*2.2. Broader Generalizability*

Big data can also facilitate opportunities for the cross-organizational analysis of educational functions, as many researchers have suggested that big data allows for greater generalizability so that other organizations can learn from each other, especially if these organizations serve similar populations in similar geographic areas [3,17].

For instance, Crossley specifically spoke about how data can be transferred internationally to allow educational research in one nation to inform the policies and practices of education in another nation. This can be an especially important technique for developing nations where human and financial resources are limited. As Crossley explained, "With references to my own work in Kenya and Tanzania ... carried out by African researchers, perhaps in partnership with international colleagues, has much to offer, if a greater proportion of educational reform initiatives are to be translated into successful practice" [17] (p. 22). In this instance, developing nations were able to learn from each other's big data and recapture limited human and financial resources related to big data capture and analysis.

Wang also spoke to the nature of big data as facilitating generalizability, as they argued that big data often informs educational policy through mass communication over websites and through social media. As an emerging form of big data, educational policymakers can now understand public sentiment and access trend-related data to best understand how students, teachers, and other stakeholders feel toward educational policies or identify educational inequities [3]. Wang argued that this form of big data allows for generalizability, as the internet and communication technologies allow many different stakeholders to have

a public-facing voice on issues facing educational institutions [3]. Although beyond the traditional student demographics and test scores to inform policy, Wang suggested that innovative and new forms of communication can allow for educational leaders to analyze big data to generalize public sentiment and inform educational policy toward equity [3].
