The Data Science Team recently released its set of predictions for the 6-year graduation probabilities of the 2020 Freshman cohort. Below is a snapshot of the current cohort's predictions, in blue, with the 2019 Freshman cohort's predictions, in red. 

The vertical axis represents the end of 2nd semester prediction probability; the horizontal axis is the end of the 3rd semester prediction. 

The black diagonal line indicates the point on the graph at which the second semester and third semester predictions are equal. If a dot, representing an individual student, rests on the line there was no change in the student's predicted probability of graduating between their second and third semester. Points above the line mean a student's predicted 6-year graduation probability decreased from semester 2 to semester 3. 

The group of students above the line, particularly in the Moderate and Low probability color bands, are of concern as their predicted probabilities of graduation have declined over their last two completed semesters. 

The 2020 Freshman cohort was the first freshman class during COVID and one of the concerns is the effect COVID may have on student performance in later semesters. From the predictions chart there seems to be reasons for optimism. Looking at the dispersion of points, there is a greater concentration of students in the High and Very High likelihood buckets compared to the 2019 cohort, as shown by the clustering of blue dots in the upper right corner of the chart. 

However, some concern may remain. Students whose predictions fall in the Low and Moderate buckets have experienced sharper declines in predicted likelihood to graduate than students from the 2019 cohort (because the blue dots, 2020 cohort, are much further above the diagonal line than the red dots, 2019 cohort). 

The diagram we've shown in this post is produced by a tool developed by the Data Science Team.  The tool allows staff with broad student success responsibilities to identify groups of students who may need additional support to achieve their goals.  The tool is available at analytics.umbc.edu in the student success section.  Access to it requires permission.  

(NOTE: Please join us Friday, March 18th from 12-1pm, for the fourth in our series of our Spring 2022 Data Science Workshops. This predictive model will be the topic of the session. Go to this link - https://my3.my.umbc.edu/groups/instructional-technology/events/101281 to register)

Len Mancini

Data Scientist and Statistical Specialist

The Analytics, Business Intelligence, and Student Success Technologies Group is part of the Provost;s Office and the Division of Information Technology.  Our component parts include the Business Intelligence/Data Warehouse Team, the Analytics/Data Science Team, the PeopleSoft SA/Salesforce Team, and since late 2021, the myUMBC/Campus Information Portal Team.  

We're very pleased to provide you with our "annual" report (delayed by the pandemic, like so many other things).  The report details selected projects and initiatives from 2019 through mid-year 2021, our goals, and our projects going forward.  As the report is part of our assessment activities, we welcome your comments.

We are grateful to our many collaborators and partners across the campus.  Success is never final, but it is also surely a joint effort.

First-year retention is UMBC’s single biggest point of loss during the lifetime of a freshman cohort and a key focus area of the university’s student success efforts. To support this work the Data Science Team (from DoIT and the Provost's Office) and its campus partners have worked with our HelioCampus to produce the first of a series of predictive analytics reports or “playbooks.” 

The first playbook, just deployed on analytics.umbc.edu, predicts the likelihood of a first-time full-time freshman returning for their second year.  It is being used by the Academic Advocates in Undergraduate Academic Affairs to help identify students who may be at risk of not returning next fall. (Access to the playbook is role-based.)

On February 25th, at noon, the REX Analytics Group will meet to explore the factors that make these predictions change the most, how to read the dashboards, and how to interpret and use the playbook.  Please join us! Contact lmancini@umbc.edu or kjoseph@umbc.edu for meeting details.

Len Mancini

Data Scientist and Statistical Specialist

DoIT is excited to announce that during January we will be replacing more than 1,000 wireless access points throughout academic, administrative and support buildings on campus. We are taking measures to minimize disruptions however, some areas may see momentary impacts to wireless service. 

We expect that each building will require approximately 3 days of work to complete and we will complete each building before moving on to the next. During the work for your building please be patient as we try to complete your area as quickly as possible while also making our best efforts to maintain stable service.

Replacing wireless access points will modernize the wireless infrastructure and provide faster connections, better wireless coverage and an overall improved experience to the UMBC community. 

If you have any questions or concerns about this project, please do not hesitate to contact me. 

Ray Soellner

Assoc. Director - DoIT

rays1@umbc.edu

Tonight, Tuesday December 21st, beginning at 6pm we will be performing emergency software upgrades on the new campus phone system. This work is to address a recent security vulnerability that exists in the software of the servers running the campus phone system. We expect the work to require less than 2 hours to complete. 

We don’t anticipate any service disruptions during the maintenance window, however we appreciate your patience and understanding should you experience any abnormalities. If you have any questions or concerns regarding this work please feel free to contact me directly. 

Ray Soellner

Assoc. Director - DoIT

rays1@umbc.edu