<p>Although extensive research has examined how exemplar sequencing (interleaving vs. blocking) influences category learning, the mechanisms underlying these effects remain incompletely understood, particularly for natural categories that differ in structural properties. By more rigorously controlling the degree of nondiagnostic feature variability, we constructed two natural category structures: one characterized by low between-category discriminability, and one characterized by high between-category discriminability alongside high within-category similarity—a structural configuration that prior work has not directly examined. Across three experiments, blocked learning enhanced classification accuracy and metacognitive regulation efficiency for high-discriminability categories, whereas interleaved learning proved more effective for low-discriminability categories, yielding higher accuracy and more effective regulation. These findings suggest that similarity-based processing difficulty is unlikely to fully account for exemplar sequencing effects, particularly the advantage of blocked learning. Our findings offer a possible signal-to-noise perspective on the cognitive mechanisms underlying these effects, while also providing a complementary metacognitive account based on cue-utilization.</p>