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= Overview =
= Overview =
The experiential gaming model is a learning approach that integrates experiential learning theory, [[flow | flow theory]] and game design. The focus is understanding how the factors contributing to a flow state can be used in educational games to maximise its impact. The model emphasises the importance of providing players with immediate feedback and clear goals and challenges that match their skill level.
The experiential gaming model is a learning approach that integrates [[Experiential Learning | experiential learning theory]], [[flow | flow theory]] and game design. The focus is understanding how the factors contributing to a flow state can be used in educational games to maximise its impact. The model emphasises the importance of providing players with immediate feedback and clear goals and challenges that match their skill level.


== Stages of Computer-mediated flow states ==
== Stages of Computer-mediated flow states ==
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
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  
 
# <u>Flow antecedent </u> - It related to focused attention <ref> Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15,585 – 608  </ref> , a clear set of goals, immediate and appropriate feedback <ref> Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608  </ref>, potential control <ref> 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 </ref> , a perception of challenges that match the person’s skills <ref> Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608  </ref>, playfulness <ref> 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.  </ref> speed and ease of use <ref> 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.</ref>
 
# <u>Flow experience </u> - The flow experience comprises a merging of action and awareness, concentration, a sense of control over activity <ref> Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608  </ref> time distortion, and telepresence<ref> 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 </ref>
 
# <u>Flow consequence </u> - Leads to increased learning <ref> 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.</ref> , increased exploratorybehaviour<ref> 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.  </ref>, positive effect, an acceptance of information technology <ref>  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 </ref> and perceived behavioural control <ref> 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 </ref>


= Evidence =
= Evidence =

Latest revision as of 14:51, 24 February 2023

Overview[edit | edit source]

The experiential gaming model is a learning approach that integrates experiential learning theory, flow theory and game design. The focus is understanding how the factors contributing to a flow state can be used in educational games to maximise its impact. The model emphasises the importance of providing players with immediate feedback and clear goals and challenges that match their skill level.

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

Evidence[edit | edit source]

Examples[edit | edit source]

Critique and Design Implications[edit | edit source]

Challenges[edit | edit source]

References[edit | edit source]

  1. ↑ Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15,585 – 608
  2. ↑ Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  3. ↑ 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
  4. ↑ Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  5. ↑ 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.
  6. ↑ 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.
  7. ↑ Chen, H., Wigand, R., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15, 585 – 608
  8. ↑ 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
  9. ↑ 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.
  10. ↑ 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.
  11. ↑ 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
  12. ↑ 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
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