Naturalistic fact-learning dataset from an adaptive learning system (25,843 sequences, 218 learners)¶
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Evidence · 5 claims (5 for) · 1 study (1 associational),q2· 0 of 1 report an effect size · 5 claims rest on one study
Description¶
An OSF-released dataset from Maarten van der Velde et al. containing naturalistic open-answer retrieval-practice sequences from 218 undergraduate cognitive psychology learners using an adaptive fact-learning system.
Components¶
Claims¶
- Allowing ACT-R memory parameters to vary with the between-session interval produces a strong fit between model and recall data across timescales [+W]
- A single time-invariant ACT-R forgetting function cannot simultaneously capture recall accuracy on short and long between-session intervals [+W]
- Extrapolating from parameters fitted to a restricted range of between-session intervals produces worse predictions than time-variant fits [+W]
- 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 [+W]
- Optimal ACT-R parameter values change systematically and predictably with the length of the between-session interval [+W]
Related Products and Programmes¶
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Key Sources¶
- 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
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
naturalistic-fact-learning-dataset-from-an-adaptive-learning-system-25843-sequences-218-le |
title |
Naturalistic fact-learning dataset from an adaptive learning system (25,843 sequences, 218 learners) |
description |
An OSF-released dataset from Maarten van der Velde et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-26 |
trust |
unverified — no one has confirmed this page's content |
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