6 Steps to Developing a Metric to Understand Course Compaction

Just as strategic enrollment management looks at metrics at the institutional, department, program, and course level, so too must course compaction and curriculum offerings be understood at different levels of aggregation. In this post, we'll dive into how to approach the data to create a metric of compaction.

Previous posts in the Course Compaction Series:

1. What Impact Does Course Compaction Have on Student Success
2. 4 Ways Course Compaction Benefits Instructors
3. Course Compaction: 9 Indicators of Negative Compaction
4. 6 Indicators of Healthy Course Compaction

Not all programs will have courses that can be shared across departments or with other programs, and some institutions will have missions and mandates which influence program design, course offerings, and whether an under-enrolled course is kept regardless of its efficiency.

As an example, many Canadian institutions have expanded their program offerings and added Indigenous content to their course curriculum in response to the Truth & Reconciliation Commission Calls to Action for educators. This may create more dense course content, create more pathways to graduation and increase complexity in analyzing student course registration behaviour. The balance of efficiency, progress, student interest, and the educational mission is unique to each institution, and should influence the application of this metric.

6 Steps to building a Compaction Index

1. Standardize data collection and consistently report the metrics. Build data literacy around the data fields and metrics you expect to use.

2. Normalize the data across different programs and course types and sizes

3. Select a limited combination of factors to use. This selection should include at least one factor to represent: Course Efficiency & Demand, Program Course Sequencing, and Student satisfaction.

4. Design a basic compound formula, and aim for clarity and actionability over perfection.

i. For institutions with limited data resources and time, a single compound indicator may be sufficient to spur conversation and inform decision-making.

ii. For institutions with more resources available, creating a few formulas with different combinations of indicators from each area may enable better analysis for understanding and selecting appropriately significant factors.

Note: Selecting too many factors may cause overfitting. Instead, use the Compaction Indicator as a signal for further investigation, where other indicators can be analyzed as needed and as resources allow. We recommend prioritizing factors that decision-makers understand, which can be influenced by policy, scheduling, or curriculum changes.

5. Apply and test different factor weights at each aggregation level and across different academic areas on past data. Test the indicator against a year or years where you are aware of compaction issues, or where you’d expect significant changes in enrollment or policy to change the result.

6. Confirm indicator, set benchmarks, add indicator to standard reports.

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