The UDP Accelerates Advising Action

Published September 23, 2026

With the fall semester now fully underway, we have entered a critical phase of student success. While conventional wisdom might hold that the first assignment, quiz, or exam will set the tone for student performance, a new school of thought – aided by learning data – suggests that student engagement with course materials during the first few weeks of the semester could be a more consequential and actionable performance indicator.  

Student engagement with course materials can be as simple as accessing the syllabus or joining a group discussion. Because these behaviors often precede graded assignments or instructor notes being added to the LMS, recognizing them can help advisors identify students who are disengaged from the outset to offer support and make adjustments to course correct.

Across the Unizin consortium, data analytics teams are working closely with advising communities to deploy dashboards, reporting tools and predictive platforms to provide real-time views of student engagement.  While the scope and complexity of these solutions vary from campus to campus, they share a common core – the Unizin Data Platform (UDP) and a growing array of Unizin Data Marts. 

Many of these solutions also share a common origin. As campuses have become more connected, collaborative and digitally centric, the need for common, shared solutions has become paramount.  Without dedicated resources and integrated systems, advising teams created workarounds - often including manual data capture from across disparate systems - to track student progress. While born of necessity, these approaches are difficult to sustain, impossible to scale and don’t provide the real-time behavioral insights necessary to support early student engagement. 

By standardizing LMS and SIS data emanating from disparate learning tools and platforms into a common data language updated in near real time, the UDP helps data teams better serve their advising colleagues by consolidating data streams into a single source of truth to inform advising platforms that can be scaled across institutions.  Unizin Data Marts further streamline the development process by providing plug-and-play access to some of the most common data queries and calculations.

“About 80% of the data for the PowerBI Dashboard we developed to support our Mizzou advising teams comes directly from the UDP,” says David Reid, Director of Solutions Architecture & Analytics at the University of Missouri. “The UDP integrates the nightly feeds of Canvas 2 data, live clickstream data, and the stream from our SIS and normalizes it all.  These Unizin Data marts, coupled with PowerBI row-level security, enable us to provide four different advising groups with four different data views, all from the same core dashboard.”

The Mizzou advising dashboards are just one example of the UDP enabling advisors to assess student engagement as both a snapshot and trending over time.  Other Unizin members have tailored their advising platforms to meet the bespoke needs of their advising communities and practices.

Indiana University’s Canvas Activity Score was one of the first advising tools developed within the consortium and has inspired and informed several other platforms.  The Canvas Activity Score not only established the core data framework for advising tools, the rigorous evaluation of the model demonstrated the predictive value of student engagement correlated to student success, as well as the positive impact of early advisor engagement on student grade performance and persistence. 

The University of Iowa’s Course Activities Insights (CAI) is a direct descendant of the Canvas Activity Score, sharing much of its data DNA.  Having a template not only enabled the Iowa team to accelerate the development of their own advisor-facing platform, it provided latitude to analyze the model’s effectiveness against the Iowa UDP data and make adjustments. The resulting advisor tool is integrated directly into Iowa’s SIS to alert advisors when students might benefit from outreach. 

Anteater Advising at the University of California Irvine emphasizes rapid access to actionable insights for advisors. The platform not only consolidates what had been a growing array of disparate, legacy reporting systems into one, shared, secure, advising platform focused on student success; it also serves as the gateway to other key analytics resources for advisors.  UCI continues to expand Anteater Advising to serve as a centralized advising toolkit to support dynamic querying for list creation, deeper integrations with UCI campus systems and to support new non-LMS use cases, such as creating and sharing course plans and managing advisor notes. 

Student Succes Viewer at the University of Michigan is an early warning system that helps academic advisors identify at-risk students using data about students' current term grades, activity, and assignments. Featuring a series of Tableau dashboards, the platform pulls LMS data from the UDP to provide daily updates for advisors in several, flexible views, including academic summaries, assignments, and course selection, as well as a report dashboard to export data.

Perhaps the most advanced advising application developed to-date is Penn State’s Performance Outlook, which goes beyond data integration and visualization to incorporate machine learning and real-time predictive risk modeling. Performance Outlook merges daily student activity data with advanced predictive analytics to generate actionable, real-time insights so advisors and educators can intervene and support student success as early as possible.   

By correlating learning data in the UDP to student behaviors and mapping those behaviors to eventual outcomes – Unizin is giving advisors powerful new insights to better support students across institutions.  While the modes of delivery may differ across campuses, speed is the common denominator.  Taking action early in the semester can make all the difference.