pith:CQZWDOCP
LLM-Based Educational Simulation: Evaluating Temporal Student Persona Stability Across ADHD Profiles
LLM-generated ADHD student personas hold self-reported traits steady over time, but their observed behaviors drift in unscripted conversations unless interactions use explicit scripted task prompts.
arxiv:2605.06307 v2 · 2026-05-07 · cs.HC
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Claims
Self-reported characteristics remain stable for high intensities, constituting a necessary prerequisite for valid behavioral simulation. Observer-rated behavioral expression reveals selective instability: within-conversation drift occurs in unscripted dialog for high and moderate ADHD personas. Scripted interactions with explicit task prompts eliminate this drift entirely.
That observer ratings of behavioral expressions accurately and unbiasedly capture persona alignment without influence from rater expectations or LLM generation artifacts.
LLM-simulated ADHD student personas show stable self-reported traits but behavioral drift in unscripted interactions that explicit task prompts fully eliminate.
Receipt and verification
| First computed | 2026-05-25T02:01:22.171530Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
143361b84f83fb7c49f54e5cfa455467fdeab03baab6253054e5d679cb8cd61f
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CQZWDOCPQP5XYSPVJZOPURKUM7 \
| 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: 143361b84f83fb7c49f54e5cfa455467fdeab03baab6253054e5d679cb8cd61f
Canonical record JSON
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