Information Systems & Service Design

Designing a Flow-Dashboard to display physiological- and flow related data to the user

  • Type:Bachelor and Master
  • Supervisor:

    Nico Loewe

  • Add on:

    Available

  • Motivation & Problem Description

    Flow, the experience in which people are completely focused on an activity and where action takes place fluently, manifests a desirable state in the work environment. Scholars and practitioners consider its role as fundamental because people who often experience flow at work are happier and more productive than those who experience little or no flow at work. Despite rising interest in flow, scholars solely rely maily on established self-reported-scales, which are administered post-task, to measure flow. However, according to the latest research results, flow can also be measured using physiological data such as heart rate variability and machine learning algorithms with good accuracy.

    Knowing on which days of the week and at which times flow is particularly frequent at work can help employees to optimize their daily and weekly planning in order to experience flow more frequently at work.

    Goals

    • Design and create a Dashboard able to display flow related and physiological data

    Required Skills

    • Strong analytical skills
    • Interest in the topic of Flow and Physiological Computing
    • Very good time management, organizational and communication skills
    • Very good programming skills with focus on javascript and web development languages
    • Good English skills

    Contact

    If you are interested in this practical seminar, please contact me via email (nico.loewe@kit.edu)

    References

    • Rissler, R., Nadj, M., Li, M. X., Knierim, M. T., & Maedche, A. (2018, April). Got flow? Using machine learning on physiological data to classify flow. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-6). doi:10.1145/3170427.3188480
    • Knierim, M. T., Rissler, R., Hariharan, A., Nadj, M., & Weinhardt, C. (2019). Exploring Flow Psychophysiology in Knowledge Work. In Information Systems and Neuroscience (pp. 239-249). Springer, Cham. doi:10.1007/978-3-030-01087-4_29