Data Storytelling to Improve Course Scheduling

Report Hero:
Raelyn O’Neil

Institution: University of Toledo

Location: Toledo, Ohio

System Membership: University System of Ohio

Undergraduate Student Population: 13,000+

Campuses: Main Campus & Health Science campus with University of Toledo Medical Center

Raelyn O’Neil, Student Success Systems Administrator, is bridging course scheduling gaps at the University of Toledo using data-driven storytelling and historical enrollment trends to better inform the scheduling process.

Getting Started

As the University of Toledo’s first Student Success Systems Administrator, Raelyn O’Neil had a unique opportunity to define her role. Backed by strong support from leadership, O’Neil set out to strategically transform the scheduling process, pairing her expertise with Ad Astra’s analytic capabilities.

Her approach with stakeholders was incremental. While she served as the administrator of the Ad Astra platform, she used the data to create and share personalized “course cards” containing high-level data for each course, including current enrollment, room capacities, historical enrollments, and future term predictions. Additionally, Raelyn provided each college and department the top course changes recommended by Ad Astra. Departmental response forms were completed after course cards were reviewed by the colleges in order to determine why or why not faculty made certain course scheduling changes.

With this new workflow in place, Raelyn soon became the major resource for scheduling information among faculty and administrators at the University.

Creating Ownership

After seeing positive momentum over several semesters, Raelyn helped her stakeholders move from being passive receivers of the analytics to active users in the Ad Astra’s solution, Align with Predict and Monitor. Raelyn hosted a series of trainings with Caleb Tegtmeier, Ad Astra’s Strategic Solutions Consultant, with the goal of demonstrating how the University’s data could be filtered through Ad Astra’s software to help inform scheduling decisions.

Raelyn’s presentation included step-by-step suggestions for reviewing course data in the platform, especially the course’s historical and predictive enrollment trends. If changes were recommended by the platform, the presentation would take a deeper dive into the course’s heat map to determine the best time to add or cancel a course and the right section to cancel.

Course-specific heat map

Investigate the course’s historical enrollment using Align. Identity which past terms had high enrollment or low enrollment, in comparison to the number of seats offered during that coordinating term.
Explore the number of students who are predicted to have this course up next on their pathway. The use of Align with Predict will allow you to click on the predicted number in order to view the actual students at your university expected to take this course for the upcoming term.
Review the suggested number of seats needed for the course. Clarify that this reflects both the historical enrollment trend and the anticipated predicted trend. Refer back to steps 1 and 2 in order to help justify this prediction.
Offer suggestions for how to make this change a reality. Utilize the course-specific heat map to determine the availability of students based on the timing conflicts with other courses. If you need to add another section, offer it during a time where there are minimal time conflicts.

Data-Driven Storytelling

Understanding there’s an art and a science to scheduling, Raelyn relies on a data-driven storytelling approach. Specifically, the Course Offerings Index Report allows her to create a baseline to demonstrate the importance of reviewing the course schedule. The report indicates how well the course schedule performed the year prior by offering a breakout of under-utilized, overloaded and balanced courses. Providing a good starting place for discussion, it also shows where a problem could occur if action is not taken.

Further Analysis and Establishing
Goals

For Raelyn, evolving leadership and natural resistance to change meant recommendations took some time to adopt. Yet through persistence and stakeholder education, Raelyn continues to see transformation.

Moving forward, she’ll continue to seek out opportunities to demonstrate the power of using predictive data in planning and scheduling. In the next five years, Raelyn hopes to establish a scheduling champion in each department to support her quest to create improved scheduling experiences for faculty and students alike.

Ad Astra Products Used:

Align with Predict (for collaborative, student-driven scheduling)
Monitor (for registration tracking)