As AI becomes more common in classrooms, K-12 district leaders face a defining question: How can technology strengthen, not dilute, the kind of feedback that drives lasting student learning?
That question guided a recent NSSI conversation between Keri Hubbard (Chief Program Officer, NSSI), Robert Hawke (Senior Director of Math, NSSI), and Jon Laven (NSSI mentor teacher and co-founder of Snorkl). Together, they unpacked how high-quality feedback, whether delivered by a teacher or supported by AI, helps students think more deeply, develop confidence, and build long-term understanding. For districts, summer learning provides an ideal space to test and refine feedback practices that can strengthen Tier 1 instruction throughout the year.
Design feedback that builds thinking, not compliance
Effective feedback does more than correct mistakes—it changes how students think. Jon described great feedback as “timely, asset-based, and designed to meet students in the moment of their thinking.” Robert added that when students are developing procedural skills, feedback can be direct. But when they’re working toward conceptual understanding, it must “start with a deep understanding of what the student is thinking” and then guide them to take the next step.
“The feedback that matters most is the kind that changes how students think about the next problem,” Robert said. “That’s what lasts.”
When students see feedback as recognition of their thought process, not just their answers, they begin to build the confidence and identity that sustain engagement across subjects—a reminder that great teaching is as much about developing teacher mindsets as it is about student skills.
Summer classrooms provide an opportunity to focus on this kind of thinking-centered feedback. With smaller class sizes and targeted goals, teachers can study student reasoning, refine prompts, and test routines that help students articulate not only what they know, but also how they learn. Those same practices can then inform year-round instruction across subjects.
Use AI to extend the reach of meaningful feedback
Robert acknowledged a practical reality every leader understands: time is finite. “It’s not that teachers should give feedback or AI should,” he said. “It’s whether five students get human feedback while twenty-five get none—or whether those twenty-five also get AI feedback that’s accurate most of the time.” When used thoughtfully, AI can extend access to timely, specific feedback without replacing the teacher’s expertise.
Jon emphasized that the most powerful use of AI is when it helps capture how students think, not just whether they’re right. Snorkl, the tool he co-founded, allows students to record their reasoning before AI offers feedback—a design choice that protects productive struggle and keeps student thinking at the center. “AI is extremely good at helping us think less,” he noted. “Our challenge is to help students think more.”
AI tools that surface patterns in student reasoning can make teacher feedback more strategic, especially when teachers can see where students struggle in real time. These kinds of insights help districts design summer learning programs that build momentum into the school year, ensuring that learning gains don’t fade once students return to regular classes.
“AI doesn’t know your kids,” Robert said plainly. “Teachers do. That’s what makes their feedback powerful.”
Adopt AI as part of instructional learning, not a tech initiative
Both speakers cautioned leaders against treating AI adoption as a compliance task. Robert described a coaching model grounded in experimentation: define what success would look like if a tool truly deepened student thinking, pilot small changes, collect evidence, and iterate together. “You can’t mandate thinking,” he said. “You can invite it. The same goes for adopting new tools.”
That iterative mindset mirrors the decision-making process leaders use when deciding whether to build or buy programs and tools for their schools. It centers professional learning, reflection, and local ownership—rather than top-down rollout.
Jon added that clear boundaries and modeling are key. Teachers should explain how and why AI is used for feedback, ensuring that it complements the relational work of teaching. As Keri reflected, “When teachers value student voice and reasoning, it shapes how students engage with AI—and with each other.”
The conversation underscored a core truth: AI cannot replace the teacher’s role in motivating and guiding student thinking—but it can help extend the reach of high-quality feedback. Districts that lead this work through a lens of instructional improvement, not technology adoption, will see stronger student reasoning, greater confidence, and deeper learning across subjects.
NSSI partners with districts to design summer programs and year-round systems that make this kind of feedback routine—timely, specific, and centered on student thinking.
This content is derived from a LinkedIn Live webinar hosted by NSSI featuring Keri Hubbard, Robert Hawke, and Jon. For more conversations like this, follow NSSI on LinkedIn to keep an eye out for future blog posts and LinkedIn Live events.
