Friday Follow Up, Part One

If institution type is a major confounder that isn't properly specified in the main analysis, the sensitivity analysis can tell us how strong such unmeasured confounding would need to be to explain away the results, but cannot directly tell us whether institution type specifically is that confounder. OHA’s statement of sensitivity analysis is also misleading: “Our sensitivity analysis checked all outcomes and model specifications, revealing that it would be unlikely (emphasis mine) that an observed treatment effect associated with enrolling in an exclusively online degree program was caused by an unmeasured or hidden confounder.” It is misleading because it implies the improbability of a hidden confounder, which is not what Rosenbaum’s sensitivity analysis can assess. Rosenbaum’s method is designed to measure how strong a potential unmeasured confounder would need to be to nullify or significantly weaken the observed treatment effect, not to estimate the likelihood of such a confounder existing.

Without properly accounting for institution type as a confounder, we risk implementing policies that address symptoms rather than causes, potentially making it harder for non-traditional students to access higher education while failing to improve their chances of success.

The bottom fell out of the market in 2022 and buyers were afraid of the end of the world or at least under strict instructions to cut spending and conserve cash. Many of the newish EdTech start-ups / founders were a bit insulated from that fear mongering or still believed in the 2021 pandemic era school-at-home bubble and the employment oriented workforce / HCM start-ups had yet to see their end clients really start to reduce staff and, with such, seats for their underlying SaaS or marketplace solutions.

Buyers were marshalling cash and for those that did want to buy, there were no market clearing prices.

This changed in 2023, at least from my perspective and portfolio. Initially the ice was thawed for AI education start-up with real technical chops and actual client revenue traction fresh off the attention grabbing launch of Chat GPT 3.5 in Q3-4 2022, but by mid 2023, I was seeing plenty of demand for my K-12 curriculum companies at historical SaaS multiples (6-12x ARR). I guess buyers got the all-clear from their investors, especially in K-12 which has remained relatively insulated and increasingly confident that the expiration of ESSER funding was not going to crash their business. This continues through today.

That being said, employment levels and HR budgets have remained challenged thus making it hard for me to get most of my Workforce / Professional Education / HR deals over the finish line. With a challenged outlook for end markets as well as the new demographic realities and eternal product-market fit issues of traditional college programs, Higher Ed M&A has also remained difficult for me and my companies.

Again, at least from my perspective, Education M&A is really a Tale of Two Markets: K-12 and everything else.

I agree, there is something in the air. I believe these deals show there is plenty of appetite for education businesses with healthy unit economics and a strong grip on cashflow. Less appetite for growth at all costs.

According to the latest government data, higher ed contingent workers now occupy the lion’s share of the nation’s academic workforce at an overwhelming two thirds (68%), while tenured and tenure-track faculty have been reduced to a dismal quarter (24%). These numbers reflect a deeply troubling dependency on perilous academic workers, with some calling them the new faculty majority. In a topsy-turvy transformation, it’s a dramatic reversal from three decades ago, when the nation’s college instructional staff occupied nearly equal proportions of contingent and tenure-stream faculty.

It’s a common belief that professors teach most classes at our colleges, when the fact is that most students in American classrooms receive instruction from others, mostly graduate teaching assistants and adjuncts. If you wander down the halls, poking into classrooms, there’s no obvious, discernable difference between full-time, credentialed faculty and contingent instructors, especially when the two are assigned similar courses, often teaching right next door to each other in the same hallway. As in Shakespeare comedies, you often can’t tell who’s who, but in college it’s no laughing matter. Students mostly aren’t aware of who among their teachers is a tenured professor and who is an adjunct. And they don’t know which one earns a handsome wage and who makes just peanuts.

“Colleges mostly use contingent faculty for teaching and learning,” Phil Hill, publisher of the On EdTech newsletter told me. “With tenure, you’re involved year after year, but adjuncts don’t get access to their courses until the last minute. So, if you care about quality teaching, you’re scrambling to make it happen.”

Robert Kelchen, head of the Department of Educational Leadership and Policy Studies at the University of Tennessee at Knoxville, agrees: “There’s a very real concern about the quality of adjunct teaching.”

There are many good points raised by Robert Ubell in this article - many negative consequences for both adjuncts and students - in the ways adjuncts are used and treated in HE. To highlight just one, just-in-time teaching assignments serve no one. How can these instructors be adequately prepared to teach in this situation? These last minute assignments are far too frequent, a tactic rather than an exception, because it keeps instruction costs in alignment with demand and revenue.

For online courses, it can be especially problematic if the instructor has not had adequate training to teach online. This can be as true for full-time faculty who primarily teach F2F and are thrust into teaching online at the 11th hour as it is for adjuncts. If I had a dime for everytime poor student engagement and performance is blamed on the online modality, rather than poor practice in preparing and supporting faculty to teach in this modality, I would be a rich woman.

You know, you come from nothing - you're going back to nothing.

What have you lost? Nothing!

Always look on the bright side of life.