La Mort du Chercheur: How well do students' subjective understandings of affective representations used in self-report align with one another's, and researchers'?

Wixon, Danielle Allessio, Jaclyn Ocumpaugh, Beverly Woolf, Winslow Burleson, Ivon Arroyo

Research output: Contribution to journalConference articlepeer-review

Abstract

We address empirical methods to assess the reliability and design of affective self-reports. Previous research has shown that students may have subjectively different understandings of the affective state they are reporting [18], particularly among younger students[10]. For example, what one student describes as "extremely frustrating" another might see as only "mildly frustrating." Further, what students describe as "frustration" may differ between individuals in terms of valence, and activation. In an effort to address these issues, we use an established visual representation of educationally relevant emotional differences [3, 8, 25]. Students were asked to rate various affective terms and facial expressions on a coordinate axis in terms of valence and activation. In so doing, we hope to begin to measure the variability of affective representations as a measurement tool. Quantifying the extent to which representations of affect may vary provides a measure of measurement error to improve reliability.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
Volume1446
StatePublished - 2015
Externally publishedYes
Event8th International Conference on Educational Data Mining, EDM 2015 - Madrid, Spain
Duration: Jun 26 2015Jun 29 2015

Keywords

  • Affective States
  • Intelligent Tutoring Systems
  • Reasons for Affect

ASJC Scopus subject areas

  • General Computer Science

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