Aviso Predict - Student Risk Modeling

 

Predictors Help Us Understand Outcomes

 

Aviso Predict harvests student information where our data scientists manage a continually growing file of predictors used for assessing risk.

Objectives:

  • Better understand individual Risk Factors that are correlated with historical success at your institution

  • Identify the right students at the right time that could benefit from timely interaction

Features:

  • Actionable outreach leads to measurable results

  • Custom risk factors are determined using your institutional data

  • Risk predictions continue to improve over time

Watch a detailed video on Student Risk Modeling from our Chief Data Scientist below:

Displaying Risk:

 

The Aviso Risk Indicator is a symbol used to represent risk levels at both the student and course level. Risk level is represented by this indicator placed at the student level by the student’s profile picture through the Engage platform and is meant to provide the user with a high-level indication of the respective risk, prompting the user to consider exploring the Risk Score further.

The Student Persistence Indicator will always be located to the left of the Course Completion indicator, however, you can hover over either indicator in order to identify, of the two, which is indicating the associated risk. An example of these indicators displayed on each student profile picture is shown below.

Olivia Risk Indicators 1.png

Risk Scores provide a more detailed visual of Student Persistence Risk and Course Completion Risk.

The bar below represents the Risk Score for student persistence when displayed within the Student profile header or for course completion when displayed within the course section title for each course listed within the Term tab.

The percentage listed (Risk Score) is the probability of the student persisting to the next term (or completing the respective course) and the Risk Level is identified via the color of the bar.

The determination of a risk level (i.e. color) is made by establishing Risk Thresholds or limits that determine when a score should produce a red, yellow or green outcome and can be derived in a number of ways to optimize the operational outreach of your student success initiative given the resource levels available at your institution.

Our data science team manages a continually growing file of predictors that include Geo-Demographic, Academic Ability, Academic Performance, Academic Scheduling, Course Sequencing, Ability to Pay, and Financial Support factors, along with certain behavioral and engagement factors for the various predictions made.

Dashboards are also made available based of role and needs of your institution.