September 2025

Eight Tiny Experiments for Better Measurement

1) Labels Nudge Behavior  Call a student “behind” and you’ll triage. Call them “not yet” and you’ll coach. The same reality; different category; different action. Choose labels that produce the behavior you want… from you and from them. 2) Count Before You Calibrate  If you’re overwhelmed, start with a count: How many submissions? How many absences? Counting […]

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Say What You Mean, Measure What You Said

“Participation” can mean eye contact, chat posts, or peer feedback. Until you say which, you haven’t measured; you’ve wished. An operational definition is a promise to your future self: “When I see X, I’ll count it as Y.” That promise reduces arguments and increases learning. Before you reach for a rubric or a dashboard, sharpen

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Ship the Sample

We love talking about “the population”… all students, all courses, all outcomes. But you never hold a population in your hand. You hold a sample: this section, this semester, these ten advising notes. That’s not a bug; it’s the vehicle. A decent, honest sample moves you forward faster than a hypothetical population ever will. Treat

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Pick the Lens, Change the World

Some problems want bins. Others want measuring rulers. Calling students “on-time/late” highlights a threshold; logging “minutes late” reveals a gradient. Both are true… just different truths. Categories are for commitments (“Do we intervene?”). Quantities are for improvement (“By how much?”). If you’re stuck, ask: What conversation do I want to change: policy or practice? Then

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Statistics Is a Translation Layer

We don’t live in a clean lab. We live in the wild… half-filled forms, distracted students, glitchy software, good intentions. Statistics is not the hero of certainty; it’s the translator that turns mess into movement. When you ask a clear question and choose a measure that actually reflects it, you’re not “doing math,” you’re building

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