“The short answer is: because it’s already reshaping the world our students are living in and because it holds the potential to dramatically improve the way students engage with mathematics.

AI can help students receive just-in-time feedback, explain their reasoning, reflect on their learning, visualize abstract concepts, and practice skills at the appropriate level. It can also support teachers with lesson design, differentiation, assessment, and workload reduction. AI in math education offers a world of benefits.

AI can also support productive struggle—a core component of deep math learning. When used well, AI can help students wrestle with problems rather than shortcut their thinking. It can guide rather than give away, probe rather than tell. It can give students agency to explore, test, and reflect, which is vital for building conceptual understanding.”

“How can AI be used to enhance learning without becoming a crutch? (e.g. ensuring students still practice problem-solving and not just ask the AI for answers)

What about accuracy and trust? AI tools can make mistakes or “hallucinate” answers. How do we teach students to verify AI outputs and think critically?

Does AI compromise academic integrity? Tools like Photomath have raised cheating concerns, but new AI tutors aim to guide rather than give away answers. How do we strike the right balance?

What is the teacher’s role in an AI-enabled classroom? With AI tutors and lesson generators, teachers might worry about being sidelined. How do we use AI as a supportive ally rather than a replacement for teacher expertise?

“Math teachers who want to understand how AI fits into their world need help envisioning how students will engage with mathematics in an AI-shaped future. Without an understanding of what’s possible, teachers risk being unprepared to support changing student needs. In this sense, vision isn’t a luxury, but rather the essential first step toward any meaningful integration of AI in instruction.

To spark this vision, let’s explore three highly plausible near-future classroom scenarios: one in upper elementary, and two in secondary math. The featured tools are fictional, but their capabilities are modeled on existing or rapidly advancing technologies, grounded in AI developments we’ll likely see in classrooms soon.”

“There persists a glaring paradox when it comes to AI in math instruction,. On one hand, AI is making groundbreaking strides in mathematical research and complex computations. On the other, AI is often derided as "bad" at math. Consequently, reports of its mathematical abilities seem strikingly contradictory. This raises an important question: What exactly is AI capable of in mathematics, and how can we leverage its strengths while mitigating its weaknesses?

The sensationalist headlines proclaiming ‘AI is bad at math"‘ were primarily based on evaluations of earlier models, often GPT-3.5. As such, these assessments are largely inconsequential. AI models are certainly not error-free today, but these headlines largely fail to reflect the dramatic advancements seen in the latest iteration of AI large language models.”

“There is no single “right” way to integrate AI tools into math instruction. However, I encourage teachers to follow a natural progression that begins with exploring how AI can assist with teaching tasks and gradually shift toward how students use of AI can enhance learning. This approach allows teachers to build confidence and competence before asking students to engage directly with these tools.

As math teachers become more comfortable with AI tools, they can move from task offloading to transforming instruction. Educators can gradually integrate AI to save time, enhance student thinking, and deepen learning outcomes if teachers follow a thoughtful progression. While the landscape of AI tools continues to evolve, this framework can serve as a starting point for purposeful, pedagogically grounded integration.”

“To really get benefit from metacognitive strategies, create a classroom culture that values process over just answers.

Celebrate when a student explains something well or finds a mistake and corrects it. Maybe have a “favorite mistake” segment where you actually use an AI to generate a mistake, a student fixes it, and you commend that process.

Make sure students know that struggle is part of learning – as one Edutopia article title put it, students “don’t need an answer, they need help with the process.” Reiterate that AI is there to help with the process, not just to give answers.”