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CASE STUDY

Aligning for Success

How the Community College of Allegheny County created a tactical plan to boost enrollment

Fast Facts

13

Percent increase in on-campus seats

7

Percent increase in year-over-year enrollments

5

Percent increase in student satisfaction with the ability to enroll in classes needed

The Challenge

Unpredictable student demand creates scheduling challenges

As the number of students in the traditional age bracket decline, many colleges and universities are preparing for an enrollment cliff. To get ahead of this challenge, the Community College of Allegheny County, Pittsburgh, began looking for new ways to bridge the intersection of enrollment management and course scheduling.


Through improved ability to predict course demand, the Community College of Allegheny County set out to create new scheduling practices that would help them become nimble in responding to student demand.

The Solution:

Better efficiencies would be built on the foundation of a new scheduling culture, one specifically focused on students that would boost retention. The Strategic Enrollment Retention plan, led by the Vice President of Enrollment Management, welcomed new players to the scheduling table with a focus on current data, strong partnerships, and a mindset of continuous improvement.


The process includes three deans, five associate deans, 30 department heads, program coordinators, and a unionized scheduling staff who were tasked with using data to improve scheduling success through the development of a tactical plan during the 2022-2023 academic year.


Registrar Diane Jacobs worked with Ad Astra to build sample plans for student-centric schedules and to close the design loop to improve programs/pathways. Additionally, research insights allowed the institution to determine the number of sections offered and response to demand.

 

The modified process ensured pathways were accurate and in alignment with a goal of annual planning in the immediate future. In turn, a process of continuous improvement highlights where scheduling adjustments can be made and how to deal with developmental courses that aren’t on the pathways.


“Annual scheduling is a big part of the tactical plan,” said Diane Jacobs, Registrar, Community College of Allegheny County. “We want to show reliable data to faculty and staff, and we need to find ways to engage faculty and departments in evaluating this and show where there are blocks in the paths.”


The tactical plan includes student input on the scheduling process. Students receive a 2-minute survey after they register. Associate deans also receive a feedback form to ensure schedules are in alignment.


Immediate outcomes include an increase in retention rate and in the number of credit hours with a goal of boosting overall enrollment in the short term. Seeking continuous improvement, CCAC plans to use data insights to predict Spring 2024 demand, analyze modality preferences, and share the results with those involved in the schedule-building process.

Constant attention to the data and improvements in analysis is critical to keeping ahead of the trends in academic planning and scheduling.”

-Diane Jacobs

-Registrar

Ad Astra Products

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Data-Informed Scheduling

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Student-Centered Scheduling

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Student Demand Prediction

School Background:

The Community College of Allegheny County, Pittsburgh, is a public community college located in Allegheny County, Pennsylvania. Founded in 1966, the multi-campus (urban and suburban) college encompasses four campuses and three centers, offering associate degrees, certificates, and diplomas in more than 130 programs across 10 career paths. The Community College of Allegheny County is accredited by the Middle States Commission on Higher Education and is part of the Ad Astra Charter for Integrated Planning.

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Ad Astra is the trusted partner of colleges and universities committed to graduating more students faster. ​Through data-informed planning and course scheduling, we empower institutions to remove barriers to completion while also ensuring financial sustainability.

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