A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138860" target="_blank" >RIV/00216305:26230/20:PU138860 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/12184/" target="_blank" >https://www.fit.vut.cz/research/publication/12184/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3334480.3383060" target="_blank" >10.1145/3334480.3383060</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments

Popis výsledku v původním jazyce

Much research has sought to provide a flow experience for students in gamified educational systems to increase motivation and engagement. However, there is still a lack of quantitative research for evaluating the influence of the flow state on learning outcomes. One of the issues related to flow experience identification is that used techniques are often invasive or not suitable for massive applications. The current paper suggests a way to deal with this challenge. We describe a methodology based on multimodal learning analytics, aimed to provide automatic students flow experience identification in the gamified assignments and measuring its influence on the learning outcomes. The application of the developed methodology showed that there are correlations between learning outcomes and flow state, but they depend on the initial level of the user. This finding suggests adding dynamic difficulty adjustment to the gamified assignment.

Název v anglickém jazyce

A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments

Popis výsledku anglicky

Much research has sought to provide a flow experience for students in gamified educational systems to increase motivation and engagement. However, there is still a lack of quantitative research for evaluating the influence of the flow state on learning outcomes. One of the issues related to flow experience identification is that used techniques are often invasive or not suitable for massive applications. The current paper suggests a way to deal with this challenge. We describe a methodology based on multimodal learning analytics, aimed to provide automatic students flow experience identification in the gamified assignments and measuring its influence on the learning outcomes. The application of the developed methodology showed that there are correlations between learning outcomes and flow state, but they depend on the initial level of the user. This finding suggests adding dynamic difficulty adjustment to the gamified assignment.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems

ISBN

978-1-4503-6819-3

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

1-9

Název nakladatele

Association for Computing Machinery

Místo vydání

Honolulu

Místo konání akce

Honolulu

Datum konání akce

25. 4. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000626317803089