Designing the Future

Higher education is facing a quiet crisis, one not driven by enrollment cliffs or political pressures, but by the widening gap between innovation and implementation. It’s the kind of crisis that doesn’t warrant emergency meetings or task forces, just a lot of awkward silences in department meetings. While headlines tout the promise and peril of artificial intelligence, campus conversations remain split. Some faculty view AI tools as a looming threat to academic integrity or job security. Others see them as another tech trend unlikely to live up to the hype. After all, nothing says ‘disruptive innovation’ quite like a tool that can write a syllabus faster than most committees can schedule a meeting to discuss writing one.

But a growing number of instructional designers are quietly rewriting that script. These are the people who shape learning experiences behind the scenes, and they recognize that AI is not just about chatbots or plagiarism detection. It’s about fundamentally rethinking how we design, deliver, and improve education.

This work isn’t something that makes the front page. It doesn’t fit neatly into either polemic of utopia or dystopia. But it matters because in a time when institutions are expected to do more with less, to offer quality, flexibility, personalization, and relevance, educators need tools that help them meet those expectations without burning out.

And that’s exactly where AI, when used wisely, comes in.

This column tells the story of one such educator: Nadine Schreiter, an instructional designer at the University of Florida’s College of Journalism and Communications. With more than 20 years of experience in curriculum development, online learning, and faculty training, Schreiter represents a new kind of change agent. She’s skeptical enough to question every tool, but curious enough to try it anyway. That combination of skepticism and curiosity is more exciting than a parking spot near your office.

What makes her work notable isn’t just her technical fluency. It’s her conviction that instructional quality and innovation can coexist, that a rigorous, student-centered design process doesn’t need to be replaced by AI but can be enhanced by it.

“AI isn’t here to replace educators; it’s here to support them,” Schreiter says. “Used thoughtfully, it can help us work smarter, not harder, and focus more deeply on the creative, human-centered aspects of learning design.”

From Skepticism to Strategy

Like many educators, Schreiter was initially wary of generative AI tools. But her perspective shifted once she saw their potential to streamline tasks like writing rubrics, aligning assessments with objectives, and revising outdated course materials. She began experimenting with tools like ChatGPT, testing small changes that yielded big improvements, not just in efficiency, but in quality.

One such test involved “stress-testing” assignments. By prompting AI to simulate student responses to a set of instructions, Schreiter identified confusing phrasing, hidden assumptions, and alignment issues. The approach allowed her to suggest focused improvements that enhanced clarity and reinforced course goals.

“It took just minutes,” she says, “but the insights were invaluable. And faculty were more engaged when they saw how these refinements helped students succeed.”

Building AI Into the Design Process

What makes Schreiter’s approach especially noteworthy is her deliberate, ethics-driven process. AI is not a shortcut, she insists, but a strategic partner. She uses it to compare learning objectives with actual course materials, ensuring alignment from module to program level. She’s also built an AI prompt library that allows her to replicate quality assurance work across different courses quickly.

Her rubric development process offers a case in point. Instead of using generic templates, she uses AI to draft task-specific rubrics that align directly with course outcomes and instructional priorities. Work that previously took hours can now be initiated in minutes, with faculty input shaping the final product.

But Schreiter is clear: AI must not overshadow the expertise of subject matter experts. “I’m always asking, ‘How much is too much?'” she says. “We can’t let the human element, the voice and vision of the faculty, be drowned out by efficiency.”

She also stresses transparency, “I tell every faculty member I work with exactly how I use AI. It’s not a secret sauce; it’s part of the conversation.”

Changing Minds, One Module at a Time

To address the fear of obsolescence among faculty, Schreiter takes a “baby steps” approach. Instead of overhauling entire courses, she collaborates with instructors to rework just one module or assignment using AI. The result is often a shift in mindset.

Faculty who were once skeptical report enjoying their teaching more. Students, in turn, respond with higher engagement. “Once they see the impact,” Schreiter says, “they want to do more.”

Her weekly “Funday Fridays,” informal sessions where she explores new AI tools and shares findings with her team, have become a model for curiosity-driven innovation.

“It’s brought fun back into my work,” she says. “It’s not just about efficiency. It’s about discovery.”

The Future of Course Design

Looking ahead, Schreiter sees AI becoming integral to personalized learning and continuous improvement in course development. She’s especially excited about tools like “Connectors” that can integrate AI directly with curriculum maps and institutional standards, enabling more sophisticated curriculum analysis.

These tools, she says, may eventually allow instructional designers to surface alignment issues, curricular redundancies, or missing scaffolding with a few prompts. This is a process that currently requires hours of cross-referencing and meetings.

“If AI can help us ensure that every piece of a course is aligned, intentional, and transparent, that’s a game changer for quality assurance,” she says.

She also believes higher education must do more to prepare administrators, designers, and instructors to use AI ethically and responsibly. “We’re shaping the future workforce,” she says. “We have a duty to teach our students and colleagues how to use these tools with intention.”

Getting Started: Practical Tips for Educators

For educators who are curious but hesitant, Schreiter has a simple message: just start. “You don’t need to master everything at once,” she says. “Pick one small area, a rubric, an assignment prompt, a discussion question, and explore how AI might help.” Think of it as dipping your toe in the AI pool instead of doing a cannonball—much less chance of a painful belly flop.

She offers several quick wins:

• Revise a learning objective: Ask AI to clarify or reword it using Bloom’s Taxonomy.
• Brainstorm discussion questions: Provide a topic and let AI generate creative prompts.
• Draft a grading rubric: Share assignment criteria and ask AI to structure a rubric.
• Simplify complex content: Have AI explain a concept in plain language.
• Generate real-world examples: Use AI to connect abstract ideas to practical contexts.

These aren’t theoretical ideas. Schreiter has used them herself and shared them with dozens of faculty. The response has been overwhelmingly positive, not just for saving time, but for enriching the teaching process.

Final Thoughts

In an era when higher education is increasingly asked to justify its value, improve its agility, and modernize its practices, often all at once, Nadine Schreiter’s work offers a roadmap. It’s not about using AI to replace instructors or automate learning. It’s about designing with more intention, more precision, and yes, more joy.

Her message to fellow educators is clear: AI isn’t the enemy of academic rigor. In the right hands, it might be its greatest ally.