Building a nationally representative sample of teachers' online and offline: the Public Instructional Network of School Resources
JOURNAL OF RESEARCH ON TECHNOLOGY IN EDUCATION(2023)
摘要
The emerging big data allows educational studies to examine teaching and learning behaviors over time and at scale. Less available is population-representative big data. This paper builds the first nationally representative sample of teachers' online curation on a social media platform (i.e. Pinterest), the Public Instructional Network of School Resources (PINSR). This effort includes developing a big-rich data sampling framework, integrating social media data with administrative and census "ground truth" sources, and validating the population representativeness. Finally, we employ PINSR and present a worked example of teachers' social media curation behavioral patterns across regions and time.
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关键词
Educational big data,Pinterest,social media,teaching in social media,nationally representative sampling,bottom-up approach
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