As research teams analyzing after-college outcomes of students, we rely heavily on myriad data points to help us gauge how students fare after attending our institutions and how we can continuously improve. However, complex analyses are often the easy part – accessing the best data for the task at hand can be incredibly challenging or even impossible. Student-level data are disparate and scattered; in order to paint an accurate, holistic picture of student success, analysts must think outside the box and weave together the best datasets for their institutional and regional contexts, even if those datasets weren’t designed for education research.
In the session, presenters from the Research Institute at Dallas College will highlight the disparate datasets they synthesize in their analyses of long-term academic and workforce success, moving beyond the typical internal warehouses, state coordinating boards, and surveys to more creative realms like data integration systems (e.g., for business or politics) and social media scraping.
Founding Executive DirectorResearch Institute at Dallas College
