Predicting Real-Time Affective States by Modeling Facial Emotions Captured During Educational Video Game Play

Vipin Verma, Hansol Rheem, Ashish Amresh, Scotty D. Craig, Ajay Bansal

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

4 Scopus citations

Abstract

In an attempt to predict the cognitive-affective states of a player during an educational video game session, this study used a self-emote procedure in which participants’ facial expressions and emotions were continuously recorded along with self-reported data about their emotional states. Participants’ facial expressions and emotions were captured using Affdex SDK from Affectiva. The captured data were used for binomial logistic regression to predict the cognitive-affective states of flow, frustration, and boredom. The binomial logistic regression uncovered that expressions and emotions could be used to predict these cognitive-affective states of a player. We discuss these predictors and their potential to adapt an educational video game session with non-intrusive and affect-sensitive personalization capabilities. The current study provides a pathway for the educational play design and suggests that it should be non-intrusive while being adaptive to a player’s capabilities.

Original languageEnglish (US)
Title of host publicationGames and Learning Alliance - 9th International Conference, GALA 2020, Proceedings
EditorsIza Marfisi-Schottman, Francesco Bellotti, Ludovic Hamon, Roland Klemke
PublisherSpringer Science and Business Media Deutschland GmbH
Pages447-452
Number of pages6
ISBN (Print)9783030634636
DOIs
StatePublished - 2020
Event9th International Conference on Games and Learning Alliance, GALA 2020 - Laval, France
Duration: Dec 9 2020Dec 10 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12517 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Games and Learning Alliance, GALA 2020
Country/TerritoryFrance
CityLaval
Period12/9/2012/10/20

Keywords

  • Affective computing
  • Educational games
  • Emotion in human-computer interaction
  • Sensor-free

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Predicting Real-Time Affective States by Modeling Facial Emotions Captured During Educational Video Game Play'. Together they form a unique fingerprint.

Cite this