Flow in Knowledge Work: An Initial Evaluation of Flow Psychophysiology Across Three Cognitive Tasks

Karen Bartholomeyczik (), Michael Thomas Knierim (), Petra Nieken, Julia Seitz (), Fabio Stano () and Christof Weinhardt ()
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Karen Bartholomeyczik: Karlsruhe Institute of Technology, Institute of Information Systems and Marketing
Michael Thomas Knierim: Karlsruhe Institute of Technology, Institute of Information Systems and Marketing
Julia Seitz: Karlsruhe Institute of Technology, Institute of Information Systems and Marketing
Fabio Stano: Karlsruhe Institute of Technology, Institute of Information Systems and Marketing
Christof Weinhardt: Karlsruhe Institute of Technology, Institute of Information Systems and Marketing

A chapter in Information Systems and Neuroscience, 2022, pp 23-33 from Springer

Abstract: Abstract To accelerate the development of flow-adaptive IT in NeuroIS research, the present work aims to improve the automatic detection of flow in knowledge work-related situations by observing flow emergence across three controlled tasks. In a pretest, we manipulated the type and difficulty of task and recorded subjective (self-reports) as well as objective (EEG features) measures of flow and mental effort. Results indicate that a novel text typing task resembles the expertise of knowledge workers best which is reflected in elevated flow levels across tasks. Difficulty manipulations based on autonomously chosen task difficulty elicited contrasts in flow and mental effort, which was also reflected in the EEG data by Theta band power modulations. This further highlights the utility of autonomy for stimulating flow. We discuss limitations and improvements for the experiment and how this contributes to further research on flow-adaptive IT.

Keywords: Flow; Psychophysiology; Knowledge work; Adaptive systems (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-13064-9_3

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DOI: 10.1007/978-3-031-13064-9_3

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