Beyond Seat Time
What the "science of learning" can teach us about competency-based education
For over a century, American education has mostly organized itself around time. Students earn credits by sitting through a prescribed number of hours of instruction regardless of what they actually learn. This system was designed for administrative purposes, not as a way to measure learning. Educators and policymakers have made overtures about escaping this system for decades.
Competency-based education is the most promising alternative. Under this model, students only advance when they’ve mastered the material, not when the clock runs out. The logic is intuitive and the motivation is in the right place. But in practice, CBE has largely been confined to the margins, in things like credit recovery or alternative programs, where it often functions as a faster path to a passing grade or a credential rather than a more rigorous one to actual learning. Too often, the practical effect is to accelerate students through material quickly rather than ensure they have learned it deeply.
Moreover, the theory behind competency-based education doesn’t account for how students actually behave. Left to manage their own pace, most students won’t distribute their effort wisely. They’ll defer, delay, and then scramble. In my experience, teenagers are not exactly strong in the planning department, and without external structure, even motivated students will treat a flexible timeline as permission to procrastinate. A system that relies on students to self-regulate their way to mastery will mostly produce last-minute cramming with a competency label stamped on it.
A well-designed competency-based system can get around this issue. It would have students retrieve, apply, and revisit knowledge continuously along the way. By the time students make their way through these types of gateways checks, any endpoint assessment would become a confirmation of learning that’s already happened, not a high-stakes gamble on whether cramming worked.
This structure builds on one of the most replicated findings in learning research. Frequent, low-stakes quizzes and check-ins don’t just measure learning; they help produce it. If those retrieval opportunities are spaced out over time, the benefits will compound into deeper learning. Competency-based models could help students build that type of durable knowledge, but only if they include frequent opportunities to monitor progress along the way.
Reading List
Bruno Manno: AI reinforces the case for strong disciplinary knowledge
Holly Korbey: When teachers ditch “productive struggle” for evidence, student performance improves
Harry Patrinos: Learning Pays More Than Schooling
Todd Truitt: Gratitude for (Virginia’s) standardized tests
Pamela Snow: “education has a fraught and not very pretty history when it comes to generating, critiquing, and applying rigorous evidence”
Kerry McDonald: The College Credit Opportunity Few People Know About