Strategy and research are essential parts of strategic enrollment management (SEM), yet little information exists regarding how to use research and predictive analytics for effective strategy. It is often easier to react to what is happening in the moment, rather than be proactive in predicting the future or developing long-term plans. This…

An estimated 1,400 colleges and universities nationwide have invested in predictive analytics technology to identify which students are at risk of failing courses or dropping out, with spending estimated in the hundreds of millions of dollars. How accurate and stable are those predictions? The authors put six predictive models to the test to gain…

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students' learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped…

School violence research is often concerned with infrequently occurring events such as counts of the number of bullying incidents or fights a student may experience. Analyzing count data using ordinary least squares regression may produce improbable predicted values, and as a result of regression assumption violations, result in higher Type I…

Now that all 50 states and the District of Columbia are building statewide longitudinal data systems, the next step is to ensure that the information in these systems is used to improve student learning. The Data Quality Campaign (DQC) has identified 10 actions that states can take to ensure that the right data are available and accessible and…