The link between flow and performance is moderated by task experience

Palomaki J., Tammi T., Lehtonen N., Seittenranta N., Laakasuo M., Abuhamdeh S., ...Daha Fazla

COMPUTERS IN HUMAN BEHAVIOR, cilt.124, 2021 (SSCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 124
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.chb.2021.106891
  • Dergi Adı: COMPUTERS IN HUMAN BEHAVIOR
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, IBZ Online, Aerospace Database, Applied Science & Technology Source, CINAHL, Communication Abstracts, Computer & Applied Sciences, EBSCO Education Source, Education Abstracts, Educational research abstracts (ERA), INSPEC, Linguistics & Language Behavior Abstracts, Metadex, Psycinfo, Social services abstracts, Sociological abstracts, Civil Engineering Abstracts
  • Anahtar Kelimeler: Flow, Learning, Game, Experience, Performance, SELF-DETERMINATION, SKILL, CHALLENGE, SCALE, MODEL, PLAY
  • Marmara Üniversitesi Adresli: Evet

Özet

Flow is an intrinsically motivating (i.e. 'autotelic') psychological state of complete absorption in moment-tomoment activity that can occur when one performs a task whose demands match one's skill-level. Flow theory proposes that Flow causally leads to better performance, but empirical evidence for this assumption is mixed. Recent evidence suggests that self-reported Flow may not be linked to performance-levels per se, but instead to deviations from anticipated performance (the so-called flow deviation, or F-d effect). We aimed to replicate and extend these results by employing a high-speed steering game (CogCarSim) to elicit Flow, and specifically focused on the moderating effects of learning and task experience on the F-d effect. In a longitudinal design, 18 participants each played CogCarSim for 40 trials across eight sessions, totaling 720 measurements across participants. CogCarSim reliably elicited Flow, and learning to play the game fit well to a power-law model. We successfully replicated the F-d effect: self-reported Flow was much more strongly associated with deviationfrom-expected performance than with objective performance levels. We also found that the F-d effect grew stronger with increasing task experience, thus demonstrating an effect of learning on Flow. We discuss the implications of our findings for contemporary theories of Flow.