'What Do You Need Wednesday?'—The Intersection Edition
(Still) "...every tiny thing by one percent..."
Much of what we know about learning comes from careful research conducted under ideal conditions—but classrooms, assignments, and students’ lives are anything but ideal. This week’s WDYN sits at that intersection, where evidence meets design and intention meets reality. Across student study habits, AI-inflected assignments, and elementary math classrooms, a shared theme emerges: learning holds when strong systems are thoughtfully extended. The work ahead is noticing where those systems already exist—and deciding how to build on them.
🏎️ Something to Think About—Do Study Strategies Survive Real Life?
Research on studying is unusually clear: retrieval practice beats rereading, spacing beats cramming, and highlighting mostly wastes time. The problem isn’t the findings, it’s the conditions. Psychology labs are tidy; students’ lives are not. That tension has surfaced repeatedly in our early work with the CTL Student Advisory Board, where students wonder whether “research-backed” strategies still work once homework collides with phones, practices, jobs, and fatigue.
A recent synopsis from our friends at Learning and the Brain highlights a study of nearly 2,500 Spanish students (grades 7–10) examining how students actually study at home and how those habits relate to grades. The reassuring news: retrieval practice, elaboration, quiet study spaces, and strong self-efficacy correlate with better outcomes, while rereading and highlighting do not. The more revealing finding is that spacing shows no clear grade advantage. That doesn’t mean spacing fails—it suggests that real spacing depends on curriculum-level design, not just student effort. Some study strategies are within students’ control; others quietly depend on how teachers structure learning. You can unlock these discrepancies through one simple trick: just ask them.
Try this soon: Ask students how they studied for your last assessment, then notice which strategies they chose—and which ones your course design made realistic.
🤖 Something to Do—Design for AI, Don’t Just Defend Against It
As generative AI becomes a default writing companion for students, the real instructional question isn’t whether they’ll use it, but how intentionally we’ve designed the assignment. Literacy scholar Amy Stornaiuolo offers a practical framework for answering that question, helping teachers decide when AI should support learning, when it should be resisted, and when it should become the object of study itself. Her five-part framework—assistive, resistive, creative, rhetorical, and critical—begins with a deceptively simple move: clarify what you want students to learn before deciding how AI fits.
Some assignments invite AI as a thinking partner or feedback tool; others deliberately foreground student voice, local knowledge, or lived experience in ways AI can’t easily replicate. Still others ask students to use AI creatively or rhetorically—and then analyze, critique, or explain what it produced. The power of the framework isn’t choosing the “right” category, but being explicit about instructional intention. When teachers don’t decide in advance, students will—and often in ways that flatten learning rather than deepen it. Thoughtful design turns AI from a policing problem into a pedagogical one.
Try this in January or February: Take one upcoming writing assignment and decide which role AI should play in it (if any), then name that intention explicitly for students before they begin
⚡ Something to Remember—Fluency Is What Frees Thinking
In this widely read essay, engineer and learning scientist Barbara Oakley describes her unlikely path from math-phobic literature kid to professor of engineering—and the lesson it taught her about learning. Insight alone wasn’t enough; progress came through sustained practice that built fluency, until ideas no longer had to be consciously re-assembled. Without that fluency, students are prone to illusions of competence: I understood it in class, so why can’t I use it now?
That truth was on full display this week in CTL observations of 3rd grade teacher Cat Ryan’s classroom. Students moved through math fact work with speed and confidence, not because understanding had been skipped, but because it had been consolidated. The fluency freed cognitive space for problem-solving, explanation, and strategy—not the other way around. This is the part we sometimes forget: memorization and repetition aren’t intellectual shortcuts; they’re what make higher-order thinking possible. Understanding explains why something works. Fluency ensures students can actually use it when it counts.
Try this ASAP: Notice where students are burning cognitive energy on basics, and ask whether greater fluency there would unlock better thinking elsewhere.
🧱 The Last Word—When New Tools Extend Old Systems
The Last Word is a final offering meant to prime your thinking for the work ahead. Intentionally adjacent to the research-heavy resources we often share, it’s designed to be eclectic, a little playful, and quietly provocative. This week’s Last Word comes from an unexpected place: a short video introducing a new idea from LEGO.
Watch the new LEGO Smart Brick video and it’s easy to fixate on the novelty—sounds, sensors, responsiveness, even bricks that burp. But the more interesting move is structural. LEGO didn’t replace what already worked; it added a layer to one of the most powerful learning systems ever built: open-ended construction, imagination, and play. The intelligence isn’t in the tech alone—it’s in what the tech is layered onto.
That’s a useful lens for schools. Powerful systems like fluency, practice, discussion, and problem-solving don’t need disruption to stay relevant; they need extension. When new tools work, it’s often because they amplify what already matters rather than trying to reinvent it. It’s hard not to see a parallel with AI: its real promise isn’t replacing thinking, but adding responsiveness and flexibility to systems already doing meaningful cognitive work.
Sometimes the future isn’t a new structure at all. It’s an old one, with a smart brick snapped on top.