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Pith Number

pith:GSLWYP6Z

pith:2026:GSLWYP6ZHV4AVWAM5W6JRZL3YC
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Revisiting the Regularity of Student Learning Rate: Sensitivity to Which Observations Are Included

Benjamin W. Domingue, Candace Thille, Cristina Barnard, Guilherme Lichand, Hansol Lee, Lucas Klotz, Yunsung Kim

Capping practice sequences at the first five to ten opportunities per student-skill pair substantially inflates estimates of student learning-rate variability.

arxiv:2605.01690 v2 · 2026-05-03 · cs.CY

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\usepackage{pith}
\pithnumber{GSLWYP6ZHV4AVWAM5W6JRZL3YC}

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Capping at the first ten opportunities per student-skill pair inflates the median estimated IQR of student learning rates by 75%; capping at five inflates it by 205%, with individual datasets ranging from negligible to 17-fold.

C2weakest assumption

That systematic truncation of practice sequences at fixed depths provides a valid test of the ignorability assumption without introducing new biases from the resulting data sparsity or from the specific functional form of iAFM.

C3one line summary

Truncating practice sequences at 10 or 5 opportunities per student-skill pair inflates the median interquartile range of estimated learning rates by 75% and 205% respectively across 26 educational datasets.

Receipt and verification
First computed 2026-05-20T00:05:45.768989Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

34976c3fd93d780ad80cedbc98e57bc0b580c897e06947f192b9689436bfb02b

Aliases

arxiv: 2605.01690 · arxiv_version: 2605.01690v2 · doi: 10.48550/arxiv.2605.01690 · pith_short_12: GSLWYP6ZHV4A · pith_short_16: GSLWYP6ZHV4AVWAM · pith_short_8: GSLWYP6Z
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GSLWYP6ZHV4AVWAM5W6JRZL3YC \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 34976c3fd93d780ad80cedbc98e57bc0b580c897e06947f192b9689436bfb02b
Canonical record JSON
{
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    "abstract_canon_sha256": "6cc2b6ce034c8f5e89e65cc323056f8dc70117339ac359443cb7ae9aaa6b62ba",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CY",
    "submitted_at": "2026-05-03T03:07:36Z",
    "title_canon_sha256": "d758b56bea450fe2bb9e2c5952df07a5b398f8043863ef6a4798e5c0e7354adb"
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  "source": {
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    "kind": "arxiv",
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}