Publication Details

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

PASTUSHENKO Olena, OLIVEIRA Wilk, HRUŠKA Tomáš and ISOTANI Seiji. A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments. In: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu: Association for Computing Machinery, 2020, pp. 1-9. ISBN 978-1-4503-6819-3.
Czech title
Metodologie pro multimodální analýzu učení a flow state identifikaci v rámci gamifikovanych úkolů
Type
conference paper
Language
english
Authors
Pastushenko Olena, Ing. (DIFS FIT BUT)
Oliveira Wilk (USP)
Hruška Tomáš, prof. Ing., CSc. (DIFS FIT BUT)
Isotani Seiji (USP)
Keywords

gamification, flow theory, multimodal learning analytics, automatic identification, educational systems

Abstract

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.

Published
2020
Pages
1-9
Proceedings
Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
Conference
Human Factors in Computing Systems, Honolulu, US
ISBN
978-1-4503-6819-3
Publisher
Association for Computing Machinery
Place
Honolulu, US
DOI
UT WoS
000626317803089
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12184,
   author = "Olena Pastushenko and Wilk Oliveira and Tom\'{a}\v{s} Hru\v{s}ka and Seiji Isotani",
   title = "A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments",
   pages = "1--9",
   booktitle = "Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems",
   year = 2020,
   location = "Honolulu, US",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-6819-3",
   doi = "10.1145/3334480.3383060",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12184"
}
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