Madison Klarkowski Thesis

THE PSYCHOPHYSIOLOGICAL EVALUATION OF THE PLAYER EXPERIENCE Madison Klarkowski B. Games & Interactive Entertainment, Honours (IT). Written under the supervision of Assoc. Prof. Daniel Johnson & Assoc. Prof. Peta Wyeth Assoc. Prof. Simon Smith Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy School of Electrical Engineering and Computer Science Science and Engineering Faculty Queensland University of Technology 2017 i Keywords Challenge; Challenge‒skill balance; Electrocardiography; Electrodermal activity; Electroencephalography; Electromyography; Enjoyment; Flow; Physiology; Player experience; Psychophysiology; Self-determination theory; Video games The Psychophysiological Evaluation of the Optimal Player Experience ii Abstract As video games emerge as a leading form of entertainment, so too does the need for a comprehensive understanding of the player experience. Player experience research thus expands upon this understanding through the lens of psychological constructs such as flow, presence, challenge, competence and self-determination theory. The psychophysiological method presents one approach for evaluating this player experience. A variety of psychophysiological investigations of the player experience have been undertaken, and have contributed novel results that expand upon the understanding of physiological response to video game play. However, these assessments often feature small sample sizes (occasionally only comprising participants of a single gender), or are restricted to employing one or two psychophysiological measures. The value of a study with a large sample size and multiple psychophysiological and subjective measures was thus identified, and undertaken for this program of research. For this study, pilot testing was undertaken to confirm the suitability of the chosen psychophysiological measures, refine the game artefacts and identify the most appropriate subjective measures to use. The full study was conducted with 90 participants playing three game conditions that were manipulated in terms of challenge‒skill balance. These conditions featured one optimal player experience, ‘Balance’ (in which the challenges of the game matched the skills of the player’), and two sub-optimal player experiences, ‘Overload’ and ‘Boredom’ (in which the challenges of the game outstripped, or were outstripped by, the skills of the player). The full study featured the use of both subjective (Player Experience of Needs Satisfaction scale [PENS], flow and Intrinsic Motivation Inventory [IMI]) and psychophysiological (electrodermal activity [EDA], The Psychophysiological Evaluation of the Optimal Player Experience iii electromyography [EMG], electrocardiography [ECG] and electroencephalography [EEG]) measures. Psychophysiological assessment revealed increased positively valenced emotional expressivity associated with increased challenge of the condition; greater EDA was found in the Overload condition than in the Boredom condition; and decreased high-frequency (HF) peak components of heart rate variability (HRV) were found in the Overload condition compared with either Boredom or Balance. Results also revealed increased heart rate (HR) in the Boredom condition. Greater EEG alpha, beta and theta activity was also found in Balance and Overload conditions. These results suggest increased positive valence with challenge, and greater presence of arousal in the Balance (optimal) and Overload conditions; however, increased HR in the Boredom condition indicates some complexities in interpreting psychophysiological data or assessing sub- optimal player experiences. Results for cognitive activity suggest greater alertness, creativity, attentional focus, problem-solving and restfulness in the Balance and Overload conditions, as assessed by electroencephalographic alpha, beta and theta frequency bands. Predictive relationships between physiological responses and specific subjective responses were not found, suggesting that psychophysiological evaluation may be limited in predicting individual components of the player experience. Overall, this study identifies psychophysiological evaluation as an insightful and distinctive approach for assessing the player experience. It proposes recommendations for employing this approach alongside subjective analysis. Despite this, limitations exist for using psychophysiological evaluation in terms of its temporal, financial and methodological costs; however, these limitations may be minimised through certain approaches. The Psychophysiological Evaluation of the Optimal Player Experience iv List of Publications Klarkowski, M., Johnson, D., Wyeth, P., McEwan, M., Phillips, C., & Smith, S. (2016). Operationalising and Evaluating Sub-Optimal and Optimal Play Experiences through Challenge‒Skill Manipulation. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16), 5583‒5594, ACM, Santa Clara, CA. doi: 10.1145/2858036.2858563 Klarkowski, M., Johnson, D., Wyeth, P., Phillips, C., & Smith, S. (2016). Psychophysiology of Challenge in Play: EDA and Self-Reported Arousal. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16), 1930‒1936, ACM, Santa Clara, CA. doi: 10.1145/2851581.2892485 Klarkowski, M., Johnson, D., Wyeth, P., Smith, S., & Phillips, C. (2015). Operationalising and Measuring Flow in Video Games. Proceedings of the Annual Meeting of the Australian Special Interest Group for Computer Human Interaction (OzCHI ’15), 114 118, ACM, Melbourne, Australia. doi: 10.1145/2838739.2838826 Other publications include: Vella, K., Cheng, V. W. S., Johnson, D., Mitchell, J., Davenport, T., Klarkowski, M., & Phillips, C. (2017). Pokémon GO and Social Connectedness. Manuscript submitted for publication. Vella, K., Klarkowski, M., Johnson, D., Hides, L., & Wyeth, P. (2016). The social context of video game play: Challenges and strategies. Proceedings of the Designing Interactive Systems Conference (DIS ’16), 761‒772, ACM, Brisbane, Australia. doi: 10.1145/2901790.2901823 Phillips, C., Johnson, D., Wyeth, P., Hides, L., & Klarkowski, M. (2015). Redefining Videogame Reward Types. Proceedings of the Annual Meeting of the Australian Special Interest Group for Human Interaction (OzCHI ’15), 83‒91, ACM, Melbourne, Australia. doi: 10.1145/2838739.2838782 Johnson, D., Wyeth, P., Clark, M., & Watling, C. (2015). Cooperative Game Play with Avatars and Agents: Differences in Brain Activity and the Experience of Play. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI ’15), 3721‒3730, ACM, Seoul, Republic of Korea. doi: 10.1145/2702123.2702468 The Psychophysiological Evaluation of the Optimal Player Experience v List of Figures Figure 1. The flow channel .......................................................................................................... 11 Figure 2. Divisions of the nervous system. .................................................................................. 23 Figure 3. Russell's Two-Dimensional Model of Emotion ............................................................ 28 Figure 4. The relation of valence and arousal. ............................................................................. 29 Figure 5. Relationships between psychological and physiological domains ............................... 35 Figure 6. Illustrations of various phasically occurring physiological measures .......................... 38 Figure 7. Optimal placement of EDA electrodes on palmar sites ................................................ 40 Figure 8. Schematic representation of facial musculature ........................................................... 41 Figure 9. Suggested facial EMG electrode placement ................................................................. 42 Figure 10. A typical ECG trace and the associated physiological events .................................... 44 Figure 11. EEG traces during various mental states .................................................................... 47 Figure 12. International 10‒20 System ........................................................................................ 51 Figure 13. EDA during play and interviews ................................................................................ 55 Figure 14. Research stages. .......................................................................................................... 78 Figure 15. Screenshot of Left 4 Dead 2. ...................................................................................... 94 Figure 16. Left 4 Dead 2: Tank and Witch boss enemies. ........................................................... 97 Figure 17. Screenshot of Boredom condition (second iteration). ................................................ 99 Figure 18. Screenshot of Balance condition. ............................................................................. 100 Figure 19. Screenshot of Overload condition. .......................................................................... 101 Figure 20. Screenshot of tutorial. ............................................................................................... 103 Figure 21. Boredom condition (second iteration), feat. no combat............................................ 106 Figure 22. Screenshot of Sequencer main menu. ....................................................................... 110 Figure 23. Experimental laboratory ..........................................................................................

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