Uncovering associations between users' behaviour and their flow experience

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU156210" target="_blank" >RIV/00216305:26230/24:PU156210 - isvavai.cz</a>

Result on the web

<a href="https://www.tandfonline.com/doi/epdf/10.1080/0144929X.2023.2276822?src=getftr&getft_integrator=scopus" target="_blank" >https://www.tandfonline.com/doi/epdf/10.1080/0144929X.2023.2276822?src=getftr&getft_integrator=scopus</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/0144929X.2023.2276822" target="_blank" >10.1080/0144929X.2023.2276822</a>

Result language

angličtina

Original language name

Uncovering associations between users' behaviour and their flow experience

Original language description

Flow experience is one of the most ambitious targets of any user interface designer. However, it has remained elusive to evaluate how well user interfaces give rise to flow experience outside conducting invasive self-reporting-based questionnaires, which remove the users from the flow experience and can't be massively applied. At the same time, otherwise, well-built systems do track the behaviour of users on the interface, and therefore, user behaviour data could act as a reliable proxy for assessing the experience of users. Currently, there is little empirical research or data about which indices of user behaviours might correspond with having a flow experience as well as the different psychological constituents of the flow experience. Therefore, facing the challenge of using users' behaviour data to model users' experience, we investigated the associations between users' behaviour data (e.g. mouse clicks, activity time in the system, and average response time) and their self-reported flow experience by using data mining (i.e. associations rules) analysing data from 204 subjects. Results demonstrate that the speed of users' actions negatively affects the flow experience antecedents while also positively affecting the loss of self-consciousness. Our study advances the literature, providing insights to identify users' flow experience through behaviour data.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

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

Name of the periodical

BEHAVIOUR & INFORMATION TECHNOLOGY

ISSN

0144-929X

e-ISSN

1362-3001

Volume of the periodical

43

Issue of the periodical within the volume

14

Country of publishing house

GB - UNITED KINGDOM

Number of pages

20

Pages from-to

3416-3435

UT code for WoS article

001097752800001

EID of the result in the Scopus database

2-s2.0-85176090484