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Controlled tutor-audit testbed: ConvTutor, PedTutor, and cold baseline over identical frozen weights with a weak simulated student

Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 causal), q3 · 0 of 1 report an effect size · 2 claims rest on one study

Description

A within-base testbed in which two tutoring policies are instantiated from identical frozen model weights so that only the policy layer differs. ConvTutor is a minimal one-call helpful tutor whose answer-giving is emergent; PedTutor is a four-node routed policy with a learner-state tracker and three responders (problem decomposer, answer-deferral gate, hint cascade). All conditions face one deliberately weak simulated student, Llama-3.1-8B-Instruct, with "about11% unaided accuracy", making tutoring load-bearing, plus a no-tutor cold baseline and a frozen 19-problem mixture/weighted-average instrument.

Design Implications

Context

Requirements

  • A weak simulated student so that tutoring is load-bearing and a process contrast is measurable
  • Frozen judge, rubrics, metric definitions, and outcome-interpretation table fixed before confirmatory data collection

Constraints

  • The serving vendor co-varies with the tutor base and Gemini's provider enforces a minimum reasoning setting, so no base is a pure base-model swap
  • Results describe one simulated learner on one algebra domain and do not license claims about human learners

Target Learners

  • Simulated weak algebra learners (Llama-3.1-8B-Instruct)

Learning Goals

  • Translating word problems into mixture or weighted-average balance equations

Claims

Examples

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Key Sources

  • Shuyi Fan, Boyuan Deng, Mengyu Xu, Jiale Liu, Hongyang Zhang, Qiaoxin Yang, Chongyang Gao. (2026). Rethinking LLM-Judged Helpfulness as a Pedagogy Signal: A Pre-Registered Audit Across Tutor Models. arXiv. https://arxiv.org/abs/2607.28128
Page metadata
Field Value
type design
id conv-ped-tutor-audit-testbed
title Controlled tutor-audit testbed: ConvTutor, PedTutor, and cold baseline over identical frozen weights with a weak simulated student
description A within-base testbed in which two tutoring policies are instantiated from identical frozen model weights so that only the policy layer differs.
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — shuyi-fan-2026

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