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

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.