Conference Takeaways: Lessons Learned from Miami Dade College at Teaching & Learning with AI

Last week, our team presented alongside Miami Dade College at the Teaching & Learning with AI Conference in Orlando, where educators from across the country came together to talk about one question that feels increasingly important in higher education right now:

How can AI support learning in ways that actually improve student outcomes?

During our session, Victor Calderin, Associate Professor of English, shared how Miami Dade College has been exploring that question inside its online learning programs, particularly in courses where keeping students engaged has been an ongoing challenge.

The challenge many online programs are facing

One of the biggest challenges Miami Dade has seen, especially in asynchronous courses, is student drop-off midway through the semester.

Students begin strong, but participation starts to decline, assignments go unfinished, and too often learners disengage before completing the course.

What stood out most was when students were doing the work: late at night.

A large percentage of activity was happening outside the hours when instructors, tutors, or other academic support systems were available.

For institutions focused on student success, it raises an important question: how can we better support students when they’re learning independently?

Rethinking how AI shows up in learning

A big theme throughout the conference was that many AI conversations in education have focused on productivity and answer generation.

But learning is a much messier process than simply getting to the correct answer.

In Miami Dade’s case, the focus was on creating learning experiences that gave students more opportunities to engage with course material in an active way, through practice, dialogue, and adaptive feedback.

Rather than one-size-fits-all interactions, each student moved through a learning experience that adapted based on their responses and understanding as they progressed.

Miami Dade College Online adopted Kyron to support these goals and Victor shared some initial results from this integration.

What the early results showed

After expanding Kyron implementation across online English courses, Miami Dade began seeing encouraging patterns.

Some of the early data shared during the session included:

• 1,000+ students engaging with learning modules
• More than 50% of engagement happening outside of when traditional support was available
• 82% of students reporting increased confidence with the material
• 4-6% increase in overall pass rates across courses

Victor also shared outcomes from his own sections, where he saw zero student withdrawals, zero D grades, and only one failing student across two course sections.

The bigger takeaway

One of the most interesting parts of the session wasn’t necessarily the data itself.

It was the reminder that as institutions continue adopting AI, the conversation needs to move beyond what AI can do and focus more on how AI can meaningfully support learning.

Education has never been about simply getting answers faster.

It’s about helping students practice, think critically, work through uncertainty, and build confidence over time.

That was probably the biggest takeaway from the conversation in Orlando.

As AI continues finding its place in education, the most important question may not be how do we bring AI into the classroom?

It may be:

Are we designing AI experiences around efficiency — or around learning itself?