Is this the future of business school learning?

When I piloted this AI-based alternative in both my undergraduate and graduate business classes at UCLA, I saw much more participation and interaction in class, with students animated by what they were discussing.
Daniel Nathanson
Daniel Nathanson
Dr. Daniel Nathanson is a continuing lecturer and faculty advisor at the UCLA Anderson School of Management.

Business schools are filled with educators who cut their teeth on case studies. Invented over 100 years ago at Harvard, these teaching tools are used in about 40% of MBA classes at most top business schools, such as Harvard Business School (HBS), which uses it in 80% of its classes. Many educators consider HBS-style case studies the gold standard for helping students develop analytical business skills.

I believe that the case method is an integral part of teaching. I have consistently used four or five HBS cases in my classes throughout my career at NYU Stern and the UCLA Anderson School of Management. While I used and liked the HBS cases, I can now say that I’ve found a better alternative, and over 95% of my students agree. As an entrepreneur and investor committed to innovation, I’m constantly seeking new approaches to enhance the teaching and learning experience, especially with regard to providing real-world experiences whenever possible.

And guess what? This better alternative I found is fueled by academia’s current bugaboo: artificial intelligence.

More from UB: Why you need to teach your business school students to lead like a coach, not a boss

What needed to change in the age-old model

To better understand the improvements I saw, it’s essential to recognize the problems with the classic case study model for students, faculty and teaching assistants when students are required to cover 20 to 40 pages of text.

The classic case study model requires extensive reading and individual written analysis, which is inefficient and time-consuming for both the student and the grader, and it has relatively zero teaching value since assessment and grading are completed after the case has been discussed in class. Alternatively, group case assignments, where students discuss their points of view and collaborate on a deliverable, are more engaging and reflective of real-world situations. However, assessing each student’s contribution and preventing free-riders is virtually impossible.

A better alternative for business schools

The new alternative I’ve implemented in my classes has a more compelling format. With this AI-based model, I can offer case studies with dynamic multimedia presentations centered on high-quality videos. These appeal to my Gen Z undergraduate students who are digital natives, MBA students and Executive MBAs. Based on their feedback, they all prefer learning via multimedia as opposed to traditional texts.

With this model, I can tee up small-group discussions for students in online breakout rooms. Over 200 studies have shown that this type of active, discussion-based learning is more effective for every kind of student and promotes critical thinking. I’ve also found that this group learning approach not only supplements my lectures but also improves student engagement.

In these breakout discussions, students are prompted by key questions related to the case study. They decide what they would do and then discuss and defend their decisions with their fellow students. As students deliberate and defend their decisions, an AI-based assessment process is used to evaluate the quality of the discussions. I receive AI-generated session summaries using Bloom’s taxonomy, with engagement, contribution, and comprehension scores for team and individual student assessment. Even better: I’m no longer required to assess students by grading a stack of papers.

Better experiences and results for students and instructors

I have found that this AI-based alternative eliminates busy work, increases engagement, fosters critical thinking and cultivates a better understanding of the material. The format allows business school students to gain different perspectives on a case as they build communication and collaboration skills. And it returns education to a form of inspiration rather than explanation.

From my experience, the new method also offers multiple benefits for faculty. These advantages require no changes to the teaching approach or syllabus while helping us to prepare better, more targeted lectures. The fact that AI assessments help simplify grading and make evaluations more objective is hugely beneficial. They also provide true student accountability around cheating, participation, engagement and use of appropriate curriculum tools.

Since the format can be shared with teaching assistants, this new methodology enables better communication with TAs and greater accountability and confidence in their assessments of students. Finally, the process as a whole is far more enjoyable, meaningful and productive for students, leading to better student ratings for professors and their courses!

A teaching model for the digital age

When I piloted this AI-based alternative in both my undergraduate and graduate business classes at UCLA, I saw much more participation and interaction in class, with students animated by what they were discussing. And despite fears that AI will eliminate students’ authentic assessments, I found that the AI grading fairly captured their contributions.

It’s still early days for this new technology. Faculty members from a growing list of top business schools are now on board to use it, with more results and developments to come. But given how far the business world has come since Harvard’s first case studies were produced, this type of multimedia, AI-based transformation bodes well for creating new teaching models that can educate, engage and inspire students in the digital age.


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