Towards automatically detecting whether student is in flow

Po Ming Lee, Sin Yu Jheng, Tzu-Chien Hsiao*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Csikszentmihalyi's flow theory states the components (e.g., balance between skill and challenge) that lead to an optimal state (referred to as flow state, or under flow experience) of intrinsic motivation and personal experience. Recent research has begun to validate the claims stated by the theory and extend the provided statements to the design of pedagogical interactions. To incorporate the theory in a design, automatic detector of flow is required. However, little attention has been drawn to this filed, and the detection of flow is currently still dominated by using surveys. Hence, within this paper, we present an automated detector which is able to identify the students that are in flow. This detector is developed using a step regression approach, with data collected from college students learning linear algebra from a step-based tutoring system.

Original languageEnglish
Title of host publicationIntelligent Tutoring Systems - 12th International Conference, ITS 2014, Proceedings
PublisherSpringer Verlag
Pages11-18
Number of pages8
ISBN (Print)9783319072203
DOIs
StatePublished - 1 Jan 2014
Event12th International Conference on Intelligent Tutoring Systems, ITS 2014 - Honolulu, HI, United States
Duration: 5 Jun 20149 Jun 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

Conference

Conference12th International Conference on Intelligent Tutoring Systems, ITS 2014
CountryUnited States
CityHonolulu, HI
Period5/06/149/06/14

Keywords

  • Educational Data Mining
  • Flow Theory
  • Intelligent Tutoring System
  • Student Modeling

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