ABSTRACT
Many studies conducted in non-virtual activities have shown that flow significantly influences performance, yet studies in virtual activities often reveal only a weak association. This paper begins by building a theoretical explanatory model, and then conducts 3 empirical studies to explore this question. Study 1 exams the mechanism of weak association in two virtual activities. Study 2 tests the effectiveness of a potential approach to strengthen this association. In Study 3 we applied our proposed model and design approach to optimize a VR tennis game. Results show that the influence of flow on performance was not significant in those virtual activities where the primary task and the operation of interactive artifacts were less congruent such that the artifacts can lead to flow experience that is independently of the primary task. Our research offers a theoretical and empirical basis on how to optimize virtual environment design and maximize positive effect of the flow experience.
Supplemental Material
- Wilfried Admiraal, Jantina Huizenga, Sanne Akkerman, and Geert ten Dam. 2011. The concept of flow in collaborative game-based learning. Computers in Human Behavior. 27, 1185--1194. Google ScholarDigital Library
- Ozlem Baydas, Turkan Karakus, F. Burcu Topu, Rabia Yilmaz, Mehmet E. Ozturk, Yuksel Goktas. 2015. Retention and flow under guided and unguided learning experience in 3D virtual worlds. Computers in Human Behavior. 44, 96--102. Google ScholarDigital Library
- Riccardo Berta, Francesco Bellotti, Alessandro De Gloria, Danu Pranantha, and Carlotta Schatten. 2013. Electroencephalogram and physiological signal analysis for assessing flow in games. IEEE Transactions on Computational Intelligence and AIin Games. 5, 2: 164--175.Google ScholarCross Ref
- Yulong Bian, Chenglei Yang, Fengqiang Gao, Huiyu Li, Shisheng Zhou, Xiaowen Sun, Xiangxu Meng. 2016. A framework for physiological indicators of flow in vr games: construction and preliminary evaluation. Personal and Ubiquitous Computing. 20, 5: 821--832. Google ScholarDigital Library
- Yulong Bian, Chenglei Yang, Dongdong Guan, Sa Xiao, Fengqiang Gao, Chia Shen, and Xiangxu Meng. 2016. Effects of Pedagogical Agent's Personality and Emotional Feedback Strategy on Chinese Students' Learning Experiences and Performance: A Study Based on Virtual Tai Chi Training Studio. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI' 16), 433- 444. Google ScholarDigital Library
- Bressler and Alec Bodzin. 2013. A mixed methods assessment of students' flow experiences during a mobile augmented reality science game. Journal of Computer Assisted Learning. 29, 6: 505--517.Google ScholarCross Ref
- Max Birk and Regan L. Mandryk. 2013. Control your game-self: effects of controller type on enjoyment, motivation, and personality in game. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI' 17), 685--694. Google ScholarDigital Library
- Cristina Calvo-Porral, Andrés Faíña-Medín, and Manuel Nieto-Mengotti. 2017. Exploring technology satisfaction: An approach through the flow experience. Computers in Human Behavior. 66, 400--408. Google ScholarDigital Library
- Michael Chau, Ada Wong, Minhong Wang, Songnia Lai, Kristal W.Y. Chan, Tim M.H. Li, Debbie Chu, Ian K.W. Chan, Wai-ki Sung. 2013. Using 3D virtual environments to facilitate students in constructivist learning. Decision Support Systems. 56, 1: 115--121.Google ScholarDigital Library
- Li-Keng Cheng, Ming-Hua Chieng, and Wei-Hua Chieng. 2014. Measuring virtual experience in a threedimensional virtual reality interactive simulator environment: A structural equation modeling approach. Virtual Reality. 18, 3: 173--188. Google ScholarDigital Library
- Csikszentmihalyi Mihaly. 1990. Flow: The psychology of optimal experience. New York: Harper and Row.Google Scholar
- Csikszentmihalyi Mihaly, Abuhamdeh Sami, and Nakamura Jeanne. 2005. Flow. In Elliott AJ, Dweck CS (eds.), Handb. Competence Motiv. Guilford, New York, 598--608.Google Scholar
- Stefan Engeser. 2012. Advances in flow research. Springer Science & Business Media.Google Scholar
- Stefan Engeser, and Falko Rheinberg. 2008. Flow, moderators of challenge-skill-balance and performance. Motivation and Emotion. 32, 158--172.Google ScholarCross Ref
- Stefan Engeser, Falko Rheinberg, Regina Vollmeyer, and Jutta Bischoff. 2005. Motivation, Flow-Erleben und Lernleistung in universitären Lernsettings {Motivation, flow experience and performance in learning settings at university}. Zeitschrift für Pädagogische Psychologie. 19, 159--172.Google ScholarCross Ref
- Xitao Fan and Stephen A. Sivo. 2005. Sensitivity of fit indexes to misspecified structural or measurement model components: Rationale of two-index strategy revised. Structural Equation Modeling. 12, 343--367.Google ScholarCross Ref
- Christina M. Finneran and Ping Zhang. 2003. A person-- artefact--task (PAT) model of flow antecedents in computer-mediated environments. International Journal of Human-Computer Studies. 59, 4: 475--496. Google ScholarDigital Library
- Wei Gai, Chenglei Yang, Yulong Bian, Mingda Dong, Juan Liu, Yifan Dong, Chengjie Niu, Cheng Lin, Xiangxu Meng, and Chia Shen. 2017. Supporting Easy Physical-to-Virtual Creation of Mobile VR Maze Games: a New Genre. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI' 17), 5016--5028. Google ScholarDigital Library
- Rosanna E. Guadagno, Jim Blascovich, and Cade Mccall. 2007. Virtual Humans and Persuasion: The Effects of Agency and Behavioral Realism. Media Psychology. 10, 1--22.Google Scholar
- László Harmat, Örjan de Manzano, Töres Theorell, Lennart Högman, Håkan Fischer, Fredrik Ullén. 2015. Physiological correlates of the flow experience during computer game playing. International Journal of Psychophysiology. 97, 1: 1--7.Google ScholarCross Ref
- Li-An Hoa and Tsung-Hsien Kuo. 2010. How can one amplify the effect of e-learning? An examination of hightech employees' computer attitude and flow experience. Computers in Human Behavior. 26, 1: 23--31. Google ScholarDigital Library
- Ting-Chia Hsu. 2017. Computers & Education Learning English with Augmented Reality: Do learning styles matter? Computers & Education. 106, 137--149.Google ScholarCross Ref
- Cheng-Yu Hung, Jerry C. Sun, and Pao-Ta Yu. 2015. The benefits of a challenge: student motivation and flow experience in tablet-PC-game-based learning. Interactive Learning Environments. 23, 2: 172--190.Google ScholarCross Ref
- Susan Jackson, Stephen K. Ford, Jay Kimiecik, and Herb Marsh. 1998. Psychological correlates of flow in sport. Journal of Sport & Experience Psychology. 20, 358--378.Google ScholarCross Ref
- Susan A. Jackson. 2010. Positive performance states of athletes: Toward a conceptual understanding of peak performance. The Sport Psychologist. 6, 156--171.Google ScholarCross Ref
- Susan A. Jackson, Pat Thomas, Herb Marsh, and Christopher J. Smethurst. 2001. Relationship between flow, self-concept, psychological skills, and performance. Journal of Applied Sport Psychology. 13, 129--153.Google ScholarCross Ref
- Kalle Jegers. 2007. Pervasive game flow: understanding player enjoyment in pervasive gaming. Computers in Entertainment. 5, 1: 9. Google ScholarDigital Library
- Puneet Kaur, Amandeep Dhir, Sufen Chen, and Risto Rajala. 2016. Flow in context: Development and validation of the flow experience instrument for social networking. Computers in Human Behavior. 59, 358--367. Google ScholarDigital Library
- Johannes Keller and Herbert Bless. 2008. Flow and regulatory compatibility: An experimental approach to the flow model of intrinsic motivation. Personality and social psychology bulletin. 34, 2: 196--209.Google Scholar
- Johannes Keller and Frederik Blomann. 2008. Locus of control and the flow experience: An experimental analysis. European Journal of Personality. 22, 589--607.Google ScholarCross Ref
- Raymond MacDonald, Charles Byrne, and Lana Carlton. 2006. Creativity and flow in musical composition: An empirical investigation. Psychology of Music. 34, 292--306.Google ScholarCross Ref
- Mitchell McEwan, Alethea Blackler, Daniel Johnson and Peta Wyeth. 2014. Natural mapping and intuitive interaction in videogames. In CHI PLAY '14 Proceedings of the First ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, 191--200. Google ScholarDigital Library
- Adrian D. McInman and Robert Grove. 1991. Peak moments in sport: A literature review. Quest. 43, 333--351.Google ScholarCross Ref
- Nakamura Jeanne and Csikszentmihalyi Mihaly. 2009. Flow theory and research. In C. R. Snyder & S. J. Lopez (Eds.), Oxford Hand- book of positive psychology. Oxford University Press, Oxford, UK, 195--206.Google Scholar
- Richard M. Ryan, C. Scott Rigby, and Andrew Przybylski. 2006. The motivational pull of video games: A self-determination theory approach. Motivation and Emotion. 30, 4: 347--363.Google ScholarCross Ref
- Ulrich Schiefele and Emmanouil Roussakis. 2006. Die Bedingungen des Flow-Erlebens in einer experimentellen Spielsituation {Experimental conditions for experiencing flow in computer games}. Zeitschrift für Psychologie mit Zeitschrift für angewandte Psychologie und Sprache & Kognition. 214, 207--219.Google Scholar
- Julia Schüler. 2007. Arousal of flow experience in a learning setting and its effects on exam performance and affect. Zeitschrift für Pädagogische Psychologie. 21, 217--227.Google ScholarCross Ref
- Julia Schüler and Sibylle Brunner. 2009. The rewarding effect of flow experience on performance in a marathon race. Psychology of Sport and Exercise. 10, 1: 168--174.Google ScholarCross Ref
- Bing Shi, Yonggang Hu, and Feng Shi. 2003. A Study on the Appraisal Criteria of University Students' 24stroke Taiji. Journal of Nanyang Teachers' College (Natural Sciences Edition). 2, 3: 3--5.Google Scholar
- Dong-Hee Shin, Frank Biocca, and Hyunseung Choo. 2013. Exploring the user experience of threedimensional virtual learning environments. Behaviour & Information Technology. 32, 2: 203--214. Google ScholarDigital Library
- Gary L. Stein, Jay Kimiecik, J.Daniels, and Susan A. Jackson. 1995. Psychological antecedents of flow in recreational sport. Personality and Social Psychology Bulletin. 21, 125--135.Google ScholarCross Ref
- Oliver Stoll and Andreas Lau. 2005. Flow-Erleben beim Marathonlauf. Zeitschrift für Sportpsychologie. 12, 3: 75--82.Google ScholarCross Ref
- Yu-Shan Su, Wei-Lun Chiang, Chin-Tarn J. Lee, and Han-Chao Chang. 2016. The effect of flow experience on player loyalty in mobile game application. Computers in Human Behavior. 63, 240--248. Google ScholarDigital Library
- Xiaowen Sun, Yafang Wang, Gerard de Melo, Wei Gai, Yuliang Shi, Lu Zhao, Yulong Bian, Juan Liu, Chenglei Yang, and Xiangxu Meng. 2017. Enabling Participatory Design of 3D Virtual Scenes on Mobile Devices. In Proceedings of the Conference WWW'17. Google ScholarDigital Library
- Penelope Sweetser and Peta Wyeth. 2005. GameFlow?: A Model for Evaluating Player Enjoyment in Games. Computers in Entertainment. 3, 3: 1--24. Google ScholarDigital Library
- Jari Takatalo, Göte Nyman, and Leif Laaksonen. 2008. Components of human experience in virtual environments. Computers in Human Behavior. 24, 1: 1--15. Google ScholarDigital Library
- Ron Tamborini, Nicholas D. Bowman, Allison Eden, and Ashley Organ. 2010. Defining media enjoyment as the satisfaction of intrinsic needs. Journal of Communication. 60, 4: 758--777.Google ScholarCross Ref
- Tahmine Tozman, Elisabeth S. Magdas, Hamish G. MacDougall, and Regina Vollmeyer. 2015. Understanding the psychophysiology of flow: A driving simulator experiment to investigate the relationship between flow and heart rate variability. Computers in Human Behavior. 52, 408--418. Google ScholarDigital Library
- Paul van Schaik, S. Martin, and Michael Vallance. 2012. Measuring flow experience in an immersive virtual environment for collaborative learning. Journal of Computer Assisted Learning. 28, 4: 350--365. Google ScholarDigital Library
- Astrid M. von der Pütten, Nicole C. Krämer, Jonathan Gratch, and Sin-Hwa Kang. 2010. ? It doesn ' t matter what you are!" Explaining social effects of agents and avatars. Computers in Human Behavior. 26, 6: 1641 -- 1650. Google ScholarDigital Library
- Li-Chun Wang and Ming-Puu Chen. 2010. The effects of game strategy and preference-matching on flow experience and programming performance in gamebased learning. Innovations in Education and Teaching International. 47, 1: 39--52.Google ScholarCross Ref
Index Terms
- Exploring the Weak Association between Flow Experience and Performance in Virtual Environments
Recommendations
The Role of the Field Dependence-independence Construct on the Flow-performance Link in Virtual Reality
I3D '20: Symposium on Interactive 3D Graphics and GamesThe flow experience-performance link is commonly found weak in virtual environments (VEs). The weak association model (WAM) suggests that distraction caused by disjointed features may be associated with the weak association. People characterized by ...
Empathy and embodied experience in virtual environment
This study investigates the user experience to clarify what it is like to experience stories in VR (virtual reality) and how immersion influences story experiences in immersive storytelling. This study explores the immersive storytelling context, ...
The impact of virtual reality (VR) technology on sport spectators' flow experience and satisfaction
AbstractVirtual Reality Spectatorship (VRS) is becoming an emerging sport media consumption trend as it delivers such optimal experience that maximizes user satisfaction. To clearly understand media user experiences in VRS, the current study ...
Highlights- Media type and sport involvement determine flow in Virtual Reality Spectatorship.
Comments