山陽論叢 第 27 巻 （2020）
山陽論叢 第 27 巻 (2020)

論文

Implications of the Predictive Processing Model of
Human Cognition for Foreign Language Learning andTeaching
Stephen M. Ryan1)

Keywords: Predictive Processing, ELT, Language Learning
Predictive Processing Theory is a model of human cognition which offers an
explanation of how individuals perceive, learn from, and predict sensory signals fromtheir environment. Since everything we do can be conceptualized in terms of interaction
with our environment, this is a very wide-ranging theory which has implications for all
aspects of human existence.
In this paper, I shall explore the implications of Predictive Processing Theory forthe learning and teaching of a foreign language. The primacy of experience in thelearning process, as envisaged by Predictive Processing Theory, means that certain
language learning activities, such as extensive reading and discovery learning, arerecommended as more effective than others, such as having the teacher explain things
or de-contextualised practice activities.
Learning
Thought Experiment
Imagine you are trapped inside a box (Feldman Barrett, 2020). You cannot get outof the box. You are almost completely cut off from the world outside the box, having only
a few holes in the sides of the box through which to perceive it. Yet, you are dependent
on the world outside the box for the resources you need to live. Over time, you becomeaware, through the holes in the box, that there are changes in the world outside. Someof those changes represent opportunities to increase your store of resources. Others
represent threats to your very existence. In order to take advantage of the opportunities
and avoid the threats, you need to reposition yourself and re-distribute the resourcesthat you have access to.
The box is your skull. Your brain sits inside your skull. It cannot leave your skull
and can gather information about the world outside your skull only through the very
limited “holes” of your five senses: limited physically, because, for example, your eyes canlook in only one direction at once, your ears perceive sound over a limited range of
frequencies and even that only within a certain distance; and limited in terms ofprocessing capacity, as your brain can process only 40 or so of the estimated eleven
million bits of information that are available from your physical environment at any one

1)

山陽学園大学総合人間学部言語文化学科

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Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
and Teaching
Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
andTeaching

time (Zimmerman, 1986). Yet, your brain and body are dependent on resources fromoutside the skull, such as air, food, and water, for their survival. Knowing how tointerpret limited sensory information in a way that makes sense of the world outside is
the difference between sudden death and surviving to pass on your genes to the next
generation.
So, what strategies has the brain, under such evolutionary pressures, developed toget by on the small amount of information available to it? First, it has learned to detectand take note of patterns. In your box, however small the holes, you will notice thepassage from night to day and back again. You will gradually become aware of otherpatterns: the sounds and smells the arrival of certain phenomena: lightening, predators,
companionship.
Second, on the basis of such patterns, it has learned to make predictions about
what will happen next. Having a good idea what to expect is essential to theredistribution of resources (limbs, glucose, hormones, electrolytes, oxygen supply, eventhe location of the box itself – after all, our particular box has arms and legs). Without
this redistribution, the organism will not be positioned to take advantages of theopportunities and to avoid the threats that the brain predicts from its environment(Damasio, 1994). The predictions are made by comparing (incomplete) patterns sensed
through the holes with previously sensed (also incomplete) patterns. Just like the child
who is able to complete the sequence “1, 2, 3,,,” the brain learns to predict the next

parts of a pattern based on its previous experiences of similar patterns.
Third, because the predictions are based on necessarily incomplete information
about the world outside the skull, they will at first be crude and unreliable, so amechanism is needed whereby new data, forming new patterns, can be used to update
the basis on which future predictions are made. Thus, a heavy rain shower does notalways occasion the sound of thunder. If I had predicted, based on limited experience,that the sound, smell, and feel of rain would soon be followed by the rumble of thunder,
further experience would help me to form more nuanced predictions: sometimes thunder,
sometimes no thunder. With further experience, I might then become aware of thesensory antecedents of a thunderstorm as opposed to those of a downpour without
thunder. Further experience would continue to refine the basis of my pedictions fromever more subtle sensory signals that allow me to make ever more accurate predictions
about whether that sounds, looks, and feels a certain way is likely to be accompanied bythunder.
Predictive Processing
This, in essence, is the Predictive Processing model of human cognition (Clark,2015) first developed to account for how we thrive despite having access only toincomplete information (Feldman Barrett, 2020), but now coming to be recognized as thepreeminent theory of how the brain makes sense of the world around it (Campbell, 2016).
An efficient pattern detection routine sifts through whatever data is available. The
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patterns are used to construct a series of “priors,” basically distillations of experience:an understanding, from previous encounters, of the sensory patterns occasioned bychanges in our environment. The priors are used to make specific predictions about
subsequent sensory information. The predictions are used, in turn, to set up the mostappropriate balance of bodily resources to deal with the developing situation. Successful
predictions lead to efficient use of resources. Unfulfilled predictions generate a“prediction error,” a signal that all is not as expected and that the priors for such asituation need to be modified, using the (unpredicted) data that generated the error
signal, to allow for more accurate predictions and, hence, more efficient use of resources
the next time this situation is encountered.
The Predictive Processing model has turned our understanding of human cognition
upside down (Feldman Barrett, 2018). While classical models of cognition begin withsensory input, which the brain reacts to and tries to make sense of, the new model begins
with the sense that our brain has made of the world so far (our priors), and uses it togenerate predictions about the sensory data that is about to be perceived. These
predictions then prime the organism to react. The reaction occurs, unless data comingfrom the senses suggests that the predictions are incorrect (prediction error),necessitating a change in the reaction and a modification of the priors for next time.
This is also, it should be noted, a model of learning (Campbell, 2017). The
modification, by experience, of our expectations about the world is exactly what we meanby learning. It can be conceptualized in two ways: as attempting to make a new piece ofthe puzzle fit our existing understanding of the world; or as allowing the new information
to modify our understanding. In reality, the two processes are one: mutual adjustment
between priors and new sensory information to sharpen our predictive abilities.
The importance of priors in this process needs to be stressed. They are central bothto predicting and to learning. They are formed by experience, or, more precisely, by
repeated exposure to similar experiences (similar patterns perceived outside theskull/box). On the neurophysiological level, such experiences occasion the repeated firingof similar groups of neurons. From our example above, repeated exposure to rainstorms
would cause the firing of a certain group of neurons. The neurons fired would not be
exactly the same, as no two rainstorms are exactly the same. However, there is sufficientsimilarity between rainstorms for a core group of neurons to fire together during eachrainstorm. These neurons that become accustomed to being fired together (Hebb, 1949)
constitute our core concept of a rainstorm and thus are the “priors” on which our brain
bases predictions about future rainstorms.
There is, however, another kind of learning. There are, after all, other brains inother boxes all around us. We can learn not only from our own experience but from thatof others, too, thanks to our ability to communicate our experiences to others across timeand space. Language (verbal or non-verbal) allows us to do this, liberating us from thesolitude of the box. Learning from the experience of others increases our ability togenerate accurate predictions about the world around us exponentially. It is the3- 99 -

Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
and Teaching
Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
andTeachingsuperpower that has made human beings the most (ecologically) successful species everto exist on this planet, able to adapt to just about any environment, to survive there andto thrive. Thanks to language, the brain is a social organism, and learning an essentiallysocial process.
It should be noted that what we get from others is not experience; it is knowledgeof experience. The predictive processing model suggests that knowledge and experience
are treated quite differently. While knowledge is something that we may store in memory
and later call on when it is useful, it is experience that directly builds, modifies, and finetunes our priors. As we shall see, knowledge is not the same as experience, but it can beconverted into experience.
Language Learning
So, how do humans learn language? The same way they learn anything else: byusing priors to generate predictions which either match the data accessed by our senses
or, when they do not, are refined or refocused by it (Kuhl, 2000). This process of attention
to and statistical sampling of patterns is how a baby learns about its physical, emotional,
and social world. It is how we learn language, along with everything else.
It comes as no surprise that language is a series of patterns, whether those patterns
are phonological, orthographical, semantic, grammatical, discourse-level, or sociopragmatic. The codification of these patterns as “Rules of Language” is often mistaken
by learners as a prescriptive process (especially in the case of grammar “rules”) but, infact, what the linguistic is trying to do, just like the new-born baby in the previous
paragraph, is to describe the patterns that make up language in a way that is useful for

predicting, understanding, and producing comprehensible patterns in the future.
Without patterns, language would not be meaningful, since a shared understanding of
the patterns is essential to communication. Thanks to the patterns, a language is bothpredictable and learnable.
Unlike the baby, searching for and codifying linguistic patterns in its environment,
the learner of a second (or foreign) language has access to another learning resource: theexperience of others. Teachers, material writers, and course designers attempt to use
their greater knowledge of the language being learned to design experiences for thelearner which will be helpful in learning the language more efficiently.
The question of how best to help somebody learn a second or foreign language has
stretched human ingenuity for centuries (Kelly, 1976). Our latest understanding of
cognition, and of learning, should be able to shed some light on the issue.
Like a Baby: Exposure to the Language
In order to generate and refine priors about the language and how it is used, thelearner needs to be exposed to the language. The more experience they have of thelanguage in use, the more accurate the priors will become, and the closer theirpredictions about the language will be to how it is actually used. For reception, this4

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means they will be able to make accurate predictions about what they will read or hear
next. For production, it means that what they say or write will more accurately
incorporate norms which will allow their meaning to be understood by others.
One way to gain exposure to the language is through Extensive Reading, readingfor enjoyment and relaxation, rather than for study, at a language level that does not
greatly tax the reader’s ability to understand. Learners who read extensively in theforeign language process large numbers of examples of language use that can be sifted
through and refined into priors by their (unconscious) brains. This is in strong contrast
to the handful of grammar points and example sentences that might be encountered ina more traditional reading lesson.
Although the practice of Extensive Reading has taken root in language teachingpractice over the last 40 years (Bamford & Day, 2004), its equivalent for other skills,
Extensive Listening, Oral Fluency Practice, and Written Fluency Practice (sometimes
known as journaling) are not as widely used. The Predictive Processing model suggeststhat they could have an equally important role to play in providing the wide and deep
experience of language use that will help establish accurate priors.
Also Like a Baby: Natural Language Use
The Predictive Processing model also suggests that, as far as possible, the language
use to which the learner is exposed should be natural. Obscure and archaic language
forms and usages may offer a convenient way to test the limits of a learner’s knowledge,
but they are not helpful in building priors that will guide the learner to useful predictions
about natural, contemporary language use. Similarly, the use of simplified texts should
be encouraged only to the extent that the language used in them is natural and follows
the conventions of texts written for more proficient users.
One of the defining features of natural language use is that it has a context. In
making and fine-tuning priors, the learner’s brain uses data not only about language
form and collocation but also the social and linguistic context in which the language isappropriately used. Decontextualised example sentences and discreet-point vocabulary
learning (such as lists of “3,000 words you need to know for the TOEIC,” Exam World,
2021) are of limited use. As far as possible, language should be presented and studied
within a context in which it would naturally be used.
Nudging the Process Along: Noticing
As we have seen, second/foreign language learners, like babies, can become awareof the patterns of language through extensive exposure. However, the teacher, ormaterials designer, can help the process along. Approaches to language teaching whichemphasise the importance of having learners notice regularities in language form andusage (Schmidt, 1990) are very much in tune with the pattern recognition which is at
the heart of the formation of priors.
One way to do this is to design texts and language learning tasks so that language
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Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
and Teaching
Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
andTeaching

patterns are more salient than in naturally occurring texts. For example, when teaching
about past tense forms, the teacher may select materials in which people recount pastexperiences in a way that deliberately contrasts the use of the various forms. Without
specifically having their attention directed to these forms and their usage, learners gaina more concentrated exposure to these patterns than they would from undoctored
extensive reading or listening texts, thus hastening the pattern recognition process.
Another Nudge: Awareness Rising
A further step in the direction of “helping” students to discover the natural patternsof language comes when a teacher or materials designer directs the learner’s attention
towards a linguistic pattern (Rost, 2020). This can take the form of; a) pointing up thecontext in which the patten occurs; or b) explicitly encouraging the student to focus on
the pattern itself. So, continuing the previous example of a text about past experiences,the learner could be asked a) What was John doing when he was bitten by the jellyfish?”or b) “What tense formed do you see when somebody talks about an activity in the pastthat was interrupted?” Clearly, example b) offers a much bigger nudge that example a),but both types of awareness raising have their place, and they are often used in
combination.
Many modern coursebooks now contain elements of noticing and awareness raisingamong their learning activities, but one book in particular sets out to teach grammar
entirely through these processes. Impact Grammar (Ellis & Gaies, 1998) consists of aseries of units built around grammatical contrasts (such as the past continuous v. simple
past in our jellyfish example). The series editor, Michael Rost (2020) describes the
structure of each unit in this way: 1) examples of typical learner errors involving thecontrast; 2) a listening text, with comprehension questions, featuring the contrast
prominently; 3) a written version of the listening text with blanks to fill in, drawing
attention to the contrast; 4) an invitation for learners to formulate “rules” about thecontrast; 5) a written text in which listeners are encouraged to find errors in the use of
the contrast; 6) a speaking or writing activity giving students the opportunity to use thecontrast; and 7) an explicit statement of the grammar contrast, hidden away in an
appendix at the back of the book.
Learning by Using
As priors are formed from experience, the experience of using the language should
be at the heart of language learning. Since the 1980s and the advent of a Communicative
Approach, activities involving student interaction in the language (pair-work, groupwork) have been a feature of many classrooms. More recently, Task-Based Language
Teaching, in which learners, often working together, attempt to solve non-linguistic tasks
by communicating in the target language, has also brought learner interaction inlanguage to the fore.
Predictive Processing suggests that such activities have a place not only as a means
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山陽論叢 第 27 巻 （2020）(2020)of practicing already-learned or recently-taught language forms, but also as a means of
exploring the language, feeling out what patterns of use are meaningful and useful incommunicating with others. In fact, the logic of Predictive Processing supports the useof interaction in the language to replace more traditional teacher-fronted presentationsof new language. The learners are given a task which involves using a specific language
feature, which they may or may not have experienced using previously. However, thanks
to exposure to large amounts of language in use, the particular language pattern theyneed is unlikely to be completely unfamiliar to them. By using, for example the past
continuous/simple past contrast in a task that involves sharing stories about childhood
accidents (“I was crossing the road, when a car hit me.”), the learners gain experience ofusing the language to communicate, just the kind of experience that shape their priors
and hone them for future predictions.
Non-Interactive Language Practice Activities
There appears to be a case for language practice activities that are not interactive
or exploratory. The criterion for experience to be translated into a prior appears to be the“importance” of the experience (Clark, 2015): experiences that are important are distilled
into priors, those that are not are processed at a lower cognitive level and are often
discarded (= forgotten). This explanation, of course, begs the question of how the brain
in a box judges whether something is important or not. On an evolutionary level,
anything that reduces or increases our chance of survival is important; we tend to
experience this importance as an emotion (fear, lust, hunger, pleasure, etc.) and teachers
have long known that associating an experience, or even a fact, with a strong emotion isa sure-fire way of having their students remember something. However, we cannot reallybuild a language learning model on repeatedly inducing strong emotion.
On a more prosaic level, our brain in a box appears to work on the assumption thata pattern that is repeated has more importance than one that is not (Clark, 2015). So,
one way we can raise the chances that a particular language feature will be incorporated
into a learner’s priors is to arrange for them to encounter that feature repeatedly. On themost basic level this connects with the language classroom staple “Repeat After Me.”
Pattern practice, narrow reading, and parallel writing are more sophisticated versionsof this. Testing and re-testing of the same language point will achieve the same effect. In
fact, learning scientists (Kang, 2016) recommend spaced repetition as one of the mosteffective of learning techniques: repeating the encounter with the new data withincreasing intervals as time goes by.
Explanation/Presentation
What consequences does the model have for a more traditional kind of teaching,where a teacher explains things and the learner takes note? The advantage of an
explanation is that it outsources the work of gaining knowledge to another brain in
another box. It does away with the need to figure out how to integrate new information
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Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
and Teaching
Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
andTeaching

into old patterns by handing the learner a ready-made solution.
In the field of Applied Linguistics, the question of whether conscious learning, as aresult of being told something, can be transformed into acquisition (the ability to use alanguage form automatically, without conscious processing) has been widely and hotly
debated and, at times, researched (Long, 1983). The conclusion is not yet clear. Predictive
Processing, including the formation of priors, is considered by most scholars to be analmost completely unconscious process (Clark, 2015), with consciousness engaged only if
the prediction error is egregiously large (a phenomenon we usually call “surprise”).
What can be said of conscious awareness of language patterns, whether resulting
from teacher explanation or not, is that it allows the patterns to be used for practiceactivities, the kind of activities described above, designed to give experience of thelanguage in use, which we know to generate and refine priors. Receiving information isa poor substitute for experience. In the language classroom, the teacher’s explanation of
new material is a staple, enshrined as the first “P” in the “Presentation, Production, andPractice” approach (SeeTEFL, 2021). An explanation is useful in drawing conscious
attention to a language point but, by itself, by no means guarantees incorporation of thepoint into an unconsciously held prior. For this, the others two “P”s are essential.
Moreover, explanation of a language point tends to be decontextualised, or rather
presented in the context of language learning rather than as a real-world experience. It
is experiences, rather than lectures, that inform priors. As a result, the explanation of alanguage point is most effectively done in the context of a specific example occurring in
the learner’s exposure to the language (a reading text, a search for a way to communicate
an idea) rather than as a discrete-point lesson.
Testing
In many school subjects, testing is a way to gauge what and how much knowledge
a learner has retained. As such, it is often more about memory than about learning. In
foreign language learning, however, where the goal is ostensibly to learn to use theforeign language, accumulating knowledge, as we have seen, is not enough. What weneed to measure is how far the learner has developed appropriate priors to use thelanguage in a variety of situations. As a result, we should be aiming to test not what thelearner knows about the language but what they can do with it.
A good language test will simulate actual language use by causing the learner toproduce predictions and then allowing us to check on the accuracy of those predictions.
This does not mean that testing should be limited to questions in which learners are
overtly asked to generate predictions (as in “Fill in the blanks: ‘fish and‘”or“What do you think Tom will say when he hears the good news?”), although suchquestions have their place. Just as all cognition is based on drawing on priors to makepredictions, acting on those predictions and then modifying priors if the predictions
turned out to be in error, so, too, is all language processing. Traditional language tests,
such as reading comprehension questions, translation, writing in response to a prompt,
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listening for gist or for specific information, all rely on the learner having accurate priors
on which to base their answers, and so are legitimate tests of the accuracy of their priors.
In other words, as long as the testing task simulates real-life language use, it is testinglearning rather than just knowledge.
A further use of testing should also be apparent: regular, low-stakes, classroombased tests that prompt learners to use and re-use language patterns (typically
vocabulary or pronunciation) in order to increase the importance of these patterns fromthe brain’s perspective. Again, the more the testing situation can be made to simulate
real-life language use the more effective such tests will be in generating priors.
Summary
Consideration of foreign language teaching in the light of the Predictive Processing
model of cognition leads us to the conclusion that learning comes from experience. The
more realistic the experiences that learners have in using the language, the more usefultheir learning is likely to be to them. This conclusion would lead us to de-emphasise sometraditional language-teaching practices, such as explaining the language, forced
memorisation, and tests that stimulate only the reproduction of knowledge, in favour ofa focus on activities that allow learners to experience the language.
Large-scale exposure to natural usage of the language; activities that promote
noticing of recurring language features or overtly guide students to focus on them;
contextualized practice with the language; opportunities to encounter new language
repeatedly; pair- and group-work; and tests that require learners to show they can use
the language rather than just reproduce knowledge, are all part of the language teacher’slist of learning activity. The Predictive Processing model suggests that it is on these kindsof activities that we need to focus our students’ attention for maximum learning.
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Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
and Teaching
Ryan:
Implicationsof thePredictive
Processing
Modelof Human
Cognition
for Foreign
Language
Learning
andTeaching

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