Blinded by science? Exploring affective meaning in students’ own words

Sarah E. Schultz, Naomi Wixon, Danielle Allessio, Kasia Muldner, Winslow Burleson, Beverly Woolf, Ivon Arroyo

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

Abstract

This work addresses students’ open responses on causal attributions of their self-reported affective states. We use qualitative thematic data analysis techniques to develop a coding scheme by identifying common themes in students’ self-reported attributions. We then applied this scheme to a larger set of student reports. Analysis shows that students’ reasons for reporting a certain affect do not always align with researchers’ expectations. In particular, we discovered that a sizable group of students externalize their affect, attributing perceived difficulty of the problem and their own negativity as lying outside of themselves.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 13th International Conference, ITS 2016, Proceedings
EditorsJohn Stamper, Alessandro Micarelli, Kitty Panourgia
PublisherSpringer Verlag
Pages314-319
Number of pages6
ISBN (Print)9783319395821
DOIs
StatePublished - 2016
Event13th International Conference on Intelligent Tutoring Systems, ITS 2016 - Zagreb, Croatia
Duration: Jun 7 2016Jun 10 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9684
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Intelligent Tutoring Systems, ITS 2016
Country/TerritoryCroatia
CityZagreb
Period6/7/166/10/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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