Content, Social, and Metacognitive Statements: An Empirical Study Comparing Human-Human and Human-Computer Tutorial Dialogue

Abstract

We present a study which compares human-human computer-mediated tutoring with two computer tutoring systems based on the same materials but differing in the type of feedback they provide. Our results show that there are significant differences in interaction style between human-human and human-computer tutoring, as well as between the two computer tutors, and that different dialogue characteristics predict learning gain in different conditions. We show that there are significant differences in the non-content statements that students make to human and computer tutors, but also to different types of computer tutors. These differences also affect which factors are correlated with learning gain and user satisfaction. We argue that ITS designers should pay particular attention to strategies for dealing with negative social and metacognitive statements, and also conduct further research on how interaction style affects human-computer tutoring.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA530025

Entities

People

  • Gwendolyn E. Campbell
  • Johanna D. Moore
  • Katherine M. Harrison
  • Leanne S. Taylor
  • Myroslava O. Dzikovska
  • Natalie B. Steinhauser

Organizations

  • Naval Air Warfare Center

Tags

DTIC Thesaurus Topics

  • Cognitive Systems Engineering
  • Computer Programming
  • Computers
  • Curriculum
  • Data Analysis
  • Environment
  • Feedback
  • High Reliability
  • Human-Computer Interaction
  • Language
  • Learning
  • Materials
  • Natural Language Processing
  • Natural Languages
  • Reliability
  • Statistics
  • Students

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Organizational Psychology.