Beyond the Prompt: Why Ohio State’s Master of Learning Technologies Teaches Analysis Over Automation

Ohio State’s online course reinforces the importance of human judgement and connection, skills that are becoming more critical as AI becomes more capable.

Scrolling through LinkedIn, your feed may be flooded with quick win AI tutorials: how to write a better prompt, generate an infographic in seconds, or automate a syllabus. But as the initial novelty of generative AI fades, talent development professionals face a deeper challenge. Tools are evolving faster than policies, and today’s “how to” is outdated almost as quickly as it appears.

Rick Voithofer, faculty director of Ohio State’s online Master of Learning Technologies (MLT), believes the solution isn’t turning practitioners into AI power users. It’s helping them slow down, be strategic, and think. That approach is at the center of Artificial Intelligence and Education: Issues and Practices, a new MLT course that prioritizes critical inquiry over technical shortcuts.

Moving from Mastery to Mindset

Instead of focusing on what AI can do, the course helps students evaluate it. This begins by stepping back from the current moment and looking at AI’s history.
“We start pre-LLM, so people don’t think AI all of a sudden appeared with ChatGPT,” Voithofer explained. “If we think of AI as a collection of technologies, the technologies were already being used.”

As tools evolve, the ability to evaluate their use and impact becomes more valuable than any single platform feature.
“The idea is to give practitioners a set of analytical tools,” Voithofer said. “Not necessarily, ‘here’s 10 things you can do with AI,’ but here’s how AI might, for example, impact student evaluation.”

He added, “Hopefully, the way that we’re thinking about AI will give students not a template or a checklist but the skills to take the change that is here and make sense of it.”

Contextualizing AI for Diverse Roles

For Voithofer, it was essential that students could immediately apply what they learn to their own professional contexts.

“I spent a lot of time thinking about how this will be relevant,” said Voithofer. “How can students take what they learn into practice? That was an important principle.”

To support that goal, the course utilizes a Universal Design for Learning (UDL) framework. Students engage through different professional lenses — teaching, leadership, or instructional design and development — allowing them to apply concepts directly to their current roles.

“The course has been designed from the ground up with AI in mind,” said Jacob Bane, an Ohio State instructional designer who specializes in online course development. “AI is embedded throughout, and students choose the lens through which they would like to experience the assignments.”

Voithofer explained, “As they create the pieces of their final project through the course, they share it with their peers and are asked to respond from the perspective of their lens.”

That structure reinforces a vital truth for educators and learning and development leaders: AI is not one-size-fits-all. Its value and its risks depend on how and where it is applied.

Modeling AI Transparency

As AI reshapes how people find and engage with information, it is also forcing a reexamination of how knowledge is evaluated and communicated.

“We have to totally change our approach to how we evaluate knowledge,” Voithofer said. “The course asks students to engage with the practicality, the policy, and the ethics behind that.”

The MLT program addresses this by moving beyond syllabus statements toward intentional, transparent practice. Leveraging Ohio State’s four-level framework for AI use, each week includes clear guidance on expectations, and assignments explicitly define what AI can be used for.

This approach models the kind of clarity training specialists, instructional designers, and educators are increasingly expected to provide in their own work.

Finding the Heartbeat

The course reinforces the importance of human judgment and connection – skills that are becoming more critical as AI becomes more capable.

Voithofer leveraged AI to help structure his ideas for the course, noting that the technology excelled at “putting together a body and how the parts all fit together.”

“What it lacked was a heartbeat,” he said. “It’s still going to need the instructor, more personalization, and more humanization to make the course meaningful.”

This balanced perspective is intentional. During a cultural shift where people often map their own biases onto the term “AI,” Voithofer avoids the role of evangelist. Instead, he views the evolution of Ohio State’s 100 percent online Master of Learning Technologies curriculum as a duty to his students as the industry evolves.

“Doing this work is my responsibility to my students,” he concluded. “It’s hard to imagine AI not touching them in some way.”