Pith Number

pith:IYGNHAW2

pith:2026:IYGNHAW23MTHS2HM2P3G6ZLKMA

not attested not anchored not stored refs resolved

Distinguishing performance gains from learning when using generative AI

Dragan Ga\v{s}evi\'c, Jason M. Lodge, Lixiang Yan, Samuel Greiff

Generative AI improves learner performance but does not promote deep cognitive and metacognitive processing for high-quality learning.

arxiv:2605.13731 v1 · 2026-05-13 · cs.LG · cs.HC

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Record completeness

1 Bitcoin timestamp

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

these uses do not promote the deep cognitive and metacognitive processing that are required for high-quality learning.

C2weakest assumption

That current uses of generative AI in education can be assessed for their effect on deep processing without providing specific evidence or examples of how performance is measured versus learning.

C3one line summary

Generative AI improves performance in education but fails to promote the deep cognitive and metacognitive processing required for high-quality learning.

References

10 extracted · 10 resolved · 0 Pith anchors

[1] Deng, R., Jiang, M., Yu, X., Lu, Y. & Liu, S. Does ChatGPT enhance stu- dent learning? A systematic review and meta-analysis of experimental studies. Computers & Education227, 105224 (2025). 4 2025

[2] & Gaˇ sevi´ c, D 2024

[3] Stadler, M., Bannert, M. & Sailer, M. Cognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry.Computers in Human Behavior160, 108386 (2024) 2024

[4] Fan, Y. et al. Beware of metacognitive laziness: effects of generative artificial intelligence on learning motivation, processes, and performance.British Journal of Educational Technology56, 489–530 ( 2024

[5] Soderstrom, N. C. & Bjork, R. A. Learning versus performance: an integrative review.Perspectives on Psychological Science10, 176–199 (2015) 2015

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-18T02:44:16.557810Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

460cd382dadb267968ecd3f66f656a601ecf4533d5b0d12ae284ac9bc897ccfb

Aliases

arxiv: 2605.13731 · arxiv_version: 2605.13731v1 · doi: 10.48550/arxiv.2605.13731 · pith_short_12: IYGNHAW23MTH · pith_short_16: IYGNHAW23MTHS2HM · pith_short_8: IYGNHAW2

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/IYGNHAW23MTHS2HM2P3G6ZLKMA \
  | 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: 460cd382dadb267968ecd3f66f656a601ecf4533d5b0d12ae284ac9bc897ccfb

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "1d5952aca5abe6c9f17c19aa3889dee9a72970ec9c36fee6bfe76d47bb020bf3",
    "cross_cats_sorted": [
      "cs.HC"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T16:11:05Z",
    "title_canon_sha256": "a01d647a61035df1c7131a8886607eb58eaf60ef5408411e1bc8420f4b28a1ee"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13731",
    "kind": "arxiv",
    "version": 1
  }
}