People Accurately Predict the Shape of Skill Learning Curves

Decades of research have shown that skill learning often unfolds exponentially — people improve rapidly early on, and then performance gradually levels off. Given how important expectations of learning are for actual learning, we explored whether people accurately intuit this canonical time course of skill learning. Across five pre-registered experiments (n = 375), we find that people correctly predict that skill learning (error reductions over time) on a novel visuomotor task will follow an exponential decay function, both for an imagined naïve player and for themselves, before engaging with the task. Moreover, people are sensitive to conditions that merit exponential learning and only predict these curves when an imagined player puts in effort and the task is not too difficult. Lastly, although people accurately represent the overall shape of learning, they misestimate specific parameters which may have negative downstream effects on real-world learning outcomes.