Does Mouse Click Frequency Predict Students' Flow Experience?

Pedro Kenzo Muramatsu, Wilk Oliveira, Kiemute Oyibo, Juho Hamari

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)
9 Downloads (Pure)

Abstract

Designing educational systems able to lead students into flow experience is a contemporary challenge, especially given the positive relationship between flow experience and learning. However, an important challenge within the field of learning analytics is evaluating the students' flow experience during the use of educational systems. In general, such evaluation is conducted using invasive methods (e.g., electroencephalogram, and eye trackers) and cannot be massively applied. To face this challenge, following the trend of utilizing behavioral data produced by users to identify their experience when using different types of systems, in our study, we evaluated the applicability of employing one single type of behavior data (i.e., mouse click frequency) as an exclusive metric to model and to predict students' flow experience. By conducting two data-driven studies (N1 = 25 | N2 = 101), we identified that the mouse click frequency on its own is not able to predict the flow experience. Our study contributes to the field of learning analytics confirming that it is not possible to predict students' flow experience only with mouse click frequency and paving the way for new studies that use different behavior data to predict students' flow experience.

Original languageEnglish
Title of host publicationProceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
EditorsTung X. Bui
PublisherHawaii International Conference on System Sciences
Pages1281-1290
Number of pages10
ISBN (Electronic)9780998133164
Publication statusPublished - 2023
Publication typeA4 Article in conference proceedings
EventHawaii International Conference on System Sciences - Maui, Hawaii, United States
Duration: 3 Jan 20236 Jan 2023

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Electronic)2572-6862

Conference

ConferenceHawaii International Conference on System Sciences
Country/TerritoryUnited States
CityMaui, Hawaii
Period3/01/236/01/23

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • General Engineering

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