It’s the second week of school, you have 160 students across five periods, and you get 50 minutes with each of them. On Tuesday, one of your quieter juniors sits down in a way that tells you something’s off, and by fifth period you’ll have forgotten because Tuesday is also last week’s quiz to grade, the substitute’s coverage to sort, polynomials to teach, and two families you promised to call. The relational work you know matters most keeps getting displaced by the math of the job — one teacher, 160 students, 50 minutes, and a nervous system that can only track so much at once.
There’s a way to close that gap without adding to your load, and it runs about ten minutes a day. Chrizia Dela Rosa, California’s Teacher of the Year, built it inside a public high school math class: she uses AI to surface patterns across all 160 students so she walks in the door already knowing who needs a check-in that period.
If you have ten minutes tomorrow
Try this before you build anything more elaborate:
- Build a two-question Google Form. How are you feeling today? and Is there anything I should know? Post it as the first thing students see when they log in.
- Read every response before class. Not skimming — actually reading. For a class of thirty, that’s about five minutes.
- Notice one student you’d have otherwise missed and leave a discreet post-it on their desk: I’m here if you want to talk. Then move on with the day.
That’s the practice. Everything below is scaffolding on top of it.
The 3-Part Daily Check-In System
1. The first five minutes: mood, sleep, food, and one open door
Chrizia opens each period with a Google Form where students choose a word on a mood meter built with an X and Y axis (she’s a math teacher, so of course she made it graphable). The form then asks about sleep, food, and whether anything is bothering them, and closes with the question that carries the whole system: Is there anything else you need me to know?
The reason it works is that you’re asking about emotional and somatic state — how the body is showing up before you ask it to think — which is Human Intelligence at the emotional and somatic layers: affective awareness and body awareness. The research base for daily social-emotional learning (SEL) practice is strong: a meta-analysis of 213 school-based SEL programs covering 270,000 students found an average 11-percentile-point academic gain compared to peers, alongside significant reductions in conduct problems (Durlak et al., Child Development, 2011).
When to run it: every day, first thing. Not weekly. Not on Mondays. Every day.
2. After school: hand the pattern-matching to AI
Reading 160 individual responses is doable; finding the pattern across 160 responses in the fifteen minutes before dinner is not. So Chrizia reads every entry herself, then pastes the batch into an AI tool and asks it to surface trends — which students are trending down over the last week, what emotional patterns are showing up in period three that aren’t showing up in period one.
The emerging research on AI in SEL identifies exactly this use case as high-value, with AI handling the aggregation so educators can respond at scale to emotional data (Sethi and Jain, Journal of Research in Innovative Teaching & Learning, 2024). The same authors flag the risk of substituting automated responses for the human presence that made SEL work in the first place, and this system does the opposite: AI clears the analytical bandwidth so you have more presence to spend, not less. The broader frame this how-to sits under, Human Intelligence in the age of AI, is the deeper argument for why that distinction matters.
When to run it: after school, once a day, fifteen minutes.
3. The last five minutes: student self-reflection
At the end of each period, Chrizia runs a short exit form asking students how they felt like a student today, whether they were productive, whether anything got in their way, and whether they have any feedback for her.
The closing loop teaches the kind of self-awareness that student regulation depends on, and it hands you real-time feedback on your own teaching, which changes what you plan for tomorrow. If you cut it for time, the students will ask for it back — one of Chrizia’s told her, “Sometimes this is my only class where I can just pause.”
When to run it: every day, last five minutes.
The move that ties it all together
The point of the system isn’t the data — it’s the post-it note. Within a week or two, students disclose things in that anything else I should know field that Chrizia would never have surfaced otherwise, and she writes a quick sticky, I’m here to listen if you want to talk, and drops it discreetly on the desk on her way to the next part of the lesson. That’s the whole trick.
AI handled the pattern. You handled the person.
If a full Google Form isn’t feasible on day one, Breathe for Change’s two-word check-in is a pared-down entry point that gets you 60% of the value in 30 seconds, and for a fuller view of where AI fits into classroom practice more broadly, AI in today’s classrooms is a Breathe for Change companion piece on the topic. The classroom-management frame beneath both — what teacher prep never taught most of us, and why Chrizia’s system works because of it — is covered in the thought-leadership sibling to this piece.
Educators who take practices like this one furthest tend to have studied the frame underneath them, and that work sits inside the William Jewell College Master’s of Science in Education (M.S.Ed.) in Transformative Teaching & Learning, in partnership with Breathe for Change, where educators learn to design whole-child systems that make the relational work sustainable rather than heroic. Learn more about the M.S.Ed. here.
Want to go deeper? Listen to Dr. Ilana Nankin on A Work of Heart, the Breathe for Change podcast, where she walks through the daily check-in system, the post-it technique, and what students say the practice has meant to them.
