From AI Integration to AI Co-Creation

• By viewing AI as a co-creator in their classrooms, educators can bridge the gap between the skills they teach and the skills employers want most.
• When professors use AI tools to design courses, create lesson plans, and grade assignments, they free up more of time to create meaningful learning experiences tailored to the needs of every student.
• Educators can develop their AI literacy by experimenting with one tool at a time for one task at a time, slowly growing their confidence and improving their skills.

 
What would happen if, instead of being integrated into the college curriculum, artificial intelligence co-creates the curriculum? What if AI is the curriculum?

These questions are sure to make some educators uncomfortable, get some excited about AI’s potential, and leave some pondering what the future of education will look like. As for the two of us, after spending a lot of time exploring the possibilities, we can state only one thing with certainty: The landscape of higher education will continue to change every day, as new AI-powered tools enter the market and society’s AI literacy slowly increases.

But if AI’s disruption of higher education is inevitable, how can we use it to our advantage—and to the advantage of our students? In the discussion below, we hope to stimulate discourse about the use of AI in our classrooms and encourage other educators to push the boundaries of what new technologies make possible.

The Growing Academic-Industry Divide

Traditional college curricula continue to struggle to keep pace with a rapidly evolving workforce. Too often, students invest time and money in education, only to graduate without the capabilities they need to succeed in their desired fields.

As educators, we can argue about the reasons for this common outcome. We can argue over semantics, question our measurement and assessment methods, or cite exemplars that we should emulate. But at the end of the day, in too many classrooms across the globe, educators are not teaching students the skills that employers want most, such as curiosity, creative thinking, adaptability, empathy, and technological literacy.

Over the past few years, AACSB has revised its accreditation standards to address this skills gap, particularly regarding new technology such as AI. It has facilitated AI-themed presentations, including a multitude of conversations at this year’s International Conference and Annual Meeting in Atlanta. In AACSB Insights, the association has published a number of articles exploring AI and assessment and the impact of generative AI.

We cannot keep our curricula aligned with what employers want by only making incremental changes. We must continually reimagine how we teach.

Yet, AACSB and other organizations still have a lot of room to promote best practices in AI’s application, because our students often are failing to develop up-to-date skill sets. This is happening for several reasons:

• We base too many of our courses on outdated curricula.
• We teach concepts in isolation.
• We teach students about skills through theory and simulated learning, instead of helping them master those skills through hands-on use of the latest technologies.
• We update our course content at a glacial pace.

Unfortunately, we cannot keep our curricula aligned with what employers want by only making incremental changes or by adding standalone activities and simulations. We must continually reimagine how we teach.

Transforming our teaching will not be clean or easy. But if we want our programs to remain relevant to business, embracing the messy and difficult is a better alternative than protecting the status quo.

The Promise of AI

Having spent nearly two decades pushing the boundaries of traditional teaching, the two of us do not view AI as a problem to be solved. On the contrary, we see AI as a solution, one that is key to helping us address the disconnect between what we teach and what employers want. It’s more than just a tool we can use in our classrooms—it’s a game-changer.

In fact, how business educators teach will never be the same, in the best of ways. For instance, we can use AI to keep our classes relevant and engaging, ensuring that we move beyond teaching outdated theories or skills that won’t help students capture the attention of employers.

With this technology, we also can customize our classes to fit each student’s learning style and pace in ways that were previously impossible. Imagine a class where all students receive the support they need when they need it—and where all students are presented with challenges tailored to their specific aspirations and levels of skills development.

In this new era, we can view teaching as a collaboration between people and machines. AI can take over a vast majority of the work required to design courses, create lesson plans, and grade assignments. This frees up more of our time and energy to focus on what really matters: inspiring students, mentoring them, and helping them climb Bloom’s taxonomy, so that they move more quickly from merely acquiring knowledge to analyzing problems and creating solutions.

AI’s contributions will give us more time to get to know our students better so that we can create more meaningful learning experiences tailored to the needs of every individual. It will allow us to produce college graduates who are more competent, curious, creative, and adaptable.

AI Co-Creates a Course

We can see one example of this new way of teaching in Entrepreneurial Creativity with Artificial Intelligence, a course taught by Doan Winkel, an author of this article. Part of the curriculum at John Carroll University’s Boler College of Business in University Heights, Ohio, this class leads students through four activities as they simultaneously develop their mastery of AI tools:

Developing and marketing a new product or service. Students work in teams with community business partners, using a variety of AI chatbots and image generators to create and market a new product or service. Each student team chooses the company its members want to work with from a selection of multiple business partners.

Launching a business—Phase 1. Over three weeks, students launch a business starting with just 50 USD. They are invited to use their favorite AI chatbot to develop their idea and lead them through tasks to generate revenue. However, there is a one catch: During this phase of the project, students must do exactly what the chatbot tells them to do, without conversation.

Launching a business—Phase 2. They repeat this process over the next three weeks, again using just 50 USD. However, this time they can have conversations with the chatbot to refine their strategies.

Designing or redesigning a product or service. For the final project, students each research the offerings of their individual dream employers. They then use a variety of AI tools either to reimagine new versions of existing products or services from these employers or to develop completely new ones. They each then work with AI to develop a portfolio that highlights their recommendations to their dream employers. Students share these portfolios with the class, instructor, and the employers they have selected.

Winkel does not just ask students to use AI for these projects, but also leverages AI tools himself to build the course. More specifically, he uses AI platforms such as ChatGPT-4, Claude, Perplexity, and You.com to do the following tasks:

• Design the entire course structure.
• Choose all materials.
• Grade submitted work and provide robust, instant feedback to students.
• Create, aggregate, and analyze all discussion threads on the learning management system, so he knows how well students are learning the concepts and where they are struggling (both individually and as a group).

For example, to design Entrepreneurial Creativity with Artificial Intelligence, Winkel crafted a detailed prompt, which he submitted to all four AI tools. In the prompt, he asked each AI platform to “act like a seasoned curriculum designer with over 20 years of experience specializing in entrepreneurship education, with a particular emphasis on experiential learning methodologies.”

After providing that context, he then asked each platform to craft “an in-depth and engaging course outline” for a new undergraduate course linking entrepreneurial creativity and the use of AI tools. In his prompt, Winkel included key details about the course, including:

• Class timing and duration (75-minute sessions held twice a week for 14 weeks)
• Audience (sophomores and juniors who are interested in starting their own businesses, but who will most likely work for existing companies after graduation)
• Learning objectives (the development of skills such as strategic ideation, business modeling, customer interviewing, prototyping, and experimentation)
• Desired projects (the four mentioned above)

After receiving responses from all four platforms, Winkel then asked each AI tool to combine the best elements from all four outputs into a single course outline. After reviewing all four outlines, he determined that the one that Claude generated was the most robust; he used that as his template going forward, adjusting Claude’s work where he saw the need for improvement. He followed a similar process to create lesson plans, learning modules, quizzes, and interactive activities for each course session.

Through deliberate and sustained microefforts, our AI literacy will improve over time. As it does, so will our comfort levels in using a range of AI tools for different purposes in our classrooms.

In addition, he asked AI to define learning objectives for each activity. Then, he asked the tools to create multidimensional assessment strategies that encompassed reflective journaling, peer feedback, role-plays, and other mechanisms to track student engagement and skills development, as well as evaluate individual and group performance. Finally, he collaborated with the AI to craft rubrics. He then asked all four platforms to grade student submissions and provide developmental feedback based on those rubrics, before again asking Claude to combine the outputs.

In all cases, Winkel double-checked the work the AI generated, and he added his input where he felt it necessary. But he spent minutes, not days, completing these tasks. That meant that he could spend his time doing what he considers higher-value tasks: coaching, mentoring, and interacting with students.

AI and the Future

As educators, we have a duty to continually learn new tools and approaches—especially those our students must learn to be competitive in the workforce. That said, we realize that becoming experts in AI is an impossible task—new tools are emerging at such a fast pace that we could never master them all, no matter how much time we spent trying.

The good news is we don’t need to achieve mastery—we need to achieve literacy.

For example, as we teach entrepreneurship, we do not ask students to solve multiple problems at scale from the start. Rather, we ask them to solve a single problem for just one person, then for another person, and then for a third. In this way, they can apply what they learn along the way as they work toward scaling their solutions to larger audiences.

AI literacy works the same way. We can learn to use a tool for one task, and then for a second. We then can do the same with a second tool, and then a third. Slowly, through such deliberate and sustained microefforts, our AI literacy will improve over time. As it does, so will our comfort level in using a range of AI tools for different purposes in our classrooms.

The longer we wait to immerse ourselves in AI’s present and future possibilities, the more risk we create for our students and institutions. Where technology is concerned, remember that even a less-than-ideal action, swiftly executed, stands a chance of success. Inaction stands no chance of success at all.

In closing, an acknowledgement: AI, of course, aided us as we wrote this article. Doan provided Perplexity with the article’s context, intended audience, and desired outcome to generate a rough outline, which we then perfected. Then, once we had a completed draft, we ran that draft through Hemingway Editor and Grammarly.

As we say above, AI is more than a tool. It is a game-changing technology that will inspire us to teach, write, think, and work in completely new ways—but only if we are open to its possibilities.