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Still lighting learning fires's avatar

I'm always interested to see the way colleagues use terms and obviously we use them in ways that seem accurate and appropriate for our purposes. In this case I'm thinking about the term "proficiency". Your work here brought me back to an analogy I often use when thinking about the difference between grading products and assessing for proficiency. Learning to drive makes the contrast easy to see.

The road test is a performance on a route chosen by the examiner. If you make a mistake, you can take it again—just like in your class model. Passing the written exam and the road test earns you a driver’s license, which is basically the “passing grade.”

But all of us have met drivers out in the wild who clearly passed the test and, at the same time, don’t exactly radiate driving proficiency. That’s because the road test measures how you perform on that specific sequence of tasks on that specific day. It doesn’t capture how you actually drive across real contexts, real conditions, and real time.

True proficiency shows up in a broader, more varied record of behavior—how someone merges, anticipates, adapts, or manages unpredictable situations. Some of the new in-car AI tools that track long-term patterns probably give a better picture of driving proficiency than the official test.

That distinction feels relevant in assessment, too. When evidence is limited to products the instructor defines—exams, problem sets, a specific format—we’re really assessing performance on those products. Useful, important, but limited. When learners can show what they can do in multiple ways—and sometimes have the option to propose how to demonstrate it—we move closer to the kind of capability we might honestly call proficiency.

Maybe it’s time to rethink not just classroom assessments but driver’s licenses, too. A little proficiency assessment on the Kennedy Expressway here in Chicago at rush hour might produce some very different results.

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