*3.3. Collaborative Conglomeration Efforts*

Independent researchers have also begun to integrate single-year datasets from organizations such as the OECD to compile large, longitudinal educational datasets to inform how policies and other administrative mechanisms influence the field of education over time. Barro and Lee (2013) have repeatedly conglomerated UNESCO data to compile a large educational dataset from 1950 until 2010 across 146 countries, disaggregated by sex and at five-year intervals [26]. Because of their conglomeration efforts, the researchers were able to use the data to evaluate how human capital is produced through years of schooling and the compositional education attainment of citizens. In all, the researchers found that schooling has a direct and positive impact on human capital development, and after controlling for other factors, the researchers also found that individual rate-of-return for one additional year of school was between 5 and 12% per individual [26].

At the country level, Moore's (2022) evaluation of state-level data from two Indian states [27] and Bo et al.'s (2019) use of administrative data from China also serve as evidence that conglomerated educational datasets can drive empirical inquiry and inform policy change toward equity [28]. Moore (2022) combined datasets from two state-level datasets in India to reveal that there were large school-level effects in terms of student performance, suggesting that India's state-level datasets could reveal state-to-state stratification that could inform Indian education policy [27]. Similarly, Bo et al. (2019) analyzed an administrative dataset from each of China's postsecondary institutions, exploring how standardized test scores predict how students find an academic match with their institution [28]. The researchers learned that Chinese college students would reduce their probability of mismatch by 18% if they were allowed to submit their college preferences after learning their standardized test scores and not before [28]. Again, by accessing a large, national dataset in a postsecondary context, researchers were able to evaluate college matches and potentially inform national policy related to college admissions and student choice.

In 2021, State of California (USA) legislation approved funding to create a comprehensive suite called the California Cradle-to-Career Data System. This system would merge previously disconnected data systems from schools, colleges, social services agencies, financial aid providers, and employers [29]. Streamlining these data systems will allow various stakeholders to easily access information, resources, and data [30]. By using the California Cradle-to-Career Data System, students and families will be able to access pertinent information about college opportunities and other social services (e.g., medical care) in addition to formally applying to colleges and financial aid. Educators, on the other hand, will have a centralized platform to monitor the progress and completion of college and financial aid applications. This is essential to building equity because it gives educators the ability to provide targeted support to under-resourced areas or specific communities of people. Lastly, for policymakers, researchers, and advocates, this comprehensive system will provide longitudinal student and employment outcome data that will allow them to see trends and inform potential interventions [31]. While still in its planning stage, the Cradleto-Career Data System provides a glimpse into the future in terms of how multiple data systems across sectors can be streamlined into one cross-sector data system that provides information and data to various stakeholders to promote equity and inform change.
