Using log data to predict response behaviors in classroom discussions

Ruth Wylie, Brandon Helding, Robert Talbot, Michelene Chi, Susan Trickett, Rodney D. Nielsen

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

Abstract

The Comprehension Seeding system allows students to respond to an open-ended question using tablet computers; the system provides formative feedback to teachers to facilitate discussion and encourage students to engage in reflective behaviors. Data from a semester-long intervention suggested that few students engaged in this reflective process, leading us to question under what conditions the reflection process does or will occur. Using logistic regression, we investigated different ways the system was used, and what types of usage lead to desired, reflective behavior.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages670-671
Number of pages2
Volume8474 LNCS
ISBN (Print)9783319072203
DOIs
StatePublished - 2014
Event12th International Conference on Intelligent Tutoring Systems, ITS 2014 - Honolulu, HI, United States
Duration: Jun 5 2014Jun 9 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8474 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Intelligent Tutoring Systems, ITS 2014
Country/TerritoryUnited States
CityHonolulu, HI
Period6/5/146/9/14

Keywords

  • classroom discussion
  • classroom response technology
  • data mining

ASJC Scopus subject areas

  • General Computer Science
  • Theoretical Computer Science

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