Going Small With GenAI

• Instructors looking for small ways to introduce generative AI into their classes can start by performing audits to clarify expectations for students about when the technology is required, optional, or prohibited.
• To help students access their prior knowledge of GenAI and surface their lingering questions about institutional policy, instructors can devote class time to a discussion of the guidelines both in principle and within the context of the class topic.
• By making short, targeted learning activities a regular part of the beginning or end of class time, instructors can provide students with quick and less formal opportunities to see how GenAI connects with course topics either directly or indirectly.

 
Business loves big. We have Big Tech and Big Pharma and the Big Four accounting firms. Any good C-suite has a few BHAGs—the big hairy audacious goals popularized by author Jim Collins and driven by analysis drawn from…wait for it…big data. In business, as in sports and popular culture, we are continuously reminded to go big or go home.

It’s no surprise that business scholars are predisposed to the cult of big—but so is all of higher education. The industry pivoted to 100 percent online teaching at the start of the COVID-19 pandemic, and it has embraced both massive open online courses (MOOCs) and wholesale curriculum redesigns.

Is there an alternative to big in education? James Lang presents one in his best-selling Small Teaching: Everyday Lessons from the Science of Learning. The longtime contributor to The Chronicle of Higher Education postulates that higher education instructors can make outsized impacts on student learning through “small but powerful modifications to our course design and teaching practices.” However, the book was published before generative AI (GenAI) exploded into the mainstream, leaving questions about its applicability today.

To be sure, while GenAI has not yet created large-scale disruption in higher education, it has certainly advanced powerfully through the Gartner Hype Cycle (enthusiasm, disillusionment, reassessment, and widespread adoption). In fact, some have posited that GenAI’s waning hype is the very evidence that it will eventually reach its potential. In the education field, this means that GenAI could launch wholesale transformation of teaching and learning.

Such predictions can leave some business educators feeling boxed out by the sheer bigness of GenAI and its legitimately massive implications. They may dread being asked how they are incorporating the technology into their teaching. They may be wondering specifically: Is it even still possible to make “small but powerful modifications to our course design and teaching practices” in light of the big expectations around GenAI?

The good news is that the answer to that question is a resounding yes. Three “small teaching” approaches can have a big impact in the classroom:

• Minor modifications in course designs or communications with students.
• One-time course interventions.
• Brief classroom or online learning activities.

None of these approaches require specialized knowledge of GenAI and all of them can be implemented during breaks between terms or on the fly during a class. Following are straightforward examples of each one.

Perform a GenAI Audit

The most fertile category for surfacing GenAI in a course is the first one—making a small modification to the course design or the student communication process. One example, which I call the GenAI Audit, is informed by the research of Viji Sathy and Kelly A. Hogan. They note, “You can reach more [students] by sharpening the structure of your syllabus, assignments, tests, and pedagogy [because] all students appreciate and thrive from additional structure, and some benefit disproportionately.”

Determine which assignments best lend themselves to students’ use of GenAI to enrich their learning and which pose greater challenges in that regard.

If you’re an instructor, you can perform a GenAI audit by selecting a course irrespective of its current use of or predilection for GenAI. Start by distilling a simple list of the course’s graded assignments, including homework, quizzes, papers, and exams. Then systematically go through the list item by item with the mindset of someone trying to “hack” each assignment by using GenAI. That lens will help you determine which assignments best lend themselves to students’ use of GenAI to enrich their learning and which pose greater challenges in that regard.

Accordingly, you can flag each assignment with a rating of green, yellow, or red:

• Green means that students’ use of GenAI would be very accretive to their learning and should therefore be required.
• Yellow means that students’ use of GenAI could be accretive to their learning but is not essential and therefore should be optional.
• Red means that students’ use of GenAI would undermine their learning and therefore should be prohibited.

The critical step is to transfer each rating to the syllabus or learning management system (LMS) so students know where in the course GenAI is required, optional, or prohibited.

Begin at the Beginning

Straightforward activities are all you need for the second category, which consists of one-time interventions. Early in the term, simply carve out 30 minutes in a single class session to discuss your institution’s policy on the use of GenAI. This should not be a pedantic lecture about the do’s and don’ts detailed in the policy. Rather, this should be an active learning event in which, as Lang says, “students spend at least some time doing things in the classroom rather than sitting there passively.”

You could ask students to read the policy live in class. Or you could have them read it in advance as homework, which, as Lang says, will leverage the retrieval effect and pave “the way for [students’] memories to strengthen and improve.” Either way, your next step should be holding a class discussion in which you ask questions such as these:

• Which groups are in scope for the university’s AI policy? (Hint: Students will absolutely be in scope!)
• What are individuals responsible for when they are using any GenAI tools, whether these tools are publicly available or licensed by the university?
• Why is this important in a course dedicated to marketing, finance, accounting, or other business subjects?
• What are the implications as we work together as a class this term?
• What questions do you still have?

You can extend the discussion by presenting a scenario specific to the course, especially if it pertains to a topic that will come up later in the term. This allows students to determine how they may or may not apply GenAI to that scenario, given the institution’s policy.

As Lang points out, “almost anything that students do with learned information or ideas or skills works more effectively than just looking at [their] notes about it.” For that reason, this small one-time intervention achieves several goals. It contributes to students’ understanding of the institution’s position on GenAI, it helps them access their prior knowledge, and it answers their lingering questions.

Make It a Habit

The third and final category consists of brief classroom or online learning activities. These might include small teaching interventions that you can run in 10- or 15-minute increments at the beginning or end of class. You can even hold them before class starts as students are trickling into the room or joining the online session.

Much like conversations around the proverbial water cooler, these short time slots offer quick ways for people to pick up important information. In educational settings, they give students the chance to engage informally either directly with GenAI or indirectly with its implications. These time slots become particularly powerful if you make them a regular feature in every class session.

At the start of the class, you could query a GenAI tool with increasingly better-formed prompts to illustrate how the output becomes more accurate and precise.

As an example, as students are arriving in the classroom, you could post a provocative article from the mainstream business media that connects GenAI with the course topic. (I teach management consulting, and there is no shortage of these types of articles. I recently shared a piece from The Economist titled “McKinsey and its peers need a new strategy. And some humility.”) Students are unlikely to have read the selected article in advance. But Lang notes that students will activate their prior knowledge on any topic once they engage in an informal discussion about it and share their perspectives on it.

Furthermore, Lang adds, particularly relevant topics may may evoke emotions that will help capture students’ attention and prepare them for learning. For example, consider the emotions that a headline like this one from Fast Company might evoke among students close to graduating: “PwC limits some entry-level roles to just 13 locations.”

Another activity at the start of class could be a short demo around prompt engineering. You could share your screen and query a GenAI tool with increasingly better-formed prompts to illustrate how the ensuing output becomes more accurate and precise. Through this exercise, you are providing either an abstract or explicit example of an effective GenAI prompt, which gives students a framework that they can experiment with themselves.

But moving the small activity to the end of class can be equally effective. For example, in my management consulting course, we are able to cover only a few consulting frameworks live in a single class session. To provide students with more options, I give them time near the end of class to work together with GenAI to explore more frameworks relevant to their team projects.

Good Things Come in Small Packages

Like “jumbo shrimp,” the concept of “small GenAI” seems like an oxymoron, since the technology has such big potential for transforming teaching and learning. To be sure, taking some big swings with GenAI has merit, whether universities are experimenting with wholesale course design; building GenAI agents for coaching; or automating the production of LMS pages, slideware, and teaching notes.

But if you’re a business educator who has been looking for a smaller way in, you can find inspiration from the literature on teaching and learning. You also can draw on your own creativity to create small interventions that have big results.