Learn about how Ball State University’s Teaching Innovation Team is joining a multi-year research study to examine the use of AI in curriculum design.

Ball State University’s Teaching Innovation Team, part of the Division of Online and Strategic Learning, was recently selected to participate in the QM+iDesign Human–AI Collaboration in Online Program Design initiative, a national, multi-year research study led by Quality Matters (QM) and iDesign.  

The Division of Online and Strategic Learning selected two programs in the Miller College of Business for participation: the MS in Business Analytics (MSBA) and the MS in Accounting (MSA). Together, these programs allow us to study not just what works, but how and when it works. 

Read the press release announcing this initiative.

Designing What Comes Next: AI, Alignment, and the Future of Course Design 

Over the past year, conversations about artificial intelligence in higher education have accelerated quickly. Most of those conversations focus on students, how they use AI, what it means for assessment, and how faculty respond in the classroom. But there’s another side of this shift that is just as important, and perhaps less visible: how AI is beginning to shape the way we design courses, align curricula, and ensure academic quality across programs. 

At Ball State, our Teaching Innovation Team has been exploring exactly that space. 

The initiative brings together a small group of institutions across the United States to examine how artificial intelligence can support and strengthen program-level curriculum design, as higher education faces increasing pressure to scale online and hybrid programs while maintaining coherence, alignment, and academic rigor. 

Following a competitive application process, only nine institutions were invited to participate. Ball State is one of them. That matters. It means our work is part of a broader national effort to understand how human expertise and AI can work together in meaningful, responsible ways and how institutions can maintain quality while adapting to new tools and new expectations. This work places Ball State in a meaningful position, not only participating in a national conversation but helping shape it.

What is Curriculum Alignment, and Why Does it Matter? 

At its core, curriculum alignment is about coherence. It asks a deceptively simple question: 
Does what we say students will learn actually connect to what we teach, and how we assess it? 

In practice, this means carefully mapping relationships between: 

• Course-level learning outcomes 
• Program-level outcomes 
• Assignments and assessments 

This process is essential for accreditation, program review, and continuous improvement. But it is also complex, time-intensive, and often difficult to scale across entire programs. That’s where AI begins to enter the picture, not as a replacement for faculty expertise, but as a potential support for the alignment process.

Across higher education, there is growing recognition that while AI may help accelerate parts of this work, maintaining quality, rigor, and disciplinary nuance still depends on human judgment. One of the central questions of this initiative, and of our work at Ball State, is where that balance lives in practice.

Three Ways of Doing the Same Work 

As part of the QM+iDesign initiative, we are examining three different approaches to curriculum alignment: 

• Manual mapping, using traditional tools and human review 
• Human–AI collaboration, where AI supports early-stage alignment through prompting and iteration 
• AI-enhanced tools, designed specifically for alignment workflows 

By working across these approaches, we can ask more meaningful questions: 

• Where does AI actually save time, and where does it not? 
• What kinds of alignment gaps or redundancies become more visible? 
• How do we maintain academic rigor while introducing automation? 

Across higher education, there is growing recognition that while AI may accelerate aspects of design work, maintaining quality, rigor, and disciplinary nuance still depends on human expertise. What makes this work especially valuable is that it is happening in real programs, with real curricular structures, not in abstract or simulated environments. 

Extending the Work at Ball State 

In parallel with the national initiative, our Teaching Innovation Team is conducting an institutional research study focused on how instructional consultants integrate AI into curriculum alignment workflows. 

This study examines a topic often overlooked in conversations about AI in higher education: professional practice. 

Rather than focusing on student use of AI, we are examining how instructional designers: 

• Make decisions while using AI tools 
• Evaluate efficiency and usability 
• Balance speed with disciplinary nuance and academic judgment 

The study is grounded in our day-to-day work as instructional consultants. It is designed to generate practice-based evidence, insights that are directly applicable to how we support faculty and programs at Ball State. 

As outlined in our research brief, the goal is not simply to test whether AI “works,” but to understand how it operates within real instructional design workflows and shapes professional decision-making. 

Why This Matters for Faculty 

For many faculty, AI can feel overhyped or overwhelming, or simply one more thing to navigate. 

This work is not about asking faculty to adopt new tools for the sake of innovation. Instead, it is about strengthening something that already matters deeply: clarity, coherence, and intentional design in our courses and programs. 

If AI can help: 

• Surface misalignments more quickly 
• Support clearer connections between outcomes and assessments 
• Reduce time spent on repetitive mapping tasks 

Then it has the potential to free up more space for what matters most: disciplinary thinking, student engagement, and meaningful learning experiences. 

At the same time, our work is grounded in a clear principle: AI should support—not replace—expert academic judgment. Some aspects of curriculum design require context, nuance, and deep disciplinary knowledge that AI cannot automate. One of the most important parts of this project is understanding where that line exists. 

A Quiet Kind of Leadership 

One of the things I value most about this work is that it reflects how innovation often actually happens in higher education—not through large announcements or sweeping changes, but through careful, collaborative, and sometimes invisible work, testing ideas, refining processes, and asking better questions. 

This initiative grew out of a desire to make our work at Ball State more intentional, more evidence-informed, and more forward-looking. It also reflects a willingness to take thoughtful risks: to explore new tools, to engage in national research conversations, and to position our institution as part of shaping what comes next. 

It also reflects something larger: Ball State being part of a small group of institutions actively contributing to how AI is understood and implemented in program design at the national level. 

That work is never individual. It is made possible by a team that is deeply committed to supporting faculty and programs across the university, and by partnerships, like those with the Miller College of Business, that allow us to engage in meaningful, program-level work. 

Looking Ahead 

We are still in the early stages of this project, and many of our most important insights are yet to come. But even now, one thing is clear: the conversation around AI in higher education is evolving. It is moving beyond questions of access and policy toward deeper questions of design, quality, and practice. 

Ball State has an opportunity to be part of that shift, not by adopting AI uncritically, but by engaging with it thoughtfully, rigorously, and in ways that align with our values as educators. 

That is the work we are doing. And it is work that will continue to evolve, alongside the faculty, programs, and students we serve.