8 – Flow Theory
We acquire language by understanding compelling messages that foster flow experience.
To become advanced in any language, we need time. Native speakers need the first 10 years of their lives to master complex grammar and a large vocabulary. We solve this problem with The Big Data Theory.
Native speakers can easily get big data because they spend years living with a language. Also, if you are learning Spanish as a second language, and if you live in Spain for a few years, you can easily get big data. With these two examples, learners do not need to struggle with motivation for learning language because language acquisition just happens as they live.
But if learners are studying a foreign language in school, or if they are studying for a big language test, they will probably struggle with motivation. In fact, many language learners do not have strong reasons to learn. They just study because they are required to do so. We know that these learners need big data input, retrieval, spacing, and interleaving. But they still have a problem. What will motivate them to learn?
Motivation is complex and hard to measure. But we can state a simple and elegant theory about motivation that can help us solve many motivational problems. We will call it the input-flow theory, and it can give helpful guidance for the study and teaching of languages. The input-flow theory comes from Krashen’s (2014) idea that we need to make input powerfully interesting or — compelling. Krashen calls this the “compelling input hypothesis.” Of course, Krashen stands for the centrality or supremacy of input in language education. But with compelling input, he adds that the best input is not just comprehensible. The best input comes to us as both comprehensible and compelling.
When input is comprehensible and compelling, it produces a special kind of rich experience, which is called “flow” (Csikszentmihalyi, 1991). When we experience flow, we feel a sense of control and concentration. We sense that our skills match the challenge in front of us. We don’t feel self-conscious; we forget our problems. We experience time differently. And we experience an activity as pleasurable, as its own reward. This is called “autotelic experience” where the experience itself is its own reward.
Imagine a language class in a state of flow. The class is studying a text, trying to understand the meaning, vocabulary, and grammar. In the lesson, the students feel a sense of control. That is, they feel confidence as they work on their tasks. The text is a little difficult. But students feel that their skills match the challenge. They don’t feel self-conscious. That is, when the teacher calls on students, they don’t feel nervous or worried about what others think. They don’t fear making mistakes. They are also so focused on the lesson, that they don’t think about time. If they were bored, the time would go slow. But they are interested, so the time seems to fly by quickly. And lastly, they are enjoying the lesson. They find the pleasure of the lesson its own reward.
This sounds like a strange language lesson because most people haven’t experienced anything like it. And it might be especially rare for a grammar lesson or a lesson just focused on the bits of language. In general people may experience flow in many situations, such as surfing, watching movies, and playing games. But we do know of one famous flow producing experience that relates to language learning. According to Massimini, Csikszentmihalyi, and Fave, (1988), the most common optimal experience reported in flow research is reading.
As mentioned before, we know that extensive reading provides a way to get big data. But if we use compelling stories for extensive reading, then it also works with our input-flow theory. For example, Mcquillan and Conde (1996) reported that when students read for pleasure, they more commonly experienced flow. With assigned texts, flow occurred more often when students had an interest in the text. Students experienced flow when they perceived personal or intellectual benefits coming from the texts, and fiction produced flow much more than non-fiction.
Nell (1988) likens flow in reading to a “reading trance.” And readers most often experience a reading trance when they read fiction. Nell says that “Pleasure reading is a form of play. It is free activity standing outside ordinary life; it absorbs the player completely” (p. 7). However, we can use the style of fiction to report facts. Wolfe & Johnson (1975) say that narrative non-fiction can imitate fiction. The story is a narrative of true events, which uses the elements of fiction. Thus, we can tell stories that are not true (fiction), but we can also tell true stories. Thus, with both fiction and non-fiction, we can use story grammar. With story grammar, we read or hear about (1) characters, who (2) face trouble and conflict, and (3) who try to get out of the trouble. As a formula, we can write the basic elements of story grammar like this: “character + conflict + attempted extrication” (Gottschall, 2012).
Compelling stories bring “flow-input.” Thus, we can use the input-flow hypothesis to guide our choice of classroom and reading materials. That is, as we prepare lessons, we can ask these simple questions: Will students find this content compelling? Will it help students experience flow? At the same time, we need to remember that reading motivation is complex. For example, Kirchhoff found that Japanese learners of English “often experienced flow-like concentration in an L2 extensive reading class as well as in L1 pleasure reading” (2013, p. 208). However, Kirchhoff did not find a correlation between flow and reading amount. That is, students who experienced flow didn’t always read a lot.
This is understandable. Imagine a person who never reads fiction. But one day he picks up the novel “True Grit” by Charles Portis (2010). He starts reading it and finds it so compelling that he stays up all night reading the book. After he finishes, he does not continue reading more fiction. In this case, flow did not necessarily motivate an extensive reading of fiction. However, flow did motivate the reading of “True Grit.” And it remains possible that flow could motivate more and more reading. For example, Wigfield & Guthrie found that many L1 learners experienced flow, and that when learners enjoyed stories (input-flow), they read more. That is, “An intrinsic motivation composite predicted amount and breadth of reading more strongly than did an extrinsic motivation composite” (1997, p. 420).
Clearly, readers can experience flow that comes through compelling input in stories, and this raises several big questions. Does flow experience correlate to big data reading (300,000 to 1,000,000 words)? That is, will big data readers report more flow experience than those who do not read big data? Will compelling input that promotes flow enable readers to sustain reading longer and more enjoyably than students who attempt long-term traditional study or standardized test preparation? What are the traits of texts that make input compelling and thus foster flow experience?
In the end, the input-flow hypothesis gives us questions. But they are good questions that we should try to answer. Moreover, we cannot easily argue against flow. Good teachers want to inspire students with interesting lessons. Nobody wants to kill flow. Yes, motivation is complex, but if we use input that promotes flow, then we may solve many motivational problems before they ever happen.