Teaching Practices That Support Authentic Learning With AI

As college and university faculty consider the seeming inevitability of students using AI, one of the possible responses includes fine-tuning policies that balance choice, innovation, and academic integrity. Another possible response is to nudge students in the direction of choosing what is best for their learning.

In Every Learner Everywhere’s webinar Teaching for Authentic Student Learning in an AI Age, Flower Darby, Director of the Center for Teaching and Learning at Estrella Mountain Community College, outlined classroom practices that give students reasons to invest effort. The premise of her presentation was that when students understand how the knowledge developed by working on an assignment connects to their own goals, they want to do the work to develop that knowledge rather than shortcut the work.

Darby acknowledged that “students can game every single recommendation that I’m going to talk about.” But instead of trying to design a perfect defense against abusing AI, instructors can help students by focusing on practical ways to help them “choose to do their work in a way that helps them to truly learn what we’re asking.”

Many of the approaches Darby recommended are based on the perspective of a book she co-authored, Small Teaching Online, which argues that small changes based on the science of learning can have an outsized impact.

Even though many students “are using AI in ways that undermine their learning,” she said, “we know that not all cognitive offloading is bad.” To steer students toward authentic learning experiences while they are using AI, she encouraged participants in the webinar to “lean into our academic superpowers of curiosity and critique.”

Explain relevance in terms students appreciate

When students see how course knowledge connects to their goals, they experience it as relevant and have a reason to invest effort in learning it. In the webinar, Darby urged instructors to make those connections explicit, whether students are focused on their preparation for employment, advancing to a four-year program or graduate program, or civic life.

Referring to findings from the field of neuroscience, she said, “The mind wanders to what it cares about. So we can put that superpower to work. Help our students see how what they’re learning is necessary and relevant for their well-being as an individual, as a citizen, as a future employee. And when we do that . . . they will do the work of learning.”

Darby explained that, to make relevance explicit in an assignment, instructors should think about what knowledge or judgment students will need after they submit it.

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Reduce the conditions that encourage shortcuts

Among the reasons students are tempted to cut corners are high stakes, tight deadlines, and feeling unprepared. The more those conditions are removed, the more students can choose authentic learning.

“Students are people, first of all,” Darby said. “The psychology of what tempts us to cheat applies to all of us. There are definitely decisions that we can make in our teaching and learning activities that reduce that temptation.”

One way instructors can “lower the pressure” for students is to consider forms of alternative grading, including test retakes, dropping the lowest score, and flexible due dates.

Give guidance on AI for each assignment

A general AI policy leaves students on their own to interpret what appropriate use means for a particular task. It’s not realistic that they will choose to use AI in ways to support authentic learning if they can’t see that distinction.

To help students develop that critical perspective, Darby recommended explaining expectations in the syllabus and on individual assignments in terms of a traffic light analogy — stop, caution, and go. Over time, this will “help students discover for themselves when AI is useful and when AI is not useful,” Darby said. “That is the discernment that employers are looking for.”

Ask students to examine their AI use

Darby discussed disclosure of AI use, making the point that if instructors disclose their own use in class materials, that will support students choosing authentic learning.

But she also explained it is helpful to go beyond the binary yes-no question of whether or not AI was used. Consider opportunities to ask why and how it was used and if it was helpful. Brief reflection activities at the end of an assignment give students a chance to assess a choice they might otherwise make without much thought.

Teach students effective uses for AI

Students may be less likely to use AI in ways that shortcut their learning if they can see which uses support authentic learning. Darby described seeing students use AI to make practice sets and study guides, get feedback on work they had done themselves, and plan how to finish a project.

Arguably, these are positive examples of using AI to facilitate practice rather than letting AI take over the thinking on an assignment. Instructors can present these possibilities and help students evaluate AI as a study tool in relation to the learning task at hand.

Does the syllabus make room for authentic learning with AI?

A key part of inspiring students to choose authentic learning is to step back from individual AI rules and review what they ask students to do across the course.

“We become fond of our syllabi,” Darby said. “They’re full of so much good stuff. But the world has changed. Technology has changed. And we need to ask ourselves some really hard questions as we’re critically analyzing the syllabus. And the hardest one of all is, ‘Are there things in there that are meaningless or irrelevant or no longer helpful for students in an AI age?’”

She recommended starting with one important assignment, then examining the steps students take to complete it. That review gives instructors a starting point for applying the other choices she described throughout the presentation, such as explaining the work’s relevance, identifying where AI could help, and guiding students to understand which thinking they need to do themselves.