Signals in the Noise: Maximize Student Engagement with Data 

With enrollment numbers shrinking, institutions need to maximize student engagement at every point in their college journey, from application to retention and all the way through to graduation. When collected, connected and activated through data enablement, the wealth of data generated by higher education systems can answer some of the school’s most pressing questions.

Standard reports and common metrics keep school leaders aware of known issues, but there may be more to learn. Anomalies in data can be informative and predictive. Your data may already be hiding useful behavioral triggers and anomaly signals that can help you deliver highly supportive and proactive student engagement.

Anomaly and Signal Detection

Anomaly detection is the process of identifying unexpected results in data sets, ones that differ from the norm. A change in a metric could be innocuous, represent an opportunity, or offer advance notice of a negative outcome.

Schools can leverage the data that is already available in their systems via platforms like Google Cloud that use microservices to enable data-driven insights such as detecting anomalies in student behavior. By being alerted to these behaviors and patterns, school leaders can determine which are insignificant changes and which demand action.

Examples of Data Discovery in Action

Successfully guiding new students through the admissions and enrollment process is a mission-critical activity for schools. What if there was a way to identify the likelihood of a prospect filling out an inquiry form and converting to an enrollee? By identifying those who may be considering other options but could be persuaded to engage, a school can create automated outreach campaigns that save time for staff while also ensuring purposeful communication.

Student retention is becoming another crucial strategy for mitigating the impacts of downward enrollment trends. What if there was a way to calculate the probability of a student transferring out or failing to return next semester? Proactive alerting microservices can identify students who are at risk of not continuing their studies and push these alerts directly to decision makers.

Such notifications are an important aspect of data discovery. Anomalies and important behavioral signals shouldn’t be buried in a dashboard or static report, especially when student persistence is at stake. Rather, once a school detects that a student is struggling, faculty and staff should be alerted so they can intervene before it’s too late and initiate automated processes and outreach.

Hear Everything Your Data Is Saying

Enabling the data already residing in school systems, apps and platforms for data discovery can inform focused and timely interventions throughout the student journey. In addition, anomaly and signal detection can save a massive amount of time for faculty and advisors. Instead of spending their time trying to identify at-risk students, faculty can use information provided at the critical time to make a difference.

Collegis gives colleges and universities the tools to leverage data across the entire institution for data discovery. Empowering faculty and staff with the insights they need to ensure student persistence and success is just one of the benefits it delivers.

Begin the journey of discovery with Collegis.

This article is part of a series covering data enablement’s capabilities. Read the previous or next installment.