Interleaving effects are stronger when material is more similar between categories, less similar within categories, and more complex¶

Claim · All claims
Evidence · 1 study · quant-synthesis r? · q4
Currency · newest study 2019 · checked against its sources 2026-10-21 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q4 i? Between-category similarity positively influenced the interleaving effect, whereas within-category similarity negatively influenced it, as predicted by the attentional bias framework. → Brunmair 2019

Evidence¶

Brunmair 2019¶

Brunmair, M., & Richter, T. (2019). Similarity matters: A meta-analysis of interleaved learning and its moderators. Psychological Bulletin. https://doi.org/10.1037/bul0000209

q4 · i? · quant-synthesis · r?

Meta-regression models (Models 1-3) with rater-based material-characteristic ratings as moderators; sensitivity analyses across subsets showed the pattern of effects was very stable across different models and samples. No standardized coefficient is quoted here, so no effect size is reported.

"As expected from the viewpoint of the attentional bias framework (Carvalho & Goldstone, 2015b), similarity between categories had a positive influence on the effect of interleaving, whereas similarity within categories had a negative influence, which decreased when learning materials were included in the model (Table 3)."

Studies bearing on this claim¶

How alike must the categories be for mixing to help, and when does blocking do better? This table gathers the studies behind this claim and the 2 narrower claims that bear on it: 2 distinct studies (2 quant-synthesis), q2–q4, 0 of 2 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

Related Claims¶

• Interleaving effects are larger in pure university student samples than in nonstudent samples — related
• Interleaving is most useful when differences between items are subtle; blocking can be preferable when category members are diverse — possibly the same claim (merge candidate)
• Interleaving is especially useful for inductive, subtle pattern learning without a clear verbal rule, but can equal or exceed blocking in rule-based domains too — related
• The discriminative-contrast hypothesis treats spacing and interleaving as distinct effects, with interleaving benefits more likely for similar than dissimilar interleaved tasks — related
• Interleaving category examples improves inductive category learning for visual and mathematical materials, but not for expository texts or word categories — a broader claim this one bears on
• Five null studies with spacing but no rest and dissimilar materials showed neither spacing nor interleaving effects — a narrower finding that bears on this claim