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

In: Information Systems and Neuroscience

Author

Listed:
  • 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)

  • Petra Nieken

    (Karlsruhe Institute of Technology, Institute of Management)

  • 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)

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.

Suggested Citation

  • Karen Bartholomeyczik & Michael Thomas Knierim & Petra Nieken & Julia Seitz & Fabio Stano & Christof Weinhardt, 2022. "Flow in Knowledge Work: An Initial Evaluation of Flow Psychophysiology Across Three Cognitive Tasks," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 23-33, Springer.
    • Handle: RePEc:spr:lnichp:978-3-031-13064-9_3
    DOI: 10.1007/978-3-031-13064-9_3
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