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Development and evaluation of a prototype to measure flow in realtime with wearables

Development and evaluation of a prototype to measure flow in realtime with wearables
Subject:Development and evaluation of a prototype to measure flow in realtime with wearables
Type:Bachelor Thesis / Master Thesis
Supervisor:

Raphael Rissler

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Status: Open; In cooperation with SAP SE in Walldorf

Motivation

In today’s digital economy, Information Systems (IS) are a significant investment for companies and constitute an indispensable part of employees daily work [1]. Due to technological developments such as multi-media-rich user interfaces, IS are increasingly able to induce highly engaging, interactive, and holistic experiences [1]. One such experience called flow - defined as “the holistic sensation that people feel when they act with total involvement” [2, p. 36] - is considered to be of theoretical and practical significance as this phenomenon is expected to explain a considerable amount of well-being and performance at work [3–5].

However, despite increasing interest of IS scholars in flow [6], a central challenge is the limited knowledge about real-time measurement. Researchers typically rely on self-report scales which are administered post-task (e.g., [7, 8]). As flow occurs during task execution, post-task self-reported measures cannot assess parameters like the length or depth of flow during task execution, and are subject to reporting inaccuracies [9]. The recent rise of the NeuroIS field with the inclusion and development of psychophysiological measures therefore provides new possibilities for objective and continuous measurements of psychological constructs in the context of IS [10, 11]. Especially towards flow in IS use, the benefit of increasingly reliable measurement [12, 13], but also the design of psychophysiologically adaptive IS [14] have been outlined. While previous research on flow-adaptive IS has mainly focused on structured tasks (e.g. gaming and learning [15, 16]) where difficulty levels can be adjusted on the system side, future systems could be extended to more open tasks in business contexts like those of knowledge workers (e.g., software engineers, designers, scientists) through integration of mechanisms that reduce flow-interruptions.

Goal of the Thesis

The overall goal of this thesis project is to develop a prototype, able to send physiological measurement (e.g., heart rate, temperature, etc.) from a wearable (e.g., https://www.empatica.com/e4-wristband) to a computer to process the data. Furthermore, a real-time dashboard should be developed to visualize the real-time data from the wearable. Finally, the prototype should be evaluated rigorously. The deliverables for the thesis project are:
  • Create a running prototype
  • Create a real-time dashboard to visualize the retrieved data
  • Evaluate your prototype rigorously

Skills

  • Very good time management and self-organization skills
  • Very good development skills (python is the preferred language, but all other languages are also possible)
  • Interest in hardware like the empatica (https://www.empatica.com/e4-wristband) is beneficial
  • Good english skills (as the language of the thesis is english)

Contact

Raphael Rissler: raphael.rissler@kit.edu

References

1. Agarwal, R., Karahanna, E.: Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. Manag. Inf. Syst. Q. 24, 665–694 (2000).
2. Csikszentmihalyi, M.: Beyond Boredom and Anxiety. Jossey-Bass, San Francisco, CA (1975).
3. Webster, J., Trevino, L.K., Ryan, L.: The dimensionality and correlates of flow in human-computer interactions. Comput. Human Behav. 9, 411–426 (1993).
4. Ghani, J.A., Supnick, R., Rooney, P.: The Experience of Flow in ComputerMediated and in Face-to-Face Groups. In: Proceedings of the 12th International Conference on Information Systems. pp. 229–237 (1991).
5. Mahnke, R., Benlian, A., Hess, T.: Flow experience in information systems research: Revisiting its conceptualization, conditions, and effects. In: Proceedings of the 35th International Conference on Information Systems. pp. 1–22 (2014).
6. Rissler, R., Nadj, M., Adam, M.T.P.: Flow in Information Systems research: Review, integrative theoretical framework, and future directions. In: International Conference on Wirtschaftsinformatik. pp. 1051–1065 (2017).
7. Jackson, S.A., Eklund, R.C.: Assessing flow in physical activity: The flow state scale-2 and dispositional flow scale-2. J. Sport Exerc. Psychol. 24, 133– 150 (2002).
8. Engeser, S., Rheinberg, F.: Flow, performance and moderators of challengeskill balance. Motiv. Emot. 32, 158–172 (2008).
9. Peifer, C.: Psychophysiological Correlates of Flow-Experience. In: Engeser, S. (ed.) Advances in Flow Research. pp. 139–164. Springer Science, New York, NY (2012).
10. Riedl, R., Léger, P.-M.: Fundamentals of NeuroIS Information Systems and the Brain. Springer Berlin Heidelberg (2016).
11. Riedl, R., Davis, F.D., Hevner, A.R.: Towards a NeuroIS Research Methodology: Intensifying the Discussion on Methods, Tools, and Measurement. J. Assoc. Inf. Syst. 15, i–xxxv (2014).
12. Bastarache-Roberge, M.-C., Léger, P.-M., Courtemanche, F., Sénécal, S., Frédette, M.: Measuring Flow Using Psychophysiological Data in a Multiplayer Gaming Context. In: Davis, F.D. (ed.) Information Systems and Neuroscience, Lecture Notes in Information Systems and Organisation. pp. 187–191 (2015).
13. Labonté-Lemoyne, É., Léger, P.-M., Resseguier, B., Bastarache-Roberge, M.C., Fredette, M., Sénécal, S., Courtemanche, F.: Are We in Flow? Neurophysiological Correlates of Flow States in a Collaborative Game. In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. pp. 1980–1988 (2016).
14. Adam, M.T.P., Gimpel, H., Maedche, A., Riedl, R.: Designing StressSensitive Adaptive Enterprise Systems: Theoretical Foundations and Design Blueprint. In: Gmunden Retreat on NeuroIS. pp. 1–22 (2014).
15. Afergan, D., Peck, E.M., Solovey, E.T., Jenkins, A., Hincks, S.W., Brown, E.T., Chang, R., Jacob, R.J.K.: Dynamic difficulty using brain metrics of workload. In: Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI ’14. pp. 3797–3806 (2014).
16. Liu, C., Agrawal, P., Sarkar, N., Chen, S.: Dynamic Difficulty Adjustment in Computer Games Through Real-Time Anxiety-Based Affective Feedback. Int. J. Hum. Comput. Interact. 25, 506–529 (2009).