Predicting students’ flow experience through behavior data in gamified educational systems

Abstract The flow experience (i.e., challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration, sense of control, loss of self-consciousness, transformation of time, and autotelic experience) is an experience highly related to the learning experience. One of...

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Autores principales:	Wilk Oliveira, Kamilla Tenório, Juho Hamari, Olena Pastushenko, Seiji Isotani
Formato:	article
Lenguaje:	EN
Publicado:	SpringerOpen 2021
Materias:	Students’ flow experience Educational systems Gamified education Behavior data Data-driven study Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/c8ac12e8fa2540ebb9f22bcb71b4df3f
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spelling	oai:doaj.org-article:c8ac12e8fa2540ebb9f22bcb71b4df3f2021-11-14T12:06:34ZPredicting students’ flow experience through behavior data in gamified educational systems10.1186/s40561-021-00175-62196-7091https://doaj.org/article/c8ac12e8fa2540ebb9f22bcb71b4df3f2021-11-01T00:00:00Zhttps://doi.org/10.1186/s40561-021-00175-6https://doaj.org/toc/2196-7091Abstract The flow experience (i.e., challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration, sense of control, loss of self-consciousness, transformation of time, and autotelic experience) is an experience highly related to the learning experience. One of the current challenges is to identify whether students are managing to achieve this experience in educational systems. The methods currently used to identify students’ flow experience are based on self-reports or equipment (e.g., eye trackers or electroencephalograms). The main problem with these methods is the high cost of the equipment and the impossibility of applying them massively. To address this challenge, we used behavior data logs produced by students during the use of a gamified educational system to predict the students’ flow experience. Through a data-driven study (N = 23) using structural equation modeling, we identified possibilities to predict the students’ flow experience through the speed of students’ actions. With this initial study, we advance the literature, especially contributing to the field of student experience analysis, by bringing insights showing how to step towards automatic students’ flow experience identification in gamified educational systems.Wilk OliveiraKamilla TenórioJuho HamariOlena PastushenkoSeiji IsotaniSpringerOpenarticleStudents’ flow experienceEducational systemsGamified educationBehavior dataData-driven studySpecial aspects of educationLC8-6691ENSmart Learning Environments, Vol 8, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Students’ flow experience Educational systems Gamified education Behavior data Data-driven study Special aspects of education LC8-6691
spellingShingle	Students’ flow experience Educational systems Gamified education Behavior data Data-driven study Special aspects of education LC8-6691 Wilk Oliveira Kamilla Tenório Juho Hamari Olena Pastushenko Seiji Isotani Predicting students’ flow experience through behavior data in gamified educational systems
description	Abstract The flow experience (i.e., challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration, sense of control, loss of self-consciousness, transformation of time, and autotelic experience) is an experience highly related to the learning experience. One of the current challenges is to identify whether students are managing to achieve this experience in educational systems. The methods currently used to identify students’ flow experience are based on self-reports or equipment (e.g., eye trackers or electroencephalograms). The main problem with these methods is the high cost of the equipment and the impossibility of applying them massively. To address this challenge, we used behavior data logs produced by students during the use of a gamified educational system to predict the students’ flow experience. Through a data-driven study (N = 23) using structural equation modeling, we identified possibilities to predict the students’ flow experience through the speed of students’ actions. With this initial study, we advance the literature, especially contributing to the field of student experience analysis, by bringing insights showing how to step towards automatic students’ flow experience identification in gamified educational systems.
format	article
author	Wilk Oliveira Kamilla Tenório Juho Hamari Olena Pastushenko Seiji Isotani
author_facet	Wilk Oliveira Kamilla Tenório Juho Hamari Olena Pastushenko Seiji Isotani
author_sort	Wilk Oliveira
title	Predicting students’ flow experience through behavior data in gamified educational systems
title_short	Predicting students’ flow experience through behavior data in gamified educational systems
title_full	Predicting students’ flow experience through behavior data in gamified educational systems
title_fullStr	Predicting students’ flow experience through behavior data in gamified educational systems
title_full_unstemmed	Predicting students’ flow experience through behavior data in gamified educational systems
title_sort	predicting students’ flow experience through behavior data in gamified educational systems
publisher	SpringerOpen
publishDate	2021
url	https://doaj.org/article/c8ac12e8fa2540ebb9f22bcb71b4df3f
work_keys_str_mv	AT wilkoliveira predictingstudentsflowexperiencethroughbehaviordataingamifiededucationalsystems AT kamillatenorio predictingstudentsflowexperiencethroughbehaviordataingamifiededucationalsystems AT juhohamari predictingstudentsflowexperiencethroughbehaviordataingamifiededucationalsystems AT olenapastushenko predictingstudentsflowexperiencethroughbehaviordataingamifiededucationalsystems AT seijiisotani predictingstudentsflowexperiencethroughbehaviordataingamifiededucationalsystems
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Predicting students’ flow experience through behavior data in gamified educational systems

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