Well, it's up to the reader to follow the implications. But the industry does hold sway in the design of university curricula, sometimes to the disappointment of academics, and this is nothing new.
Also consider that MIT used the Scheme version of SICP as their introductory programming textbook for years, and it remains a classic, but nowadays MIT leans into Python for introductory programming courses.
You have been voted down, but this is 100% truth. I’d been a professional software developer for 10 years and programming since a young child when I stumbled across the MIT Scheme open course (this was nearly 10 years ago now). Learning Scheme as an exercise dramatically improved me as a software developer, as it is the near perfect teaching language. The fundamentals of most computer science concepts are so clearly laid out, with no distractions. I wish I’d had the exposure at a younger age!
MIT Scheme is pretty much useless as a practical language, vastly less useful than Python. Python is infinitely more powerful to actually “make things”. But this is not the point of University!
The academic languages are powerful for learning, and it is a huge shame that they are being replaced with “professionally relevant” languages.
Real software engineering is a drudgery of stitching together other people's libraries and APIs, responding to the product team's "can't we just...?" queries, and alphabetizing your HTML properties. College doesn't prepare you for that. Shiny happy Schemeland doesn't prepare you for that. It's like the old joke about Bill Gates and the beta version of hell.
Dijkstra was a great computer scientist who was also very generous with his expressions of dismay. You can find him expressing dismay over a great variety of topics not all of which have turned out to merit it in the long run.
This says nothing about whether or not this specific instance of dismay is warranted. All you've said is a man can't be right 100% of the time which I don't find very useful.
I'd be interested in seeing an analysis that traces the programming language paths built into university curricula and how those paths have tended to change over the years. The weakening of theory components is also of interest. My sense is that the trends are real, based on what I've noticed and conversations with instructors in higher education, but I don't have an empirical dataset to support it.
A decent theoretical model can be extrapolated from Goodhart's law. Graduates' performance on programming and leetcode-style interviews is a measure that many stakeholders care about, so it's a target for university departments that would lose value as a measure of educational quality. As a CS department optimizes its performance on that measure, elements of the curriculum are reprioritized. It becomes okay for the department to sacrifice educational quality in order to enhance performance on the measure. What doesn't go directly into the measure, such as experience outside of a core programming language intended for programming interviews, gets chipped away over the years through market pressures as universities' graduates compete for relative performance on the measure. This is a theoretical model, but to me it's convincing.
For example, back in 2001, Dijkstra expressed his dismay at Java replacing a different functional programming language, Haskell, in UT Austin's introductory programming course. https://www.cs.utexas.edu/users/EWD/transcriptions/OtherDocs...
Also consider that MIT used the Scheme version of SICP as their introductory programming textbook for years, and it remains a classic, but nowadays MIT leans into Python for introductory programming courses.