citizen scientists’ data collection efforts. Computer technologies validated photo and water quality data. Therefore, quantitative data analysis supported the perception of data reliability. Terrestrial data had a range of reliability qualifications including video and paper quizzing, field observation of methods implemented, periodic data checks, and follow-up mentoring when data quality was poor. Managers of terrestrial citizen science programs were confident in the reliability of the data for the land management, policy, and research applications required.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:13423764 |
| Date | 22 December 2018 |
| Creators | Gaddis, Margaret L. |
| Publisher | The University of the Rockies |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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