*2.3. Accountability and Measurement*

Many regions and developing nations often lean on big data for accountability and measurement purposes [6,13]. At the higher education level, Macfadyen et al. reasoned that, "in the complex systems of higher education, current performance assessment and accountability policies may be the forces driving the continued focus on high–stakes testing as a means of producing comparative institutional data, despite the well–articulated weakness of such an approach for understanding student learning" [18] (p. 18). Here, although the authors point to perhaps an over-reliance on big data, many institutions of higher education often tie big data to assessment and accountability policies, for better or worse.

Likewise, Schildkamp et al. reasoned that big data allows teachers and administrators to review and confirm that they are measuring student learning, tying that learning to educational objectives and measurements, and demonstrating accountability to local, state, or national mandates and policies, many of which may be tied to important sources of educational funding [13]. Big data also gives teachers and administrators insight into current practices to improve their accountability toward educational policies, in turn allowing for educational leaders to provide educational interventions for students and support services for educators to improve the overall education system [13]. For instance, Kraft et al. analyzed administrative data from New York City school districts to learn that school safety and academic expectations were associated with lower levels of teacher turnover and higher levels of student achievement, suggesting that individual school data may be nuanced, but when combined with larger data sets, policy decisions can be made easier and in more generalizable terms [10]. These authors all emphasize the point that educational leaders need to first have well-defined goals and data available to track progress toward those goals, rendering it incredibly important for educational leaders to either be adept data managers and analysts, or to employ a team who can perform data management and analysis tasks to inform leadership [10,13].

#### *2.4. Strategic Budget Allocation*

Schildkamp et al. focused on how big data and data-driven decision-making can also inform budgetary decisions, especially on a large scale. As many national governments often disseminate resources from the national level to the regional or local level, it is critical that governments and school districts access data and explore equity gaps to disseminate funds and improve schools and communities in low-income areas [13]. Studies related to teacher turnover have found that some school districts may need to allocate budgetary resources to recruit and retain high-quality teachers, an insight only gleaned from the analysis of a large administrative data set in one of the most populous cities in the world, New York [10].

Additionally, the European Commission also gathers data from many E.U. member nations to inform how developed and developing nations can allocate budgetary resources to provide educational interventions for teachers and students, as well as understand where education systems need to be developed in both populous urban areas or rural areas [9]. Of the European Commission's strategic goals, E.U. member nations have shared data to arrive at literacy goals in primary and secondary schools and post-secondary achievement goals that have allowed individual institutions and nations to strategically allocate funds to support those initiatives [9]. Crossley's transnational work also speaks to the European Commission, as many E.U. member nations have seen the benefit of big data sharing agreements to better allocate financial resources and improve student outcomes at multiple levels [17].

#### **3. Drawbacks of Big Data in Education**

As there are countless benefits to capturing and analyzing big data and the educational context, developing nations should be particularly concerned with the many drawbacks with regard to big data and education. As many developing nations have limited resources, both human and financial, it is critical to understand the type and sculpt of big data that would best serve a particular region or an entire developing nation. As many big data initiatives take years or decades to launch, developing nations should heed these warnings as they relate to big data and educational decision-making.
