Publication Details
A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments
gamification, flow theory, multimodal learning analytics, automatic
identification, educational systems
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.
@inproceedings{BUT168473,
author="PASTUSHENKO, O. and OLIVEIRA, W. and HRUŠKA, T. and ISOTANI, S.",
title="A Methodology for Multimodal Learning Analytics and Flow Experience Identification within Gamified Assignments",
booktitle="Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems",
year="2020",
pages="1--9",
publisher="Association for Computing Machinery",
address="Honolulu",
doi="10.1145/3334480.3383060",
isbn="978-1-4503-6819-3",
url="https://www.fit.vut.cz/research/publication/12184/"
}