To quit or not to quit: Predicting future behavioral disengagement from reading patterns

Caitlin Mills, Nigel Bosch, Art Graesser, Sidney D'Mello

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

Abstract

This research predicted behavioral disengagement using quitting behaviors while learning from instructional texts. Supervised machine learning algorithms were used to predict if students would quit an upcoming text by analyzing reading behaviors observed in previous texts. Behavioral disengagement (quitting) at any point during the text was predicted with an accuracy of 76.5% (48% above chance), before students even began engaging with the text. We also predicted if a student would quit reading on the first page of a text or continue reading past the first page with an accuracy of 88.5% (29% above chance), as well as if students would quit sometime after the first page with an accuracy of 81.4% (51% greater than chance). Both actual quits and predicted quits were significantly related to learning, which provides some evidence for the predictive validity of our model. Implications and future work related to ITSs are also discussed.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 12th International Conference, ITS 2014, Proceedings
PublisherSpringer-Verlag
Pages19-28
Number of pages10
ISBN (Print)9783319072203
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
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)0302-9743
ISSN (Electronic)1611-3349

Other

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

Keywords

  • affect detection
  • disengagement
  • engagement
  • ITSs
  • reading

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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