Csikszentmihalyi (1990) flow theory is based on several interrelated psychological constructs: ability, attitude, cognition, emotion, motivation, and personality. When perfectly combined in a task, they catapult a person into a state of flow commonly known as being in the zone. Csikszentmihalyi refers to this as an optimal experience. “He discovered that people around the world had shared descriptions for flow such as the joy it yields, episodes of unfettered concentration, suspension of time, and the spontaneous automaticity during an experience” (Rogers, 2017, p.15). Flow occurs differently for different people. For example, individuals who aren’t good at playing games, or find the game uninteresting, wouldn’t experience flow during gameplay.
Instructional Design of Flow
As an instructional designer, I want to create optimal learning experiences. Flow theory has components similar to those used for effective instruction based on cognitivism. For instance, Sweller, Van Merriënboer, and Paas’ (1998) cognitive load theory recommends reducing distractions (extraneous elements) and delivering germane and intrinsic elements of instruction in manageable chunks. This correlates to the component of enjoyment in flow theory in that a person can only fully enjoy a task if they’re capable of completing it. Flow theory has eight main components that engender enjoyment: manageable tasks, deep concentration, clear goals, immediate feedback, effortless involvement, learner autonomy, the metamorphosis of self, and suspension of time. These components parallel best practices for instruction.
To make learning more enjoyable, I’d apply Miller’s s (1956) seven-plus-or-minus-two principle regarding the limitations surrounding the amount of input that can be remembered at any given time. Adherence to Miller’s principle will make a task more manageable. Additionally, I’d use Gagne’s (1985) nine events of learning to establish the optimal cognitive conditions for effective learning to occur. Three of Gagne’s events (i.e., state objective, provide feedback, provide practice) correlate with the enjoyment phenomena of flow theory (i.e., task has clear goals, task provides immediate feedback, sense of control). See my blog post to learn more about the Application of Gagne’s 9 Events of Instruction to WDE Games.
Furthermore, the aspects of clear goals and feedback correlate to the self-regulation of learning. Self-regulation processes include rehearsal, selection of important information, and metacognitive strategies. The selection of important information aids deep concentration for possible enjoyment of the optimal experience. To learn more about self-regulation, read my blog titled, Where Learning Happens.
A vehicle for cognitive learning experiences with flow potential would be well-designed educational games. Elements of good game design include goal-oriented, stimulating, active learning that is anchored in instruction (Shute, Reiber, & Van Eck, 2012). While playful (fun) learning has similar elements, the key difference is active learning, as many playful activities passively follow the teacher’s directives.
Another difference is the challenge aspect of gaming that adapts to the learners’ abilities, whereas playful learning is free form. A challenge provides learners with intrinsic motivation and the pathway to achieve learner autonomy to make their own way through the world (Thai et al., 2009). This is different from traditional learning activities that are teacher-directed. Chatti, Jarke, and Specht (2010) described this as a knowledge push, whereas knowledge-pull is akin to gaming where the learner gravitates toward knowledge.
Videogames, particularly, have similar characteristics for creating a context for flow. According to Csikszentmihalyi, clarity, centering, choice, commitment, and challenge are the characteristics necessary for unified flow experience. In my opinion, these are the flow characteristics that can be found in gameplay: (Rogers, 2017)
- Clarity with explicit gaming context, rules, feedback, and goals;
- Centering with narrative providing storyline;
- Choice with multi-levels of play, numerous episodes, variety of characters and actions, and guilds;
- Commitment via resets (do-overs) and new virtual identity; and
- Challenge via incremental task difficulty and reward system.
The challenge for instructional designers is to determine how to use the potentiality of videogames to engender flow for educational purposes. Based on the aforementioned research on cognitive learning best practices and flow theory, we have a theoretical basis to move forward.
Chatti, M. A., Jarke, M., & Specht, M. (2010). The 3P learning model. Educational Technology and Society, 13(4), 74-85.
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY: Harper & Row.
Gagné, R. M. (1985). The Conditions of Learning. New York, NY: Holt, Rinehart, & Winston.
Miller, G. A. (1956). The magical number seven, plus-or-minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.
Rogers, S. A. (2017). A Massively Multiplayer Online Role-Playing Game with language learning strategic activities to improve English grammar, listening, reading, and vocabulary (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 10265484)
Shute, V. J., Rieber, L. P., & Van Eck, R. (2012). Games…and…Learning. In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional design and technology (pp. 321-332). Upper Saddle River, NJ: Merrill Prentice Hall.
Sweller, J., Van Merriënboer, J., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review 10(3), 251–296. doi:10.1023/A:1022193728205
Thai, A. M., Lowenstein, D., Ching, D., & Rejeski, D. (2009). Game changer: Investing in children’s play to advance children’s learning and health. New York, NY: The Joan Ganz Gooney Center at Sesame Workshop.
Sandra Annette Rogers, Ph.D.