In Mnemosyne log data, item-specific difficulty parameters outperform a global difficulty for lower and higher Leitner decks, while global difficulty performs better for intermediate decks.¶
Claim · All claims
Evidence · 1 study · causalr?·q2
Currency · newest study 2016 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · overdue for a recheck since 2019: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Item-specific difficulties outperformed a global item difficulty for decks q ≤ 2 and q > 5, but the global difficulty performed better for intermediate decks; no numeric AUC values are printed. → Reddy 2016
Evidence¶
Reddy 2016¶
Reddy, S., Labutov, I., Banerjee, S., & Joachims, T. (2016). Unbounded Human Learning: Optimal Scheduling for Spaced Repetition. KDD ’16, San Francisco, CA, USA. https://doi.org/10.1145/2939672.2939850
q2 · i? · causal · r?
Observational study of Mnemosyne flashcard log data, comparing memory models by cross-validated validation AUC per deck bin. "Item-specific difficulties θi outperform global item difficulty θ for lower decks" and higher decks, but the global parameter did better for intermediate decks (models 5 vs. 10, 8 vs. 13).
"Item-specific difficulties θi outperform global item difficulty θ for lower decks (qij≤ 2) and higher decks ( qij > 5), but the global dif- ficulty performs better for intermediate decks (model 5 vs. 10, 8 vs. 13)"
Discussion¶
Related Claims¶
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Memory-decay-based models fit fact-learning datasets better than models insensitive to memory decay — the general claim this finding bears on, with the studies behind it
-
Under the Leitner Queue Network model, raising the rate of new-item introduction beyond a threshold causes a phase transition in learning rate, which a Mechanical Turk vocabulary experiment reproduced. — the general claim this finding bears on, with the studies behind it
- In Mnemosyne flashcard log data, adding a delay term improves the recall-prediction performance of exponential forgetting curve memory models. — related
- In Mnemosyne log data, setting memory strength equal to an item's Leitner deck position predicts recall better than number of past reviews, which beats constant strength. — related
- In Mnemosyne log data, exponential forgetting curve models that include a delay term perform comparably to 1PL-IRT, the best-performing benchmark model. — related
- Correlation between log response time and response likelihood is negative for almost all items, and its magnitude depends on the item difficulty parameter — related
- A one-parameter IRT model outperforms global and per-pitch baselines on AUC, BCE and Brier score but not on threshold accuracy for held-out singing attempts — related
- Item difficulty was best predicted using signal from the item stem — related
- All models predict performance worst for students of intermediate overall ability, with best performance for high and low performing students — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
item-specific-difficulty-helps-only-at-low-and-high-leitner-decks |
title |
In Mnemosyne log data, item-specific difficulty parameters outperform a global difficulty for lower and higher Leitner decks, while global difficulty performs better for intermediate decks. |
description |
In Mnemosyne log data, item-specific difficulty parameters outperform a global difficulty for lower and higher Leitner decks, while global difficulty performs better for intermediate decks. |
status |
review |
evidence_strength |
mixed |
newest_evidence |
2016 |
source_checked |
2026-10-20 |
recheck_by |
2019 |
generated |
by claude/unspecified on 2026-09-24 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — reddy-2016 |
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