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Testing agencies get nervous about "test-optional", find new markets.

Pass out course evaluations early in the semester and focus on making sure students can tell you care. If you wait until the end of the semester, struggling students may have dropped out and you won't have time to adjust your teaching style. Set clear learning objectives for each unit so students know exactly what to study and feel more in control of their learning. Without those, "We were training students not to show up for class, wait until two days before the test, and then cram," Holland said. "We wondered why students didn't retain any of the information." Create 10-minute videos for each objective that students can watch and show up to class prepared to discuss. When it comes time to review, a student can read the unit objective and watch the corresponding video. Give frequent quizzes, essays, and group work so both the instructors and students know where they stand and students stay engaged. Provide early, intrusive interventions like meeting with every student who scores below a 70 on the first test.

"Cleary is among those professors trying to tackle that challenge with strategic interventions. Through an elective called the Science of Learning she hopes that if students read the research on memory and learning they will adopt better strategies. These desirable difficulties include strategies like testing yourself regularly on what you've learned, rather than reading the same passage over and over with a highlighter in hand. "What we're teaching people doesn't feel good," Cleary admits. And the techniques require continual practice to be effective. "It's a horrible sales pitch." Cleary also helps other faculty members figure out how to incorporate these strategies in their teaching. Students tend not to like, say, weekly quizzes. And professors often don't want to stop in the middle of a lecture to ask students to jot down what they've learned so far. It makes Cleary uncomfortable, too. "It feels like I'm not doing anything. I'm just standing there," she says. "I should be cramming more content into my lecture.""

I don't think people with existing skills will ever adopt generative AI as part of their daily practice. Instead, I think we're going to see lines drawn in the sand. After all, the folks who have those skills worked to establish them, often spending years honing such skills and going into debt to establish mastery in their fields. I fully expect to see many people bias generative AI as a form of cheating. Early testing shows that those with underdeveloped or emerging skills rather than those who have mastered skills are the most likely to benefit from adopting generative AI in their jobs. This suggests that such adoption could benefit those unprepared, unmotivated, and struggling students the most. It also suggests that their higher-performing peers will see the least amount of help from adopting generative AI. What's lost in this is we want as many students as possible to develop mastery in skills for their studies and their future careers, not use generative AI as a crutch to help them pass. ... I said this last year and think it rings truer today-the mark of future mobility will not be having access to a college education. Rather, it will be if you could afford to go to an institution where a human being taught you or if you had to attend one where you learned from an algorithm.

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