Online learner’s ‘flow’ experience: an empirical study

Namin Shin

British Journal of Educational Technology · 2006 · 299 citations · 16 references

Concepts

TL;DR

Online learning flow is conceptualised as a complex, multi‑dimensional construct—enjoyment, telepresence, focused attention, engagement, and time distortion—based on Csikszentmihalyi’s theory. The study aimed to develop a virtual‑course flow model and test its antecedents, experiences, and consequences among university students. A flow measure was created and administered to 525 undergraduate students in virtual classes to assess relationships among flow antecedents, experiences, and course satisfaction. Results showed that skill–challenge balance predicts flow, flow predicts course satisfaction, and gender and having a clear goal also significantly influence flow levels.

Abstract

Abstract This study is concerned with online learners’‘flow’ experiences. On the basis of Csikszentmihalyi’s theory of flow, flow was conceptualised as a complex, multimentional, reflective construct composing of ‘enjoyment’, ‘telepresence’, ‘focused attention’, ‘engagement’ and ‘time distortion’ on the part of learners. A flow model was put forward with regard to virtual class environment in a traditional university context, comprised with flow antecedents, flow and flow consequences. Based on the model, a virtual‐course flow measure was developed and administered to 525 undergraduate students engaged in virtual classes in order to examine the empirical relationships between measured flow antecedents, flow experiences and flow consequence‐course satisfaction in this case. The analysis of the data showed that: (1) students’ perceptions of their level of ‘skill’ and ‘challenge’ specific to each course are critical to determining the level of flow, (2) flow is a significant predictor of course satisfaction and (3) other than flow, individual differences such as ‘gender’ and ‘having a clear goal’ can make a significant difference in the level of flow in a virtual course. These findings are discussed along with the implications for bringing up a computer‐mediated environment more conducive to flow and learning.

References

16