Natural Language Dialogue for Intelligent Tutoring Systems

Abstract

We study tutorial dialogue with two aims: understanding what promotes learning in one on one tutoring; developing language interfaces to Intelligent Tutoring Systems (ITSs). We worked in three different domains. Our work comprises: linguistic analysis, data mining, computational modeling (e.g., discourse planning) implementation, and empirical evaluation with human subjects. Our results show that interfaces developed on the basis of the tutorial dialogue analysis engender significantly more learning than other types of interfaces.

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Document Details

Document Type
Technical Report
Publication Date
Aug 02, 2007
Accession Number
ADA470806

Entities

People

  • Barbara Di Eugenio

Organizations

  • University of Illinois at Chicago

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Cognitive Science
  • Computational Linguistics
  • Computational Science
  • Computer Programming
  • Computer Science
  • Data Analysis
  • Data Mining
  • Information Science
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Languages
  • Psychology
  • Students
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Database Systems and Applications
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation