As AI becomes an increasingly important part of education, High School Math teacher Özge Kabakcı has embraced the opportunity to explore how it can support meaningful learning. With 17 years of experience in education and advanced academic training in mathematics, Özge helped explore how generative AI can meaningfully support student learning in collaboration with researchers at University of Pennsylvania’s The Wharton School.

 

In the study, math students from a High School in Turkey, were assigned to different learning conditions to compare how unrestricted AI, which provided direct answers, and a tutor-style AI, which guided students with questions and prompts, affected their math performance. The findings suggested that the impact of AI depends less on the technology itself and more on how it is used. Students who relied on the unrestricted tool performed lower than those without AI access, which Özge describes in clear terms: “if you rely too heavily on AI by skipping real thinking or practice, or essentially using it as a crutch you’ll inevitably stumble once it’s gone.” In contrast, the tutor-style AI—built to ask questions and keep students engaged in the process—supported learning at a level comparable to traditional instruction, suggesting that structure is what determines whether AI helps or hinders.

 

What stood out just as much was how students experienced their learning. Özge notes that “both AI groups assumed they were learning (and achieving) more than they really were,” highlighting a gap between confidence and actual performance. Rather than seeing this only as a problem, she frames it as an opportunity for education: helping students better understand what real learning feels like, not just what quick answers feel like.

 

For Özge, the key shift is in how AI is positioned in the classroom. She encourages students to treat it as a “thinking partner”—a tool that supports reasoning instead of replacing it. As she puts it, “it can really boost your performance if you know how to use it,” but only when students stay actively involved in the thinking process rather than outsourcing it.

 

She also connects this to a broader idea about learning and cognition. “Once we start asking ourselves, ‘Do I really need to do any of these calculations by hand anymore?’ we risk sidelining the part of our brain responsible for mathematical operations,” she explains. For her, this makes intentional use essential: AI should extend thinking, not replace it.

 

In her classroom, this translates into practical strategies—encouraging students to test prompts, explore different outputs, and use AI for guided exploration rather than final answers. The goal is not to restrict the use of AI but to help students understand when it is strengthening their thinking, and when it is doing the thinking for them.

 

Ultimately, Özge sees AI as a powerful addition to education when used thoughtfully. By combining her experience in the classroom with research, she continues to help shape conversations about what meaningful learning can look like in a world with AI; one where technology is a supportive tool for learning, understanding and critical thinking.