Repairing deactivating negative emotions with student progress pages

Dovan Rai, Ivon Arroyo, Lynn Stephens, Cecil Lozano, Winslow Burleson, Beverly Park Woolf, Joseph E. Beck

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

Abstract

We report on two studies that suggest that showing reports of student progress at key moments of deactivating negative emotions (boredom or lack of excitement) can help improve students' affective state and learning behavior while using an adaptive math tutoring system. The studies involved 160 middle-school students in public schools in Arizona and California who reported higher levels of interest and excitement and also demonstrated more positive engagement behavior when using the intervention progress pages.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
Pages795-798
Number of pages4
DOIs
StatePublished - 2013
Event16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States
Duration: Jul 9 2013Jul 13 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7926 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Artificial Intelligence in Education, AIED 2013
CountryUnited States
CityMemphis, TN
Period7/9/137/13/13

Keywords

  • Affect
  • Engagement behavior
  • Metacognition
  • Open learner modeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Rai, D., Arroyo, I., Stephens, L., Lozano, C., Burleson, W., Woolf, B. P., & Beck, J. E. (2013). Repairing deactivating negative emotions with student progress pages. In Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings (pp. 795-798). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7926 LNAI). https://doi.org/10.1007/978-3-642-39112-5-115