Summer School (The Good Kind)
Every year around this time, teachers start doing that particular mental math that only educators understand. How many days left? How many grades to enter? How many “are we doing anything today?” questions can one human absorb before the final bell? Summer is close, and the collective exhale is almost audible from here.
Most teachers I know fill that summer with a genuinely good mix of things: a conference or two, some professional reading they actually want to do, travel, family, and the radical act of sleeping past 6 AM. All of that is necessary and right. But I want to make a small case for adding one more thing to the list, and I promise it does not involve a syllabus or a rubric.
Get curious about GenAI.
Not in a high-stakes, district-mandate, someone-is-watching kind of way. Just curious. Summer is exactly the right time for this because the stakes are low. Nothing you try will scramble your fall classes. No 7:45 class depends on the quality of the output. You can experiment, fail, laugh at the results, and try again. That is almost never the condition under which teachers get to learn anything, and it is honestly the best condition for learning there is. Actually, the work we have done on ArtTEAMS grant for four years did exactly that each summer- but that is a story for another time. Although if you are interested our first publication just came out here.
Here are four things worth trying. These are just examples, feel free to riff…
Punch up an assignment you never had time to fix. We all carry them. The assignment that is fine, technically, but has been quietly bothering you for years because you know it could be better. Give a GenAI model the context, the learning objectives, and what you actually want students to get out of it, then see what it generates. I did this recently with an assignment where I always wanted students to think about instructional grouping using both assessment data and social and behavioral dynamics. I never had time to write meaningful student descriptions that would give the grouping decision real texture. This year I used GenAI to create those descriptions, and the assignment became substantially richer for it. The model did not replace my thinking. It handled the production work that had always been the obstacle.
Write a subject-specific AI policy. Counterintuitively, GenAI is quite good at helping you write a policy about GenAI. Start by feeding the model your district or institution’s existing policy, then describe the specificity and intentionality you want. I took this a step further and created differentiated expectations by assignment type: some asked students not to use AI at all, some encouraged proactive use, and some allowed it with disclosure. The clarity that came out of that process saved real class time and preempted a lot of the ambiguity that tends to eat up energy in the first weeks of a semester.
Make a document or presentation. The productivity tools built into or adjacent to GenAI have gotten genuinely good. I recently used one to produce a one-page project explainer that came out polished enough that I only needed to read and edit rather than draft from scratch. You still have to read it carefully and make it yours. But production time drops significantly, and for teachers who spend hours on materials that students may glance at for forty-five seconds, that math is worth considering.
Build a piece of software. This one surprises people, but it should not. GenAI is remarkably capable of creating small, functional, classroom-specific applications. I built an HTML-based reading fluency tracker that listens to a student read and another that scaffolds phonics practice. Both came out well beyond what I could have produced working alone, and neither required me to know how to code. The tools you actually want for your specific students, in your specific context, are more within reach than most teachers realize.
None of this requires a workshop. None of it needs to be assessed or reported. The only goal is to get your hands on the tools in a context where playing around is the whole point. That is how you develop genuine intuition about what these tools can and cannot do, which turns out to be far more useful than any training session.
So yes, go to the conference. Read the book. Take the trip. Sleep in. Spend lots of time with family and friends. Grill often. Drink occasionally.
And somewhere in there, try a few things. No pressure, no deadlines, no one watching. Just you, a curious question, and a summer with enough room to find out what happens. Or not, after all, it is up to you.
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