Money Bucket of Training
Most professional development in higher education is a bucket with a hole in it. Money goes in. Nothing measurable comes out. It is time to fix the bucket.
Every year, colleges and universities spend millions on faculty training and professional development. Workshops on pedagogy. Conferences on assessment. Webinars on technology integration. Lunch-and-learns on inclusive teaching. The calendar is full. The budgets are spent. And almost nobody measures whether any of it changed anything.
This is the money bucket problem. You pour resources into training, and they drain out the bottom because there is no mechanism to capture, retain, or measure the impact.
I sat through hundreds of professional development sessions in my career. Some were excellent. Most were forgettable. A few were actively harmful because they consumed time and energy that could have been spent doing the actual work. And in thirty years, not once did anyone measure whether the training I received made me a better teacher.
We measured whether I attended. We measured whether I filled out the evaluation form. We measured whether I rated the session 4 or 5 on a scale of 1 to 5. But we never measured whether my students learned more after I was trained than before.
This is insane.
If we are going to spend money on training, we should be able to answer one question: did it work? And "did it work" does not mean "did the participants enjoy it." It means "did student outcomes improve in a measurable way as a result of this intervention."
AI makes this measurable for the first time. If you have a proficiency system tracking student outcomes across a course, you can measure the before and after of a training intervention. You can see whether students in the sections taught by trained faculty perform differently than students in untrained sections. You can see which training programs actually move the needle and which ones just fill the calendar.
Fix the bucket. Then pour money into it. Not the other way around.