LoudSight Product Website

LoudSight is a predictive analytics tool with early alert functionality. The platform collects information from different systems across campus, runs that information through a predictive model, and produces a daily risk score for each class in which students are enrolled. Faculty and advisors can identify which students are struggling, in which class, down to the learning objective.

A dashboard displays a faculty or advisor’s caseload and identifies which students are most at risk for failing a particular class across their course load. Faculty and advisors can dive into a student’s profile and see the student’s risk score, composed of in-class participation and performance as well as cohort data—measures that are benchmarked against other students in each class. They are able to see which factors significantly contribute to the risk score each day, and can use that information to gauge where a student might need help and what intervention might be most useful. Advisors can set up automatic messages to be delivered when a student’s risk score moves beyond a certain threshold or send customized messages with recommended interventions. Participation, performance and cohort indicators vary by institution, so each institution has a custom predictive model. Different roles have different access to the data.

Features for Student Success:

• Flags at-risk students
• Builds custom predictive model for each class across a student’s course load
• Daily risk score
• Customized messaging and automated nudges
• API-based integrations 

Implementation:

• Time to go Live: Implementation takes about 2-4 months which involves conversations with stakeholders to understand their measureable objectives, resources and capacity, as well as their tech stack and how they access and integrate historical and real-time data.