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The Instructional Capacity Playbook

Realigning resources to meet changing enrollment patterns

No equation (much less an untested guideline or set of benchmarks) can determine the ideal alignment of resources with institutional mission. Managing instructional capacity is as much a political problem as a logistical challenge.

Better data and strong faculty engagement can lead to more productive conversations about how to work with departments to respond to changes in student demand.

In many cases, an analysis of the data reveals the illusion of capacity constraints. Often the real problem is not an absolute scarcity of resources, it is lack of transparency around how resources are currently being utilized—and missed opportunities to realign resources with areas of greatest need.

Allocating instructional resources appropriately requires negotiating difficult trade-offs through a shared governance process that engages faculty and academic leaders.

Colleges and universities both public and private are increasingly dependent on enrollment to generate essential revenue. Yet at the same time, enrollments have become significantly more volatile. Institutions are seeing greater variability in enrollments at the course, department, and college/school levels due to a range of factors.

As a result, most institutions are experiencing rapid growth in some programs or academic units, sharp declines in others, and unpredictable swings in enrollment with significant implications for capacity and financial sustainability.

Realigning resources to meet changing enrollment patterns

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    Track and predict student demand

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    Increase capacity in high-demand areas

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    Better balance faculty workload

Track and predict student demand

Rolling over the schedule no longer produces an accurate picture of demand in an increasingly volatile enrollment environment. In previous years, enrollment was easier to predict from year to year, allowing academic units to base the schedule on the previous year’s course offerings, with minor adjustments for overfilled sections. Today, demand patterns and the changing mix of credits students bring in mean enrollments are less constant across terms and years, and adjusting capacity becomes more difficult close to course start dates.
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Practice 1: Curricular interdependency

Understanding the portion of service enrollments in each department (or course) allows academic leaders to measure their programs’ contribution to students’ success outside of their own majors. Curricular interdependency also helps departments predict demand. Enrollment changes in programs with the highest number of service enrollments are a critical predictor of course demand.

Practice 2: Predicted course demand

With a strong understanding of course-level capacity and curricular interdependency, academic leaders are well equipped to predict course demand and right-size instructor assignments before the schedule is set.

Practice 3: Multi-term registration

Even with the ability to gauge demand in advance, there will inevitably be some mismatches between student demand and course availability. Once students actually register for courses and a theoretical degree plan is converted into a tangible schedule, the effects of section selection come into play, and space and instructor availability needs become more acute.

Practice 4: Central course wait lists

Most institutions allow students to place themselves on a wait list for full courses, but these wait lists are typically managed by individual instructors and are limited to a handful of students. Uncapping and centralizing wait lists allows institutions to size excess demand for course additions once the registration period has begun. Automating the wait list through existing registration systems frees up instructor time for curriculum planning and other activities.

Increase capacity in high-demand areas

Departmental resources have not kept up with enrollment increases in high-demand programs. In programs with high and growing student demand, faculty are often overloaded and unit leaders must hire adjuncts to teach courses. Students are unable to register for required courses. Often, demand is driven by general education and service enrollments, which disadvantages service departments in the traditional headcount-based model of faculty line allocation.
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Practice 5: Enrollment growth funding

Tuition revenue is a critical lever in any budget model. The Virginia Polytechnic Institute and State University (Virginia Tech) planned for rapid enrollment growth in its College of Engineering, leading to an increase in tuition revenue in an otherwise lean time (Virginia Tech was planning for a 3% across-the-board budget cut). Rather than the traditional model of using this revenue solely for Engineering’s priorities or adding it all to a central fund, Virginia Tech allocated funds based on the wide-ranging impacts of growth.

Practice 6: Faculty line reassignment

Faculty line recapture and reallocation is probably one of the most important ways of reallocating resources in response to changing enrollment. When faculty lines open due to a faculty member leaving or retiring, institutions have an opportunity to reassess whether the line is needed in the current department given enrollment shifts that occurred during the faculty member’s time in seat or changing research priorities.

Practice 7: Overflow capacity for bottleneck courses

While high-demand courses during the standard academic term may lack enough capacity to meet demand, courses outside of the traditional academic year are typically scheduled without central oversight and are often under-filled. The intersession between holiday break and spring term is often unused altogether or treated as an optional enrichment opportunity.

Reallocate underutilized capacity

A proliferation of small and under-filled courses increases teaching demands on faculty without a proportional increase in SCH production. Many institutions have sought to reduce the breadth of curricular offerings by setting a strict enrollment minimum. This approach overlooks the impact on students, especially when there is a pedagogical necessity for small courses. However, too many small courses put pressure on academic leaders to hire adjuncts to meet capacity needs in higher-demand courses.
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Practice 8: Section consolidation

The below example shows how four sections of a lower-division anthropology course with fill rates ranging from 38% to 69% could be consolidated resulting in three sections with an 80% fill rate. Not all under-filled sections should be collapsed or consolidated (some are scheduled to accommodate students taking co-requisites scheduled at the same time as the other sections of the course, for example). However, institutions that have gone through the process indicate that the savings from even a small number of consolidations still merit the effort.

Practice 9: Small course consolidation

One area where many institutions have identified opportunities to increase capacity is in very small courses, particularly those designated as independent study. Independent study constitutes about one-tenth of the total courses taught at the average institution, but they have a significant impact on faculty workload.

Reduce curricular bottlenecks

Complex prerequisite pathways and non-degree-granting tracks lead to under- and overenrolled courses and excess credits, while reducing options for student coursetaking. Demand for individual courses is often driven by prerequisite requirements and rigid curricula, leading to increased workloads and making it more difficult for students to path themselves through the curriculum. Students may graduate with more than the required number of credits, while common prerequisites are overfilled.
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Practice 10: Track consolidation

The Greenlee School of Journalism and Communication at Iowa State University took a systematic approach to reducing the number of small course offerings by focusing on non-degree-applicable “tracks” within its degree programs. Rather than eliminate all courses with fewer than five students, the Greenlee School asked faculty to consolidate courses in specialized tracks, those in extensive sequences, and very small electives or independent study.

Practice 11: Streamlined prerequisite pathways

Beyond increasing the number of instructors or increasing the number of students per course, there is a third way to increase capacity: changing the patterns of demand at the curricular level. Curricular requirements can create bottlenecks when one course is required for a large number of majors.

Better balance faculty workloads

Changes in student demand, as well as growing research and service requirements, result in unbalanced workloads. While most institutional policies have a ‘standard’ course load and distribution of effort (across teaching, research, and service) in reality, faculty workloads vary enormously.

Faculty in units with rising student numbers often struggle to keep up with demand, while faculty in units with declining demand may teach well below the standard load. Wide variation in research productivity and heavily skewed service obligations (often correlated with race and gender) result in inequitable workload allocations and lower overall productivity.
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Practice 12: Departmental teaching dashboard

A simple way to set up a departmental teaching benchmark is to add up the statutory teaching capacity of all tenured and tenure-track faculty, then subtract all planned/funded releases. The resulting “theoretical course capacity” is the maximum number of courses the unit can schedule without hiring adjuncts.

Practice 13: Faculty activity dashboard

The standard workload and planned releases are a good starting point for measuring faculty contributions to the department, but of course they do not tell the whole story. Binghamton University takes a more holistic approach to measuring faculty activity through a dashboard that counts several different types of teaching and many varieties of scholarly activity, as well as release time given for administration (in $).

Practice 14: Differentiated instructional roles

Many institutions have pursued multiple tenure tracks to allow faculty to specialize in research or teaching. The Belk College of Business at the University of North Carolina at Charlotte developed such a model in 2000, where faculty were hired for teaching, research, or combined “tracks” to tenure. However, this model led to political conflicts because it created two standards for tenure and reduced the research productivity of faculty on the balanced track.

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