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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU144723" target="_blank" >RIV/00216305:26230/21:PU144723 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/12735/" target="_blank" >https://www.fit.vut.cz/research/publication/12735/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s40561-021-00175-6" target="_blank" >10.1186/s40561-021-00175-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Smart Learning Environments

ISSN

2196-7091

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

000717490300001

EID výsledku v databázi Scopus

2-s2.0-85118944820