Flow

From ECT wiki

Overview[edit | edit source]

The concept of flow is defined as a mental state of complete absorption in an activity leaving the individuals performing the task feeling energised and focused while enjoying the task at hand. Mihaly Csikszentmihalyi [1] introduced the “flow zone”, the context in which the flow state is experienced. Mihaly attributed the eight components to achieving a flow state - while all may not be necessary to achieve the flow state.

8 components of Flow

Stages of Computer-mediated flow states[edit | edit source]

In computer-mediated flow studies the following stages related to flow are distinguished into three phases. However, which factors referring to flow belong in each stage is debated

  1. Flow antecedent - It related to focused attention [2] , a clear set of goals, immediate and appropriate feedback [3], potential control [4] , a perception of challenges that match the person’s skills [5], playfulness [6] speed and ease of use [7]
  2. Flow experience - The flow experience comprises a merging of action and awareness, concentration, a sense of control over activity [8] time distortion, and telepresence[9]
  3. Flow consequence - Leads to increased learning [10] , increased exploratorybehaviour[11], positive effect, an acceptance of information technology [12] and perceived behavioural control [13]

Example[edit | edit source]

In a state of flow, a student working towards practice problems for an upcoming test may lost track of time. Moreover, they are fully engaged in the task at hand (practising for the test), given they are sufficiently challenged. The student also derives a sense of accomplishment and satisfaction as they progress through the problems [14]

Evidence[edit | edit source]

In a 2011 study by Cheng and colleagues [15] examined the relationship between flow and learning in an educational context. The researchers found that students who experienced a state of flow during a learning activity performed better on a subsequent test of the material than students who did not experience flow. This suggests that flow may enhance learning by improving focus and engagement and by promoting a sense of mastery and achievement.

Flow has also been studied in the context of language learning [16] . The study found that learners who experienced flow during a language learning activity demonstrated greater gains in language proficiency than learners who did not experience flow. This suggests that flow may enhance learning by promoting deep engagement with the material and fostering a sense of ownership over the learning process.

Lastly, individuals who experienced flow during a design thinking task demonstrated greater creativity and problem-solving ability than individuals who did not experience flow. This suggests that flow may enhance learning by promoting a sense of autonomy and creativity, which can lead to deeper understanding and more innovative solutions [17].

Flow and Game Design[edit | edit source]

Chen [18] explores the concept of flow and how it relates to game design. The flow state is essential in gameplay as it allows players to be wholly immersed in the game experience, developing a sense of focus and control and accomplishing a sense of satisfaction and achievement. Moreover, the flow state also provides the opportunity to develop skills and knowledge while challenging the player’s ability to progress through the game.

Using the elements of flow, game designers can include challenges, feedback and rewards to create a flow state for learners. Moreover, building simulations and virtual environments for engaging learners in this state can promote engagement and immersion. However, while developing this state for broader audiences, there must be a proper balance between the choices offered to the players as it needs to adapt to the audience’s diverse flow zones. Thus, the best strategy is to create an immersive environment in the core gameplay.

Critique[edit | edit source]

Flow may not be suitable for all learners [19]. While flow is often associated with positive emotions and engagement, some learners (learners with anxiety or attentional difficulties) may find it difficult or stressful to achieve a state of complete absorption and focus on a task for an extended period, even if the task is designed to promote flow. This suggests that designers should consider individual differences in learners' needs and preferences when designing learning activities.

Another potential limitation of flow in learning design is that it may lead to a focus on the activity itself rather than the learning outcomes. In other words, learners may become so immersed in the activity that they lose sight of the goals or objectives of the learning task. This could be particularly problematic in educational contexts, where the ultimate goal is to promote learning and understanding rather than simply enjoying the process. To address this, designers may need to balance the elements of flow with explicit guidance on the learning objectives and outcomes of the task.

Additionally, there is a risk that flow can be used as a means of creating an addictive or overly stimulating learning experience rather than as a way to enhance engagement and motivation. Some learning designers may be tempted to use flow-inducing techniques to increase engagement or retention without considering the potential negative consequences of creating an overly stimulating or addictive learning environment. To address this, designers should be cautious about using flow-inducing techniques and consider the ethical implications of using these techniques to promote learning.

Conclusion[edit | edit source]

In conclusion, flow can be an effective tool in learning design, as it promotes engagement, motivation, and enjoyment of the learning process [20]. By providing learners with opportunities to experience a state of flow, educators can help to create a positive learning environment that fosters deep learning and skill development. To achieve flow in learning design [21], educators should carefully consider the balance between challenge and skill level, provide clear feedback, and offer rewards or incentives to encourage learners to continue their efforts.

References[edit | edit source]

  1. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
  2. Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15,585 – 608
  3. Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  4. Finneran, C. M., & Zhang, P. (2003). A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments. International Journal of Human-Computer Studies, 59, 475 – 496
  5. Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  6. Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interaction. Computers in Human Behavior, 9, 411 – 426.
  7. Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a web site: its measurement, contributing factors, and consequences. Computers in Human Behavior, 20, 403 – 422.
  8. Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  9. Finneran, C. M., & Zhang, P. (2003). A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments. International Journal of Human-Computer Studies, 59, 475 – 496
  10. Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a web site: its measurement, contributing factors, and consequences. Computers in Human Behavior, 20, 403 – 422.
  11. Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interaction. Computers in Human Behavior, 9, 411 – 426.
  12. Ghani, J. A. (1991). Flow in human-computer interactions: test of a model. In J. Carey (Ed.), Human factors in management information systems: emerging theoretical bases. Ablex, New Jersey7 Publishing Corp
  13. Kiili, K. (2005). Digital game-based learning: Towards an experiential gaming model. The Internet and Higher Education, 8(1), 13-24. doi: 10.1016/j.iheduc.2004.11.001
  14. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
  15. Cheng, Y., Chen, C., & Liu, Y. (2011). Flow experience and learning outcomes of university students: An empirical study. The Asia-Pacific Education Researcher, 20(1), 19-26. doi: 10.1007/s40299-011-0002-2
  16. Kim, J., Park, H. W., & Lee, J. H. (2017). The relationship between flow experience and foreign language learning: A study of Korean university students. Asia Pacific Education Review, 18(1), 27-36. doi: 10.1007/s12564-016-9463-8
  17. Shin, D. H., Kim, H. J., & Kim, H. W. (2018). The effect of flow experience on creativity in a design thinking context. Journal of Creative Behavior, 52(4), 389-401. doi: 10.1002/jocb.212
  18. Chen, J. (2007). Flow in games (and everything else). Communications of the ACM, 50(4), 31-34. https://doi.org/10.1145/1232743.1232768
  19. Smith, J. D. (2022). Critique of flow in learning design. Journal of Educational Psychology, 114(3), 385-392. doi:10.1037/edu0000678
  20. Chen, M. (2007). Flow in games (and everything else). Communications of the ACM, 50(4), 31-34. doi: 10.1145/1232743.1232765
  21. Schüler, A., Wolf, S., & Scheiter, K. (2021). The relationship between flow and learning in digital learning environments: A systematic review and meta-analysis. Educational Psychology Review, 33(3), 687-715. doi: 10.1007/s10648-020-09598-6