Optimal ACT-R parameter values change systematically and predictably with the length of the between-session interval¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The fitted parameter value in each time bin is strongly related to the bin's geometric mean interval, indicating systematic change over time and enabling interpolation and extrapolation to unobserved intervals. → Maarten van der Velde 2026

Evidence¶

Maarten van der Velde 2026¶

Maarten van der Velde, Florian Sense, Jelmer P. Borst & Hedderik van Rijn. (2026). Explaining forgetting at different timescales requires a time-variant forgetting function. npj Science of Learning. https://doi.org/10.1038/s41539-026-00447-1

q2 · i? · associational · r2

Regression of fitted parameter values on the geometric mean interval of each bin (red regression lines with 95% CI in Fig. 3). The article reports "a strong relationship between the geometric mean interval of each bin and the fitted parameter value, indicating systematic change over time."

"Fig.3 confirms that there is a strong relationship between the geometric mean interval of each bin and the fitted parameter value, indicating systematic change over time."

Discussion¶

Related Claims¶

• In 5-fold cross-validation, multi-bin time-variant model fits outperform single-bin fits, with diminishing returns beyond a 5-bin split and further gains from differentiating by learner and amount of practice — related
• Allowing ACT-R memory parameters to vary with the between-session interval produces a strong fit between model and recall data across timescales — a broader claim this one bears on
• Extrapolating from parameters fitted to a restricted range of between-session intervals produces worse predictions than time-variant fits — a narrower finding that bears on this claim