AutoTutor cannot handle most student questions, so student question frequency extinguishes quickly in tutoring sessions¶
Claim · All claims
Evidence · 1 study · reviewr2·q2
Currency · newest study 2016 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · overdue for a recheck since 2019: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? AutoTutor implemented nearly all conversational mechanisms of human tutors except handling most student questions; the relevance and correctness of answers to student questions is disappointing, so diversionary tactics were implemented and student question frequency extinguishes quickly. → Graesser 2016
Evidence¶
Graesser 2016¶
Graesser, A. C. (2016). Conversations with AutoTutor Help Students Learn. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-015-0086-4
q2 · i? · review · r2
The article reports that when students ask questions, answer relevance and correctness is disappointing in AutoTutor as in other automated environments, prompting diversionary tactics such as "How would you answer that question?". The cited consequence is that student question frequency extinguishes quickly.
"As a consequence, the frequency of student questions unfortunately extinguishes quickly in tutoring sessions with AutoTutor (Graesser and McNamara 2010)."
Discussion¶
Related Claims¶
- AutoTutor's learning gains are virtually equivalent to those of 1-to-1 human tutoring in direct comparisons — related
- AutoTutor achieved learning gains comparable to human tutors in physics and computer literacy — related
- Intelligent tutoring systems are reported to improve learning outcomes, especially in structured knowledge domains — a broader claim this one bears on
- AI solutions can automate routine tasks but cannot yet handle the complex tasks of higher learning — related
- In a case study, LLM-generated assessment conversations handled common student speech acts more naturalistically than RegExp/LSA conversations — related
- Meta-procedural requests are prominent in student discourse with a Socratic AI tutor: Next Step Guidance is the second-most common discourse move despite the tutor being designed not to direct students — related
- AutoTutor yields average learning gains of 0.3 to 0.8 sigma compared to reading text for an equivalent amount of time — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
autotutor-student-questions-extinguish |
title |
AutoTutor cannot handle most student questions, so student question frequency extinguishes quickly in tutoring sessions |
description |
AutoTutor cannot handle most student questions, so student question frequency extinguishes quickly in tutoring sessions |
status |
review |
evidence_strength |
weak |
newest_evidence |
2016 |
source_checked |
2026-10-20 |
recheck_by |
2019 |
generated |
by process:wiki-ingest on 2026-10-17 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — graesser-2016 |
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