Using automated dialog analysis to assess peer tutoring and trigger effective support

Erin Walker, Nikol Rummel, Kenneth R. Koedinger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Intelligent tutors have the potential to be used in supporting learning from collaboration, but there are few results demonstrating their positive effects in this domain. One of the main challenges in automated support for collaboration is the machine classification of dialogue, giving the system an ability to know when and how to intervene. We have developed an automated detector of conceptual content that is used as a basis for providing adaptive prompts to peer tutors in high-school algebra. We conducted an after-school study with 61 participants where we compared this adaptive support to two nonadaptive support conditions, and found that adaptive prompts significantly increased conceptual help and peer tutor domain learning. The amount of conceptual help students gave, as determined by either human coding or machine classification, was predictive of learning. Thus, machine classification was effective both as a basis for feedback and predictor of success.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 15th International Conference, AIED 2011
Pages385-393
Number of pages9
DOIs
StatePublished - Jun 23 2011
Event15th International Conference on Artificial Intelligence in Education, AIED 2011 - Auckland, New Zealand
Duration: Jun 28 2011Jul 1 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6738 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Artificial Intelligence in Education, AIED 2011
CountryNew Zealand
CityAuckland
Period6/28/117/1/11

Keywords

  • adaptive collaboration support
  • intelligent tutoring
  • peer tutoring

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Using automated dialog analysis to assess peer tutoring and trigger effective support'. Together they form a unique fingerprint.

  • Cite this

    Walker, E., Rummel, N., & Koedinger, K. R. (2011). Using automated dialog analysis to assess peer tutoring and trigger effective support. In Artificial Intelligence in Education - 15th International Conference, AIED 2011 (pp. 385-393). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6738 LNAI). https://doi.org/10.1007/978-3-642-21869-9_50