Item-level generalized linear mixed model finds no Testing Condition × Semantic Relatedness interaction, and item-level proportions correct show no pervasive ceiling effect¶

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? The item-level interaction between training condition and item semantic relatedness was not statistically significant, showing no compression of the testing effect for higher-relatedness items. → Gupta 2026

Evidence¶

Gupta 2026¶

Gupta, M.W., Pan, S.C., & Rickard, T.C. (2026). Semantic relatedness and the efficacy of retrieval practice. npj Science of Learning. https://doi.org/10.1038/s41539-026-00416-8

q3 · i? · causal · r2

Generalized linear mixed model (SAS Proc GLIMMIX) over all high-relatedness-group items with random intercepts for subjects and items; significant effects of relatedness (F(1, 8733) = 24.54) and training condition (F(1, 8733) = 82.77), but "The interaction, however, was not statistically significant."

"The interaction, however, was not statistically significant, F(1, 8733) = 0.05, p = .82. Hence there is no evidence for compression of the TE for higher relatedness items."

Discussion¶

Related Claims¶

• Retrieval practice with feedback improves 24-hour cued recall more than restudy, and high semantic relatedness raises overall accuracy, but the Training Task × Relatedness ANOVA interaction is non-significant — related
• Cumulative distribution analysis shows the dual-memory model systematically overpredicts test performance at all restudy levels for high-relatedness pairs, ruling out a participant-level ceiling effect — reports the opposite
• Model-based analysis shows the relative efficacy of testing is reduced for highly related word pairs, with the dual-memory model overpredicting test performance only in the high-relatedness group — reports the opposite