Pith Number

pith:TP67S6NV

pith:2026:TP67S6NV7GBMW7FUEURHQFUJH3

not attested not anchored not stored refs resolved

Exploring how EFL students talk to and through AI to develop texts

Chi Ho Yeung, David James Woo, Deliang Wang, Kai Guo, Yangyang Yu, Yilin Huang

Students' different ways of sharing writing responsibility with AI show no significant impact on their final text quality.

arxiv:2605.12523 v1 · 2026-04-06 · cs.CL · cs.AI · cs.HC

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{TP67S6NV7GBMW7FUEURHQFUJH3}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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

A MANOVA analysis indicated no significant multivariate effect of rhetorical load responsibility on three dimensions of students' writing performance: content, language, and organization.

C2weakest assumption

That the clustering of prompting strategies into three responsibility profiles is stable and meaningful, and that the 44-student sample provides adequate power for detecting differences in the MANOVA.

C3one line summary

EFL students' prompting strategies with AI cluster into AI-dominant, human-dominant, and collaborative profiles, yet these profiles show no significant link to writing performance in content, language, or organization.

References

3 extracted · 3 resolved · 0 Pith anchors

[1] I can understand genre / process and its approach to writing. 2. I can understand ChatGPT and identify its tasks 3. I can understand prompts and identify their categories 4. I can write prompts for di

[2] Introduction to writing approach (B1

[3] Google Docs 3

Receipt and verification

First computed	2026-05-18T03:10:02.844523Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9bfdf979b5f982cb7cb425227816893eca80b7fbc9b846e7e88df231ce549ad1

Aliases

arxiv: 2605.12523 · arxiv_version: 2605.12523v1 · doi: 10.48550/arxiv.2605.12523 · pith_short_12: TP67S6NV7GBM · pith_short_16: TP67S6NV7GBMW7FU · pith_short_8: TP67S6NV

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/TP67S6NV7GBMW7FUEURHQFUJH3 \
  | 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: 9bfdf979b5f982cb7cb425227816893eca80b7fbc9b846e7e88df231ce549ad1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e5636587ec4394d4eba58d034ccad7f69279a3712bcd096b77262108ffe7f05e",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.HC"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-04-06T04:51:05Z",
    "title_canon_sha256": "de8d0adf6ace25d9fee5773d280de41758df17d8cf70bcf7a28edfc7d7c32ef1"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12523",
    "kind": "arxiv",
    "version": 1
  }
}