Building a nationally representative sample of teachers' online and offline: the Public Instructional Network of School Resources

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.