*3.6. Turnover and Continuity*

Big data collection and analysis may be computerized and automated by developed nations or individual wealthy schools, but for many developing nations, the business of big data is human intensive. This context requires consistent and highly skilled staff to gather and analyze data toward educational equity, with human beings able to understand nuanced educational inequities and paths toward remediating those inequities [14]. However, education has remained one of the fields with the highest turnover of personnel [10,18,25], meaning that the humanistic nature of big data collection and analysis is inherently inconsistent and continuously disrupted by teacher and administrator turnover at the primary, secondary, and post-secondary levels [14].

Macfadyen et al. outlined the unique problems facing the field of education because of leadership change, as educational organizations often adjust goals and strategic plans to align with new leadership, which implies that the collection and analysis of data is also likely to experience constant change toward new initiatives and future efficiencies [18]. Nguyen et al. echoed this sentiment, stating that teacher turnover often upsets data collection and analysis techniques, especially as teachers and administrators strive to meet accountability measures, whether at the regional or national level [25]. Often, individual schools must invest a considerable amount of human and financial capital to replace teachers, which then introduces new educational staff into a system and a potentially nuanced way of gathering individual student data [14].

Kraft et al.'s work suggested that teacher turnover was tied to student achievement data, also suggesting that as teachers leave the classroom, districts and school systems must track this teacher turnover and integrate this variable into big data sets to sufficiently control for this phenomenon and maintain the integrity of data-informed analyses [10]. Overall, research suggests that data collection and analysis is inherently humanistic, and teacher and administrator turnover at the primary, secondary, and postsecondary levels introduce changing variables (humans) into a complex system of big data, working against educational progress toward equity [5,7,25].
