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AutoTutor for CSAL: trialogue-based intelligent tutoring system for adult reading comprehension

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

AutoTutor for CSAL is a web-based conversation-based ITS in which two computer agents (a teacher agent and a peer agent) hold trialogue conversations with adult learners. The three-way conversations are designed to provide instruction on reading comprehension strategies, help adults apply strategies to texts, assess performance, and guide computer use. Lessons begin with a 2–3 min video reviewing a comprehension strategy, then agents scaffold learning by asking questions, providing short feedback, explaining answers, and giving correct responses. Game-like competitions between the student and peer agent are programmed so the human student never loses.

Design Implications

Context

Requirements

  • Computer agents (teacher and peer) implementing trialogue conversations
  • Lessons aligned with a comprehension-strategy curriculum (PACES)

Constraints

  • The pragmatic communication level of comprehension was not directly implemented in the system

Target Learners

  • adults with low literacy skills

Learning Goals

  • reading comprehension strategies at multiple levels of language and discourse

Claims

Examples

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Key Sources

  • Fang, Y., Lippert, A., Cai, Z., Chen, S., Frijters, J. C., Greenberg, D., & Graesser, A. C. (2021). Patterns of Adults with Low Literacy Skills Interacting with an Intelligent Tutoring System. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-021-00266-y
Page metadata
Field Value
type design
id autotutor-csal-trialogue-adult-literacy
title AutoTutor for CSAL: trialogue-based intelligent tutoring system for adult reading comprehension
description AutoTutor for CSAL is a web-based conversation-based ITS in which two computer agents (a teacher agent and a peer agent) hold trialogue conversations with adult learners.
status review
generated by process:settle-candidates on 2026-10-28
trust unverified — no one has confirmed this page's content
sources 1 — fang-2021

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