A scale that catches AI offloading before it hardens! Tina Austin shared this study and I'm glad she did. It lines up with a lot of what I've been posting here, but it adds something the conversation has been missing. We already know the problem. Fan et al. named it back in 2025: metacognitive laziness, the habit of handing your thinking off to AI when you should be doing the goal-setting, the self-checking, the reflection yourself. Dizon et al. (2026) take the next step. They built an actual scale teachers can use to spot the early signs in students, then step in before the AI-dependent pattern gets entrenched. That second part is what makes this useful. Plenty of studies name a problem. Far fewer hand teachers a tool to detect it early enough to do something about it. Dizon et al.'s scale correlated strongly with student disaffection, both the behavioral and the emotional kind, but had basically no relationship with engagement. In other words, a student offloading their thinking to AI isn't just engaging a little less. They're actually withdrawing. They go quiet and check out. Accordingly, AI offloading doesn't simply lower enthusiasm.; It pushes students toward genuine withdrawal. Old-school work avoidance was about doing less. This looks like something more corrosive. It's an early validation study, small and single-site, so I'd hold the causal claims loosely. We don't yet know if AI use weakens metacognition or if students who already struggle are just more drawn to offloading. Still, this is a real contribution. A detector is only step one though. What we do with the signal is pedagogy, and that part is on us.