Further Thoughts on Increasing Primacy of Enrollment Challenges

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In Monday’s newsletter “Does Anyone Believe the ‘Enrollments Are Stabilizing’ Narrative?” I described that Higher Ed enrollments (and revenue) increasingly represent the topic for institutional leadership, and that the topic is structural in nature.

As a follow-up, I’d like to both share additional thoughts outside of the premium newsletter and to address some questions about the nature of the enrollment crisis and how to think about generative AI news.

What Are Some of the Recent Dots?

Since Monday we have had some education articles backing this trend:

• Yesterday Higher Ed Dive described how West Virginia University is facing a $45 million budget deficit with no recovery in site, leading that institution to review almost half of its academic programs, with the expectation to cut programs as needed.

• Today Inside Higher Ed described the state of Pennsylvania, having one of the highest institution-to-student ratios in the country, was already seeing double-digit enrollment declines at many institutions since 2010, with the PASSHE system dropping more than 30% and some regional comprehensive universities seeing 50% declines. The demographic cliff could only be one of the factors.

Prior to this week but in 2023:

• In January, the California State University system announced plans for a new funding formula that would punish underperforming campuses based on nearly systemwide enrollment declines. This performance-based funding to deal with enrollment challenges aligns (to a degree) with programs in Texas and Oregon.

• We have had numerous private conversations in our consulting engagements that show the primacy of finding new revenue sources (or solidifying existing ones to become reliable) and to actually stabilize enrollments.

Of course, not all dots are negative in nature, as there are exceptions that clarify the rule.

• Yesterday, the Columbus Dispatch described how Franklin University in Ohio had its largest graduating class ever, with an 8% enrollment increase last fall, when peer institutions had 4 - 5% declines. Franklin University leadership attributed the success to “access, affordability, quality and relevance.”

• An article yesterday in Forbes described Berry College and its 48% increase in first-year enrollment over the past five years, with much of the success credited to a strategic initiative implementing a CRM and improving their outreach to prospects and new students.

Whither AI?

I’m at the D2L Fusion users conference, and today is the Executive Summit. At the summit, the AI topic is front and center (and will likely be in the main conference as well). This raises the question of whether the big topic for HE institutions is enrollment / revenue or generative AI.

While there is something of a PR-initiative nature to the Berry College article above, the reference to prioritizing technology (and organizational change) to directly impact enrollment is part of the point from Monday’s newsletter.

You can think of this as a simplified version of Maslow’s Hierarchy of Needs as applied to institutions (or systems of institutions). At the base physiological and safety needs, institutions need reliable revenue to continue to survive, largely driven by enrollment - either directly through tuition or indirectly through state funding formulas. Needs at these lower levels must be satisfied before institutions can attend to higher needs, to paraphrase and adapt the model. If a college or university is facing a structural budget deficit driven by declining enrollments, it’s not that nothing else matters, but the primary focus must be on these base issues. At best, the higher needs can occur alongside enrollment and revenue-driven initiatives, as long there is no distraction introduced. Thus generative AI is an important and even transformational higher need, but it is not primary, despite the media hype.

Seen in this way, I think D2L did an effective job today positioning generative AI and its impact on education and LMS companies by referencing a framework of ‘this is how we think of AI and its uses and risks’ and the need for college and university research to inform how generative AI will impact education in the future. And to point out that this is different than current usage of other forms of AI such as video transcription. This message is quite different than Chegg’s approach of ‘look at our new tools and behold how we [claim to] have mastered the usage of generative AI’.

We will see if this message continues through the main D2L Fusion conference sessions.

Enrollment-driven revenue increasingly is the base need, and generative AI is a higher need that is not top priority and fits into institutional strategy only if it does not distract from or its usage can be seen as helping to address the base need.

None of this is to argue that institutions and vendors should not work on initiatives that do not directly tie to revenue and enrollment in the near- to mid-term, but we should understand how the real priorities of institutional leadership are changing this year. The priorities of 2023 and 2024 are not the same as in 2021 and 2022.

Update: Removed erroneous reference of Berry College as an HBCU

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