Sensor-free affect detection for a simulation-based science inquiry learning environment

Luc Paquette, Ryan S.J.D. Baker, Michael A. Sao Pedro, Janice D. Gobert, Lisa Rossi, Adam Nakama, Zakkai Kauffman-Rogoff

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

Abstract

Recently, there has been considerable interest in understanding the relationship between student affect and cognition. This research is facilitated by the advent of automated sensor-free detectors that have been designed to "infer" affect from the logs of student interactions within a learning environment. Such detectors allow for fine-grained analysis of the impact of different affective states on a range of learning outcome measures. However, these detectors have to date only been developed for a subset of online learning environments, including problem-solving tutors, dialogue tutors, and narrative-based virtual environments. In this paper, we extend sensor-free affect detection to a science microworld environment, affording the possibility of more deeply studying and responding to student affect in this type of learning environment.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 12th International Conference, ITS 2014, Proceedings
PublisherSpringer-Verlag Berlin Heidelberg
Pages1-10
Number of pages10
ISBN (Print)9783319072203
DOIs
StatePublished - 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

  • Educational data mining
  • affect detection
  • affective computing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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