The human and technological resources needed to ensure student success online are expensive to acquire and difficult to maintain. Consequently, institutions must make data-driven decisions about where to invest their resources. However, the data needed to inform such choices can be hard to isolate and are subject to misinterpretation given the complexities and constantly changing characteristics of online education.

Examine how you can use metrics to better support retention efforts and improve the success rates of your online students. This webcast will address the use of data for modeling and prediction, and evaluating the effectiveness of interventions, including:

• Data available to your institution
• Mechanisms for obtaining data
• Conclusions that can and cannot be drawn from data about your retention and success initiatives
• Identifying at-risk students through analysis of predictive behaviors
• Using interventions to help reduce the risks
• Monitoring the interventions for effectiveness