That’s a good point; I had forgotten how suspicious the sudden switch to online learning made so many professors. Lots of students were cheating, of course. But it did seem totally pave the way for AI use among faculty, in the sense that they want some kind of concrete way to “catch” their students doing what they suspect what the students will be doing.
I am an instructional technologist for a US public university. I do think 2020 set us up for AI in a lot of ways. You are right about that. It certainly made us more internet and device dependent. It was also the first time that many faculty began turning to technology to catch cheating and plagiarism. I believe that fed directly into the widespread desire for a technological to catching AI cheating and plagiarism. (Use of those fixes is discouraged, for good reasons, where I work.) 2020 also damaged a lot of students, perhaps keeping them from developing skills that they should have, and possibly making them readier to adopt AI as a crutch.
Our approach to AI in American higher education needs to include room for a lot of different policies, so students can develop skills they need without it and can develop skills they need at work. They need to understand its ethics (and perhaps its deeper moral implications), and learn its limitations. Students also need an overview of its history, economics, psychology and ideology (of its creators, promoters and users), and political and cultural effects.
Professors and instructors need a great deal of flexibility to experiment with the best responses for their disciplines and specific courses. I think students deserve that.
That’s a good point; I had forgotten how suspicious the sudden switch to online learning made so many professors. Lots of students were cheating, of course. But it did seem totally pave the way for AI use among faculty, in the sense that they want some kind of concrete way to “catch” their students doing what they suspect what the students will be doing.
I am an instructional technologist for a US public university. I do think 2020 set us up for AI in a lot of ways. You are right about that. It certainly made us more internet and device dependent. It was also the first time that many faculty began turning to technology to catch cheating and plagiarism. I believe that fed directly into the widespread desire for a technological to catching AI cheating and plagiarism. (Use of those fixes is discouraged, for good reasons, where I work.) 2020 also damaged a lot of students, perhaps keeping them from developing skills that they should have, and possibly making them readier to adopt AI as a crutch.
Our approach to AI in American higher education needs to include room for a lot of different policies, so students can develop skills they need without it and can develop skills they need at work. They need to understand its ethics (and perhaps its deeper moral implications), and learn its limitations. Students also need an overview of its history, economics, psychology and ideology (of its creators, promoters and users), and political and cultural effects.
Professors and instructors need a great deal of flexibility to experiment with the best responses for their disciplines and specific courses. I think students deserve that.