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The resources on this page may require permission and the use of the UMBC VPN to access. See the FAQ on getting connected for more information.
You will need to Request Access before using any of these tools. This page is under active development and we strive to continue to improve, please contact Bob Carpenter at email@example.com with any questions or ideas.
Resources that support the move to online instruction (COVID-19)
Curated REX Reports for Faculty and Advisors
The REX page now provides reports curated for faculty that show students’ engagement in their classes during our rapid move to online instruction. REX contains a host of other useful reports supporting analysis, business intelligence, operations, and efficiency.
Online Engagement Dashboard for Student Success
This tool shows student engagement with both Blackboard and myUMBC. A student with low use of both systems may not be fully engaged with their online and hybrid classes. This tool has the ability to set filters for different student segments. Particularly useful to student success staff is the tool’s ability to generate lists of students with low engagement on either or both systems. (Updated weekly)
Resources that support the Strategic Enrollment Plan
Fall 2020 Enrollment Dashboard
Shows admissions, confirmation, and registration trends for the Fall 2020 Freshman class compared to the same dates for the previous two years. Can filter by college. (Updated daily)
Fall 2020 Advising Dashboard
Shows Advising clearance and registration trends for the Fall 2020 term compared to the same date last year. (Updated weekly)
Enhanced Admitted Students by Plan (With Matriculation Predictions)
This existing report has been expanded to include results from a highly-precise predictive model that shows the probability that an admitted freshman student will enroll. Can filter by college or department. (Updated weekly)
Resources that support student success and graduation
6-Year Graduation Prediction Model
This tool presents the output of a predictive model that generates the probability that a student admitted as a freshman admits will graduate in 6 years using data through their third semester at UMBC. It is most useful for student success staff and advising and planning. Important warning to users: this model is not solely designed to identify students at academic risk. For example, students with very high GPAs who complete twelve credit hours per term will be identified as having low 6-year graduation probabilities. (Current modeled cohort: Fall 2018)
Blackboard Predict uses advanced analytics and in-semester data to identify students at risk in their individual classes. It increases student success by improving our ability to send early alerts and gives advisors enhanced tools to better understand not only who might be at risk, but why.