Reporting co-curricular outcomes to a provost or accreditor

The same set of co-curricular findings has to serve two audiences who want opposite things from it. A provost wants to know whether the number is real and what it would cost to get more of it. An accreditor wants to know whether you have a functioning process, and is comparatively indifferent to how favorable the result is.

Writing one document for both produces something that satisfies neither. Here is what each is actually testing, and how to write for it.

What a provost is testing

Not the effect size. Whether you know the weaknesses in your own number.

An administrator who presents a favorable finding with no stated limitation is inviting cross-examination, and the limitation will be found: the obvious one, in co-curricular assessment, being that participants opted in. Get there first. Put the limitation in the same paragraph as the finding, in your own voice:

Students who completed the program returned at a higher rate than the institutional average. Participants self-selected into the program, and the comparison group is the institutional average rather than a matched cohort, so the difference includes a selection effect of unknown size. What we can say without qualification is that the program reached 140 students who had no prior co-curricular involvement.

That costs one sentence and changes the character of the meeting. You are no longer defending a claim; you are working a shared problem.

Our retention guide sets out the four fixes that make a comparison stronger: define participation before the term, match the comparison group where you can, disaggregate, and report reach on its own. What follows is what to do when a matched comparison is genuinely unavailable, which on most campuses it is.

Three claims that hold without a comparison group

All three are fundable, and all three avoid a causal claim entirely.

Reach. How many students from a named population the program engaged, and how many had no prior co-curricular involvement. “We reached 140 commuter students with no prior involvement” is a real result requiring no comparison at all, and it is frequently the most decision-relevant number in the report. A dean allocating a staff line cares more about who you can reach than about a contested effect size.

Change within participants. Pre-to-post movement on a defined measure, described precisely as movement among participants and nothing more. This is a legitimate claim so long as it is never phrased as what the program did to students generally.

Implementation. The program ran as designed, at the intended scale, with these response rates and this completion rate. Unglamorous, and it is what tells a reader whether the rest of the numbers can be trusted.

Give the number a defensible reference point

A rate without a comparison is not interpretable, and the national average is the wrong comparison for almost every campus.

Median full-time retention is 71% across all US degree-granting institutions, but 77% at private nonprofit four-year institutions and 63% at public two-year institutions (IPEDS, Fall 2023). A 68% rate is a serious problem at a selective private college and a genuine achievement at an open-access community college. Benchmark against your sector and your own prior year.

One framing note that matters more than it should: use concrete peer comparisons rather than percentile or quartile language. “Institutions of our size and sector sit near 63%” is received as information. “We are in the bottom quartile” is received as an accusation, and the conversation becomes about whether the comparison is fair rather than about what to do.

What an accreditor is testing

Something different: whether you have a cycle, and whether it closes.

The reviewable unit is the loop, not the result: stated learning outcomes, a measure aligned to each, evidence collected on a schedule, an interpretation of that evidence, a documented change made in response, and evidence the change was re-measured.

A modest outcome with a closed loop reviews better than a striking outcome with no loop. The step most often missing is the fifth: reports routinely describe outcomes, measures, and findings, then stop. Write down what you changed. “Response rates in the commuter cohort were 22%, so administration moved from email to in-session in spring, and the rate rose to 61%” is the sentence a reviewer is looking for, and it is worth more than a flattering percentage.

Keep the artifacts. The instrument as administered, the item wording, the response rates by cohort, the minutes of the meeting where the change was decided. An assessment cycle you cannot document did not happen as far as a review is concerned.

Handle a provider’s data as an input, not a report

If part of your programming is licensed, its assessment belongs in your report as evidence you interpreted rather than as a finding you forward.

Ask for the instrument, the item wording, the response rates, and a participant-level export tied to your own student identifiers so you can join it to your own persistence data. Then say whose instrument it was. The NSLS includes annual program assessments, for example, and published chapter outcomes such as an 81 percent semester-to-semester retention rate among inducted students at Delgado Community College, a figure that compares participants to an institutional average, which is exactly the limitation to state when using it. Questions worth asking us covers how to ask for the underlying data.

Two documents, one dataset

Write the provost version first: one page, the finding, the limitation, the reach number, and the decision you are asking for. Then write the accreditation version from the same dataset: outcomes, measures, evidence, interpretation, change, re-measurement, with the artifacts appended.

Neither should contain a claim the other contradicts. That sounds obvious and is the most common failure in practice, because the two documents are usually written a year apart by different people from different spreadsheets.

Do this next

Take your most recent co-curricular finding and add one sentence naming its limitation, in your own words, in the same paragraph. Then find the change you made in response to last year’s data and write it down. If there isn’t one, that (not the effect size) is the gap to close before the next review. Our guide to measuring student outcomes covers the instrument and record work that makes the next cycle easier.