Abstract
The intention of the following chapter is to shed light on primary factors that play a role in defining what we coin as an optimal learning environment, an environment that buttresses an experience of flow for learners (see Chap. 10 by Andersen in this volume). The chapter begins with an overview of flow related research reframed for the purpose of measuring the experience of flow in learning. A longitudinal study of flow experienced by students undertaking a Massive Open Online Course (MOOC) is described. The Flow in Education scale (EduFlow Scale) used in the study is described and the results of the study presented. The results illustrate the potential value and relevance of measuring flow in learning as well as the relation to the extended concept of cognitive absorption. We conclude the chapter with a presentation of a model of heuristic learning: the Individually Motivated Community model. The model builds upon three major theories of the self: Self-Determination, Self-Efficacy and Autotelism-Flow.
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Notes
- 1.
According to Keller and Landäußer (2012) and Rheinberg (2008), the term ‘demands’ is more appropriate than the term ‘challenge’. Keller and Landäußer argue that “the propositions regarding the boundary conditions of flow experience can be simplified and reduced […to] the antecedent factor ‘Perceived fit of skill and task demands’” (2012, p. 53). “In any case, a sense of control is definitely one of the most important components of the flow experience, whether or not an ‘objective’ assessment justifies such feelings” (Csikszentmihalyi 1975, p. 46).
- 2.
- 3.
In balance with two other basic psychological needs, autonomy and competence.
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Heutte, J., Fenouillet, F., Kaplan, J., Martin-Krumm, C., Bachelet, R. (2016). The EduFlow Model: A Contribution Toward the Study of Optimal Learning Environments. In: Harmat, L., Ørsted Andersen, F., Ullén, F., Wright, J., Sadlo, G. (eds) Flow Experience. Springer, Cham. https://doi.org/10.1007/978-3-319-28634-1_9
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