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Ending the Reading Wars: Reading Acquisition From Novice to Expert



There is intense public interest in questions surrounding how children learn to read and how they can best be taught. Research in psychological science has provided answers to many of these questions but, somewhat surprisingly, this research has been slow to make inroads into educational policy and practice. Instead, the field has been plagued by decades of “reading wars.” Even now, there remains a wide gap between the state of research knowledge about learning to read and the state of public understanding. The aim of this article is to fill this gap. We present a comprehensive tutorial review of the science of learning to read, spanning from children’s earliest alphabetic skills through to the fluent word recognition and skilled text comprehension characteristic of expert readers. We explain why phonics instruction is so central to learning in a writing system such as English. But we also move beyond phonics, reviewing research on what else children need to learn to become expert readers and considering how this might be translated into effective classroom practice. We call for an end to the reading wars and recommend an agenda for instruction and research in reading acquisition that is balanced, developmentally informed, and based on a deep understanding of how language and writing systems work.
Psychological Science in the
Public Interest
2018, Vol. 19(1) 5 –51
© The Author(s) 2018
Reprints and permissions:
DOI: 10.1177/1529100618772271
Learning to read transforms lives. Reading is the basis
for the acquisition of knowledge, for cultural engage-
ment, for democracy, and for success in the workplace.
Illiteracy costs the global economy more than $1 trillion
(U.S. dollars) annually in direct costs alone (World
Literacy Foundation, 2015). The indirect costs are far
greater because the failure to attain satisfactory literacy
blocks people from acquiring basic knowledge, such as
understanding information about hygiene, diet, or safety.
Consequently, low literacy is a major contributor to
inequality and increases the likelihood of poor physical
and mental health, workplace accidents, misuse of medi-
cation, participation in crime, and welfare dependency,
all of which also have substantial additional social and
economic costs (World Literacy Foundation, 2015). Low
literacy presents a critical and persistent challenge
around the world: Even in developed countries, it is
estimated that approximately 20% of 15-year-olds do
not attain a level of reading performance that allows
them to participate effectively in life (Organisation for
Economic Cooperation and Development, 2016).
Not surprisingly, then, there has been intense public
interest for decades in how children learn to read. This
interest has often been realized in the form of vociferous
argument over how children should be taught to read—a
period of exchange that has become known as the “read-
ing wars” (for reviews, see Kim, 2008; Pearson, 2004).
Over many years, the pendulum has swung between
arguments favoring a phonics approach, in which the
sounds that letters make are taught explicitly (Chall, 1967;
Flesch, 1955), and a whole-language approach, which
emphasizes the child’s discovery of meaning through
experiences in a literacy-rich environment (Goodman,
1967; F. Smith, 1971). Most famously, Goodman (1967)
characterized reading not as an analytic process but as a
“psycholinguistic guessing game” in which readers use
their graphic, semantic, and syntactic knowledge to guess
772271PSIXXX10.1177/1529100618772271Castles et al.Reading Acquisition
Corresponding Author:
Anne Castles, Department of Cognitive Science, Macquarie University,
Sydney, Australia, 2109
Ending the Reading Wars: Reading
Acquisition From Novice to Expert
Anne Castles1,2, Kathleen Rastle3, and Kate Nation2,4
1Department of Cognitive Science, Macquarie University; 2Australian Research Council Centre
of Excellence in Cognition and its Disorders; 3Department of Psychology, Royal Holloway,
University of London; and 4Department of Experimental Psychology, University of Oxford
There is intense public interest in questions surrounding how children learn to read and how they can best be taught.
Research in psychological science has provided answers to many of these questions but, somewhat surprisingly, this
research has been slow to make inroads into educational policy and practice. Instead, the field has been plagued by
decades of “reading wars.” Even now, there remains a wide gap between the state of research knowledge about learning
to read and the state of public understanding. The aim of this article is to fill this gap. We present a comprehensive
tutorial review of the science of learning to read, spanning from children’s earliest alphabetic skills through to the
fluent word recognition and skilled text comprehension characteristic of expert readers. We explain why phonics
instruction is so central to learning in a writing system such as English. But we also move beyond phonics, reviewing
research on what else children need to learn to become expert readers and considering how this might be translated
into effective classroom practice. We call for an end to the reading wars and recommend an agenda for instruction
and research in reading acquisition that is balanced, developmentally informed, and based on a deep understanding
of how language and writing systems work.
reading, language, reading acquisition, phonics, text comprehension
6 Castles et al.
the meaning of a printed word. More recently, a three-
cueing approach (known as the Searchlight model in the
United Kingdom) has become pervasive, in which begin-
ning readers use semantic, syntactic, and “graphophonic”
(letter-sound) cues simultaneously to formulate an intel-
ligent hypothesis about a word’s identity (for discussion,
see Adams, 1998). Debate around these broad approaches
has played out across the English-speaking world.
The beginnings of the reading wars go back more
than 200 years, when Horace Mann (then the Secretary
of the Massachusetts Board of Education) rallied against
teaching the relationship between letters and sounds,
referring to letters as “skeleton-shaped, bloodless,
ghostly apparitions” and asserting “It is no wonder that
the children look and feel so death-like, when com-
pelled to face them” (Adams, 1990, p. 22; see also Kim,
2008). It was standard practice at that time to teach
children to read in such a way that they learned the
links between letters and sounds explicitly. This prac-
tice goes back to the 16th century (Hart, 1569/1969;
Mulcaster, 1582), but it became especially popular
through Noah Webster’s “blue-backed spellers” (so
called because of their blue binding) produced during
the 18th and 19th centuries. In particular, The American
Spelling Book (Webster, 1787) was continuously repub-
lished over the following century and became one of
the best-selling books of all time (Kendall, 2012).
Today, research in psychological science spanning
several decades has provided answers to many of the
most important questions about reading. There is a rich
literature documenting reading development and a
large and diverse body of work on the cognitive pro-
cesses that serve skilled reading in adults. Much of this
evidence is highly relevant to the question of how
reading should be taught and, pleasingly, it has been
examined in comprehensive government reviews of
reading instruction, including those conducted in the
United States (e.g., the National Reading Panel, 2000),
the United Kingdom (e.g., the Rose Review; Rose,
2006), and Australia (e.g., the Department of Education,
Science and Training, or DEST; Rowe, 2005). These
reviews have revealed a strong scientific consensus
around the importance of phonics instruction in the
initial stages of learning to read. The research underpin-
ning this consensus was surveyed in an article pub-
lished in this journal more than 15 years ago (Rayner,
Foorman, Perfetti, Pesetsky, & Seidenberg, 2001). Yet
this research has been slow to make inroads into public
policy. Although some progress has been made rela-
tively recently, most notably in the United Kingdom,
there remains a very wide gap between the state of
research knowledge about learning to read and the
state of understanding in the public and in professional
domains. Further, even where there is strong national
guidance around reading instruction, implementation often
devolves to the local level and is influenced by variations
and biases in teacher training (see, e.g., Buckingham,
Wheldall, & Beaman-Wheldall, 2013; Seidenberg, 2017).
The quality and scope of the scientific evidence today
means that the reading wars should be over. But strong
debate and resistance to using methods based on scien-
tific evidence persists (see, e.g., Moats, 2007; Seidenberg,
2017). Why should this be the case? We believe that there
have been two major limitations in the presentations of
the scientific evidence in the public and professional
domains. The first limitation is that, although there have
been many reviews describing the strength of the evi-
dence for phonics instruction (e.g., Rose, 2006), it is
more difficult to find an accessible tutorial review
explaining why phonics works. Our experience is that
once the nature of the writing system is understood, the
importance of phonics instruction in the initial stages of
learning to read becomes obvious.
The second limitation is that there has not been a
full presentation of evidence in a public forum about
reading instruction that goes beyond the use of phonics.
It is uncontroversial among reading scientists that com-
ing to appreciate the relationship between letters and
sounds is necessary and nonnegotiable when learning
to read in alphabetic writing systems and that this is
most successfully achieved through phonics instruction.
Yet reading scientists, teachers, and the public know
that reading involves more than alphabetic skills. To
become confident, successful readers, children need to
learn to recognize words and compute their meanings
rapidly without having to engage in translation back to
sounds. Therefore, it is important to understand how
children progress to this more advanced form of word
recognition and how teaching practice can support this.
In addition, reading comprehension clearly entails more
than the identification of individual words: Children are
not literate if they cannot understand text. We believe
that the relative absence of discussion of processes
beyond phonics has contributed to ongoing resistance
to the use of phonics in the initial stages of learning to
read. That is, instead of showing how a foundation of
phonic knowledge permits a child to understand and
gain experience with text, this imbalance has allowed
a characterization of phonics as “barking at print” (read-
ing aloud robotically without understanding) to con-
tinue among educationalists (e.g., Davis, 2013; Samuels,
2007) and public figures (e.g., Rosen, 2012).
We aim in this review to address these important
omissions. We define the goal of reading as being able
to understand text—a task of immense complexity (see
Box 1 for more detail on what we mean by reading)—
and review what is known about how children achieve
this goal. We then consider how reading should be
Reading Acquisition 7
taught to best support its development. Our article is
structured in three major parts, spanning from chil-
dren’s early experiences of mapping letters to sounds
to the fluent text processing characteristic of expert
readers. In the first part, we explain why cracking the
alphabetic code is so central to learning to read in
alphabetic writing systems such as English and why it
forms the foundation for all that comes later. Our cen-
tral message here is that that the writing system matters.
Although our review focuses primarily on reading in
alphabetic systems, by providing a detailed account of
the structure of different writing systems and the way
in which they systematically map onto oral language,
we aim to demystify the evidence about learning to
read. In doing so, we hope to provide our readers with
deep insight as to why particular teaching methods
support initial reading acquisition.
In the second part, we move beyond alphabetic
skills, reviewing the latest research on the acquisi-
tion of fluent word-recognition skills. Here, our central
Box 1. What Is Reading?
The goal of reading is to understand what has been read, and thus the goal of reading development
must be to develop a system that allows children to construct meaning from print. Our review takes a
broad perspective on reading development, reflecting the fact that reading is complex. To set the scene,
consider the challenges posed by this simple, two-sentence text:
What needs to happen for us to understand this text? First and foremost, we need to identify the indi-
vidual words. This in itself is hugely challenging, requiring us to distinguish a word such as jam from
all the numerous similar-looking words it could be, such as
or We must have a means of
identifying words that may be unfamiliar, such as , and of analyzing words which appear in a
complex form, such as worried Words are the building blocks of comprehension, but it’s not just a
matter of identifying words: Their meanings need to be activated, appropriate for the context. This
means understanding jam with respect to traffic, not the fruit preserve. Causal connections need to be
made within and across sentences to understand that and in the second sentence refer to
in the first sentence.
Despite its brevity, this text demands a good deal of background knowledge: that Denise was probably
on her way to work but was running late because of heavy traffic. We can further infer, perhaps prompted
by our knowledge of Denise, her routines or her attitudes. Perhaps she is in a car or on a bus; we might
wish to ponder her relationship with her boss. Perhaps she has been late several times recently and is
thus especially worried about their reaction; maybe she is en route for a meeting that, if missed, will
have important consequences. We might know her boss, and make inferences based on his or her
reputation, prompting us to think about the extent or nature of Denise’s worry. We have no idea, but
these are just some of the potential elaborations and inferences that are licensed by the text.
Other factors also add complexity. Making connections within a text and integrating information with
background knowledge places demands on working memory. Dealing with an ambiguous word such
as might engage executive skills if the contextually inappropriate meaning is activated and then
needs to be ignored.
This brief analysis makes clear that reading is complex. Even a straightforward, two-sentence text has
the potential to require a range of mental operations, ranging from word recognition through to an ap-
preciation of theory of mind. The challenge facing the beginner reader is thus substantial.
Denise was stuck in a jam. She was worried what her boss would say.
jar ham.
she her Denise
8 Castles et al.
message is that experience matters. Children’s experi-
ences in reading are often subsumed under terms such
as print exposure. However, to understand fully how
children become skilled word readers, we need to
unpack these terms and capture in much greater detail
the rich and wide-ranging reading experiences that chil-
dren have and how these experiences interact with their
knowledge at different points in learning.
In the final section, we move to text comprehension.
Here, our key message is that reading comprehension
is multifaceted. To understand its complexities, we need
to consider the range of linguistic and cognitive pro-
cesses that are implicated in text comprehension and
appreciate how these depend on children’s knowledge,
as well as features of the text itself and the purpose
and goals of the reading situation.
At the end of each major section, we consider the
implications of the science we have reviewed for the
classroom and address controversies surrounding the
teaching of these different aspects of reading. We note
here that our focus is on typical reading development
and on effective instruction in standard classroom set-
tings. The extensive and important body of work on
the complex needs of children with various kinds of
learning difficulties is beyond our scope. Our aim,
rather, is to provide our readers with the scientific back-
ground they need to promote best practice in the class-
room and so minimize the proportion of children who
struggle with reading as a result of nonoptimal teach-
ing, or “instructional casualties (Lyon, 2005).
1. Cracking the Alphabetic Code
If a child is exposed to a rich spoken-language environ-
ment, that child will almost certainly learn to under-
stand and produce spoken language. As Pinker (2009)
puts it, “there is almost no way to prevent it from hap-
pening, short of raising a child in a barrel” (p. 29). The
same cannot be said for reading. Although reading is a
heritable trait (Olson, Keenan, Byrne, & Samuelsson,
2014), influenced by multiple genes interacting with
environmental factors in complex ways, it is neverthe-
less a learned skill that typically requires years of
instruction and practice. When children begin to learn
to read, they usually already have relatively sophisti-
cated spoken-language skills, including knowledge of
the meanings of many spoken words. The challenge of
reading is to learn to associate arbitrary visual symbols—
patterns of lines, curves, and dots—with those meanings.
It is difficult for a skilled reader with perhaps decades
of practice to appreciate the scale of this challenge.
Although a child might be able to memorize the shapes
or distinguishing features of a handful of words (e.g.,
yellow has “two sticks in the middle”; Seymour & Elder,
1986), the high confusability of written language
together with limitations on memory means that this
strategy would be very unlikely to scale up to a full
vocabulary. Instead, children need to learn to analyze
the printed forms of words and map these onto mean-
ing. Precisely how they might most easily accomplish
this depends on the nature of the writing system, so
we turn now to considering the world’s writing systems
and how they are structured.
1.1. Writing systems and their
implications for learning to read
Writing is a recent cultural invention, and writing sys-
tems vary substantially in how their visual symbols
represent spoken language. All writing systems are a
kind of code for spoken language, and learning to read
requires children to crack how the code works for their
language. Once this is understood, children have the
means to access their rich spoken-language knowledge
from print. The code that children must learn varies
across different languages. Indeed, for languages that
have more than one script (e.g., Japanese), children may
need to learn more than one code, as these scripts may
map onto spoken language in different ways. There are
three major categories of writing system: alphabetic (in
which symbols represent individual sounds or pho-
nemes; e.g., English), syllabic (in which symbols repre-
sent whole syllables; e.g., Japanese Hiragana), and
morphophonetic (in which symbols represent elements
of both meaning and sound; e.g., Chinese). This latter
class of writing system is sometimes referred to as logo-
graphic. There are also variations within these broad
categories; for example, an abjad is an alphabetic writ-
ing system that represents the consonants of spoken
language but not many of the vowels (e.g., Hebrew; for
a description of writing systems associated with 131
languages, see Chang, Chen, & Perfetti, 2018).
There are many reasons why particular writing sys-
tems emerge for particular languages: Political influ-
ences, invasions, nationalism, and missionary activities
have all contributed to the nature of writing around the
world (for historical information about particular writ-
ing systems, see, e.g., Ager, 2018; Kamusella, 2009).
However, one interesting idea, developed by Katz and
Frost (1992), that is worthy of further study is that particu-
lar writing systems may be more suitable for individual
languages than others—indeed, that “most languages get
the orthography they deserve” (p. 67). For example, spo-
ken Mandarin Chinese is characterized by a small number
of syllables and consequently by a high number of
homophones, or words with different meanings but pro-
nounced the same way. A troublesome instance of this
is the word si, which means both the number 4 and
death, which is why it is quite common for hotels in
China to skip from the third floor to the fifth floor. If
Reading Acquisition 9
Chinese were written using an alphabet (particularly
an alphabet with a one-to-one mapping between letters
and sounds), then the ambiguity in the spoken language
would be mirrored in the written language, leading to
many homographs, or words with different meanings
spelled in exactly the same way. The development of
Chinese characters to communicate the spoken language
prevents some of this ambiguity. In contrast, Katz and
Frost (1992) argue that Indo-European languages such
as English are characterized by less homophony and a
larger number of much more complex syllables. The use
of an alphabet in these cases permits the spoken lan-
guage to be communicated visually with a relatively
simple set of letters mapping to sounds (Katz & Frost,
1992; see also Frost, 2012).
There have been decades of argument, often invok-
ing pedagogical philosophy, over how children can best
learn to associate the visual symbols of writing to spo-
ken language. However, a crucial point is that the most
appropriate way to learn this mapping is governed not
by pedagogical philosophy but by the nature of the
writing system the child needs to learn. In alphabetic
systems, the phonemes of the language are represented
by letters or groups of letters (graphemes; e.g., b /b/,
ph /f/). If a child learns to decode that symbol-to-
sound relationship, then that child will have the ability
to translate printed words into spoken language,
thereby accessing information about meaning. In con-
trast, failing to appreciate the symbol-sound mapping
in an alphabetic language would effectively turn read-
ing acquisition into a paired-associate learning task, as
the child attempts to memorize meanings for individual
printed words. Although this strategy may be possible
for a relatively small number of words, it is hard to
imagine it scaling up to the tens of thousands of English
words that adult readers can recognize (Brysbaert,
Stevens, Mandera, & Keuleers, 2016).
Indeed, one virtue of learning to read in an alpha-
betic system is that each learning experience can facili-
tate future learning. For example, learning the
pronunciation of vet can help the child to learn other
words, such as van and vow. This capacity for gener-
alization is much more limited in Chinese. Chinese
characters are built from phonetic and semantic com-
ponents that can provide some basis for generalization
(although the information in these components may
have quite low reliability; Lü, 2017). However, there are
many more of these components that must be memo-
rized than is the case for an alphabetic system; esti-
mates suggest that there are 895 phonetic components
and 214 semantic components that give rise the 4,300
or so characters thought to be sufficient for full literacy
(Katz & Frost, 1992). Because of the difficulty and slow
pace of learning characters through primary school, an
alphabetic system for writing Chinese known as Pinyin
was introduced in 1958. Pinyin instruction in Mainland
China runs alongside the learning of Chinese characters
in the early years of schooling and has been shown to
facilitate reading achievement (Lin etal., 2010).
Even among the alphabetic systems that are the focus
of this article, there is substantial variation in their
orthographic depth, or the transparency with which
symbols (graphemes) represent sounds (phonemes).
Shallow orthographies are characterized by a consistent
relationship between graphemes and phonemes (e.g.,
Italian), whereas deep orthographies are characterized
by substantial inconsistency in this relationship (e.g.,
English). Nevertheless, even in deep orthographies,
pronunciation is still strongly governed by the spelling-
sound relationship. To put this into quantitative terms,
Coltheart, Rastle, Perry, Langdon, and Ziegler (2001) esti-
mated that approximately 80% of English monosyllables
could be pronounced using a relatively small set of
rules relating graphemes to phonemes. In the remaining
20% of cases, typically only one grapheme deviates
from its most frequent pronunciation (e.g., pint, have,
chef; see Section However, most of the work
on spelling-sound relationships has been conducted
with monosyllables; researchers are only just beginning
to consider spelling-sound relations in letter strings
with more than one syllable (e.g., Ktori, Mousikou, &
Rastle, 2018; Mousikou, Sadat, Lucas, & Rastle, 2017;
Perry, Ziegler, & Zorzi, 2010).
Research on learning to read in English has often
focused on the high degree of inconsistency in the
relationship between spelling and sound (for discus-
sion, see Share, 2008). However, it is important to rec-
ognize that this inconsistency can take a variety of
forms, and this ultimately may have implications for
reading instruction. English contains words with highly
unusual spelling-sound relations, such as friend, yacht,
aisle, and plaid, but there are also cases in which sur-
rounding context can mitigate apparent spelling-sound
inconsistency. For example, the vowel in wash appears
unusual compared with cash, stash, and dash. However,
this vowel pronunciation is shared with other words
beginning with the letter w (e.g., want, wand, watt).
Likewise, although the vowel pronunciation in thread
is inconsistent with that in beach, leap, and seat, it is
shared with other words ending with the letter d (e.g.,
bread, stead, dead). If these subregularities are taken
into account, then the consistency of English spelling
increases (Kessler & Treiman, 2001). Further, as we
discuss in Section 2.2.3, many spelling-sound inconsis-
tencies arise because of the preservation of morphologi-
cal regularities in printed words (e.g., magic vs.
magician; Treiman & Bourassa, 2000).
Substantial research has been conducted to deter-
mine whether orthographic depth has an impact on
reading acquisition in alphabetic writing systems. In
10 Castles et al.
the most ambitious study of this type, Seymour, Aro,
and Erskine (2003) compared children’s reading aloud
of simple words and nonwords across 13 European
languages at the end of the first year of schooling
(including nonwords in addition to words in studies of
reading acquisition is important, given that they permit
an assessment of a child’s decoding skills that is rela-
tively independent of his or her existing word knowl-
edge; see Section 1.4.2). Results showed a substantial
impact of orthographic depth: Children reading in Eng-
lish lagged well behind those reading in languages with
shallow orthographies (e.g., Finnish). However, it is
difficult to draw firm conclusions about the impact of
orthographic depth from cross-linguistic comparisons
of this nature because of the differences in the age at
which children begin schooling in different countries.
In the data reported by Seymour etal. (2003), the Eng-
lish children were up to 2 years younger than those in
the other groups at the point of testing, and there were
probably also variations in the nature of reading instruc-
tion across the groups.
L. H. Spencer and Hanley (2004) were able to inves-
tigate orthographic depth in a natural experiment made
possible by the schooling system in Wales at that time.
The children could attend either Welsh-medium or
English-medium schools. Welsh, in contrast to English,
has a shallow orthography, but across the two types of
school, the children started at the same age, had the
same form of reading instruction, and were broadly
equivalent in socioeconomic status. Results of reading-
aloud tests conducted across three time points during
the first year of reading instruction showed a dramatic
benefit for the children learning to read in Welsh. These
data indicate that orthographic depth has a substantial
impact on acquiring spelling-sound knowledge in the
initial stages of learning to read. However, we are
unaware of any evidence that these initial gains as a
result of shallow orthography translate to later advan-
tages in reading comprehension. Further, although
orthographic depth affects the time taken to learn the
spelling-to-sound mapping, the cognitive factors under-
lying reading performance appear to be similar across
different European languages (Caravolas etal., 2012;
Ziegler etal., 2010).
1.2. The development of alphabetic
decoding skills
The nature of the writing system determines what will
be required for children to make links between print
and meaning, but it does not specify precisely how they
do so. Therefore, we now turn to the rich body of work
that has explored in detail how children’s skills in
alphabetic decoding develop—delineating what chil-
dren initially bring to this complex task, how their
knowledge changes over development, and the way in
which their instructional experiences shape and modify
their learning. We outline here just some key insights
from this large body of work, providing references to
reviews that expand on the theory and evidence in
1.2.1. Inducing the alphabetic principle: The child’s
initial hypotheses about print. If left to their own
resources, what hypotheses will preliterate children form
about print and its relationship to sound and meaning?
That is, on exposure to printed words, will children natu-
rally induce the basic alphabetic principle that symbols
represent sounds? If not, what is required for them to do
so? These were the questions asked by Byrne and col-
leagues in a detailed series of experiments on preschool
children between the ages of 3 and 5 years (Byrne, 1992;
Byrne & Fielding-Barnsley, 1989, 1990; for a review, see
Byrne, 2005). The experimenters used a transfer of train-
ing paradigm: Children who knew no letter names were
taught to read aloud pairs of written words, such as fat
and bat. Subsequently, they were challenged with a
transfer task in which they were shown, for instance, the
written word fun and then asked whether the word was
“fun” or “bun. The results were clear: Across more than
80 preschool children who participated in the various
experiments, virtually none succeeded on the transfer
task. When left to their own devices, the children showed
no evidence of inducing the alphabetic principle.
Further investigations were then conducted to deter-
mine what triggers the acquisition of the alphabetic
principle in preschool children. Reliable success on the
transfer task was typically achieved only when children
were trained such that they could (a) segment pho-
nemes in spoken words and identify their initial pho-
nemes and (b) recognize the graphic symbols that
corresponded to the key sounds in the transfer task
(i.e., b and f in the example above; Byrne & Fielding-
Barnsley, 1989). Note that once children had gained the
alphabetic insight needed to succeed in the transfer
task, their learning was relatively robust and could be
generalized. For example, most children who were able
to perform the task for a symbol in the initial position
of the word were also successful when the same symbol
was at the end.
As noted, the children in Byrne etal.’s studies who
induced the alphabetic principle were typically able to
segment phonemes explicitly in spoken words; for
example, they could state that the word pot begins with
a /p/ sound. This finding is consistent with a large body
of research on the importance of the metalinguistic skill
of phonemic awareness in reading acquisition, stemming
from the work of the Libermans and their colleagues
(A. M. Liberman, Cooper, Shankweiler, & Studdert-
Kennedy, 1967; I. Y. Liberman, Shankweiler, Fischer, &
Reading Acquisition 11
Carter, 1974; for review, see Melby-Lervåg, Lyster, &
Hulme, 2012). This group proposed that to crack the
alphabetic code, children must be able to abstract the
relevant phonemic units from the stream of the speech
they hear. This is a nontrivial task, because the segmen-
tation of an acoustic signal does not correspond in any
straightforward way with segmentation at the phoneme
level: In continuous speech, phonemes overlap and run
together. A large body of research is also consistent with
Byrne etal.’s second finding—that acquiring the alpha-
betic principle requires children to learn the visual sym-
bols of the writing system that correspond to phonemes.
An intimate and reciprocal association exists among
children’s letter knowledge, their phonemic awareness,
and their skill in alphabetic decoding (see, e.g., Castles
& Coltheart, 2004; Castles, Coltheart, Wilson, Valpied, &
Wedgwood, 2009; Hulme, Bowyer-Crane, Carroll, Duff,
& Snowling, 2012).
In summary, it is clear that the fundamental insight
that graphemes represent phonemes in alphabetic writ-
ing systems does not typically come naturally to chil-
dren. It is something that most children must be taught
explicitly, and doing so is important for making further
progress in reading. Fortunately, however, the founda-
tional knowledge required to trigger this insight is not
extensive and, once acquired, puts children on a path
to accruing further knowledge and firmly establishing
their alphabetic decoding skills.
1.2.2. Phases of alphabetic decoding development.
Once children have acquired the alphabetic principle,
they can move on to learning the specifics of the relation-
ships between graphemes and phonemes in their writing
system and to applying this knowledge in their reading
and spelling. This developmental process is itself a com-
plex one: Several researchers have identified broad “phases”
that children move through, reflecting the sequence of key
skills that emerge with their increasing expertise (e.g.,
Ehri, 1999, 2002, 2005a; Frith, 1985; for reviews, see Ehri,
2005b, 2017). In all cases, the first phase posited is one
before the acquisition of the alphabetic principle in
which children “read” words by relying on visual cues,
rote learning, or guessing. Of interest here, however, is
how decoding develops once the alphabetic insight has
According to Ehri’s phase theory (2005b, 2017), chil-
dren first move into a partial alphabetic phase where
they begin to use a rudimentary form of decoding.
Persuasive evidence for this strategy comes from a clas-
sic study by Ehri and Wilce (1985; see also Rack, Hulme,
Snowling, & Wightman, 1994) in which beginning read-
ers were required to associate letter strings with spoken
words over a series of trials. The letter strings were of
two types: Those in one set were highly visually distinc-
tive and were printed in different sizes and cases (e.g.,
wBc taught as the spelling of “giraffe”), whereas those
in the other set contained cues as to the sounds of the
associated words (e.g., jrf for “giraffe”). Ehri and Wilce
observed that prereaders—children who could read no
words and had little or no letter knowledge—found the
visually distinctive spellings easier to learn, whereas
children who could read some words and showed some
evidence of mastery of the alphabetic principle learned
the phonetic spellings more easily. Clearly these latter
children could not yet be considered skilled alphabetic
decoders, but they were nevertheless beginning to use
insights from their alphabetic knowledge to make links
between spellings and sounds. Spelling is an important
driver of the transition into the partial alphabetic stage
(Frith, 1985). Even a very limited repertoire of letters
allows children to generate invented spellings that cap-
ture the sounds of words. Although beyond the scope
of our review, it is worth noting that spelling skills are
tightly linked to the process of reading acquisition and
that spelling often operates in the service of reading
(for a comprehensive review of spelling development,
see Treiman & Kessler, 2014).
With further instruction and experience in reading
and spelling, children move to what Ehri describes as
a full alphabetic phase. They now have a much more
complete knowledge of grapheme-phoneme relations
and can apply this knowledge consistently across a
whole printed word. Children can now decode unfa-
miliar printed words, allowing them to access their
pronunciations and through them their meanings (if the
words are familiar in oral form). Even where the alpha-
betic decoding process results in an incorrect pronun-
ciation (e.g., “breek” for break), children may be able
to draw on their oral vocabulary to correct the partial
decoding attempt (Tunmer & Chapman, 2012) or use
the mispronunciation itself to make links between
printed and spoken words (Dyson, Best, Solity, &
Hulme, 2017; Elbro & de Jong, 2017). Put simply, in this
phase of reading acquisition, the child has cracked the
alphabetic code. This is the critical starting point for
learning to read, even though much remains to be
acquired beyond this, as we will see later in our review.
1.3. Cracking the alphabetic code: Summary
We have established that learning to read in an alpha-
betic writing system such as English requires the acqui-
sition of the alphabetic principle—the insight that the
visual symbols of the writing system (graphemes) rep-
resent the sounds of the language (phonemes). We have
also established that virtually all children require at
least some assistance in learning this principle. Foun-
dational skills such as phonemic awareness and letter
knowledge are key precursors to this alphabetic insight,
and these skills and bodies of knowledge interact
12 Castles et al.
reciprocally in complex ways (for reviews, see Bowey,
2005; Hulme etal., 2012; Marinus & Castles, 2015).
Once this initial insight is acquired, children acquire
increasingly sophisticated skills in alphabetic decoding,
moving in broad phases from partial to full decoding
ability (Ehri, 2017). In the next section, we consider the
implications of these scientific findings for classroom
instruction in relation to the initial periods of reading
1.4. Implications for the classroom
1.4.1. Systematic phonics instruction. Systematic pho-
nics refers to reading instruction programs that teach pupils
the relationship between graphemes and phonemes in an
alphabetic writing system. As explained above, the rationale
for systematic phonics instruction is that a relatively small
body of knowledge of how graphemes relate to phonemes
provides children with the ability to decode most words in
their language. Provided that children have adequate vocab-
ulary, this sound-based representation can then be used to
access the meanings of those words. If instruction instead
focused on teaching children to associate printed words
with their meanings directly, then learning to read would
require memorization of tens of thousands of individual
printed words. Thus, systematic phonics instruction should
be viewed as a natural and logical consequence of the man-
ner in which alphabetic writing systems represent spoken
Phonics programs are systematic when they teach
grapheme-phoneme correspondences in an ordered
manner. Such instruction is more straightforward in a
shallow orthography than in a deep orthography, such
as that of English. In English, there are just 26 letters
to represent about 44 phonemes (depending on dia-
lect), and thus the relevant grapheme-phoneme corre-
spondences include single-letter graphemes (e.g., d
/d/, f /f/) and multiletter graphemes (e.g., ch /ʧ/,
ai /eɪ/, eigh /eɪ/, and ng /ŋ/). In one case, a
single letter maps onto two phonemes, x /ks/. As
reviewed earlier, English has considerable inconsistency
in its spelling-sound mapping, leading most systematic
phonics programs to focus on teaching the more com-
mon correspondences (for a table of the most frequent
grapheme-to-phoneme relationships for English mono-
syllables, see Rastle & Coltheart, 1999).
The evidence for the effectiveness of phonics instruc-
tion is extensive and has been surveyed comprehen-
sively elsewhere. The most influential analysis arose as
a result of the National Reading Panel convened by the
U.S. Congress in the 1990s. Part of the work of the panel
was to conduct a quantitative meta-analysis evaluating
the impact of systematic phonics instruction compared
with nonsystematic or no-phonics instruction (Ehri
etal., 2001). On the basis of the combined results of
38 experiments involving 66 treatment-control compari-
sons, this meta-analysis yielded a moderate impact of
phonics instruction (i.e., effect size) of 0.41,1 which was
much larger when phonics instruction began early (d =
0.55) than when it began after the first grade (d = 0.27).
Phonics instruction improved decoding, spelling, and
text comprehension. This result is broadly consistent
with a subsequent meta-analysis of 14 randomized con-
trolled trials investigating the impact of phonics instruc-
tion on reading accuracy (Torgerson, Brooks, & Hall,
2006), although the overall effect size was reduced (d =
0.27). More recently, two meta-analyses have concluded
that phonics instruction is an effective intervention for
poor readers (Galuschka, Ise, Krick, & Schulte-Korne,
2014; McArthur etal., 2012). The only meta-analysis
that has examined the longer-term outcomes of phonics
instruction produced a variable pattern of results, but
there was clear evidence of benefits on spelling (Suggate,
These research studies have underpinned recom-
mendations to adopt systematic phonics instruction
methods in the United States (National Reading Panel,
2000), Australia (Rowe, 2005), and the United Kingdom
(Rose, 2006). However, these recommendations have
been implemented fully only in England, where, fol-
lowing the conclusions of the Rose (2006) review, state-
funded schools have a statutory duty to provide
systematic phonics instruction when children first start
school (which normally occurs in England in the Sep-
tember following their fourth birthday). Schools’ com-
pliance with this duty is measured via a phonics
screening check given to all children at the end of the
second year of reading instruction, when children are
5 or 6 years old. This check requires children to read
20 words and 20 nonwords aloud; the nonwords are
critical to assess pure spelling-to-sound knowledge,
without any impact of memory for individual words.
The recommendations have also informed legislation
in the United States, including the No Child Left Behind
Act of 2001 (2002) and the Every Student Succeeds Act
(2015–2016), and systematic phonics instruction is
included in the Common Core State Standards Initiative.
However, implementation and accountability for reading
performance in the United States rests with individual
states, and not all states have adopted the Common Core
(for adopters, see This
variation in reading instruction may contribute to the
wide differences in reading achievement across U.S.
states (U.S. Department of Education, 2015). The Aus-
tralian government has recently proposed a federal
screening program to test children’s phonic knowledge;
this is a matter of significant current debate and discus-
sion (e.g., Buckingham, 2016).
Although the meta-analyses described above provide
clear evidence for the effectiveness of systematic
Reading Acquisition 13
phonics instruction, the introduction of a statutory duty
to provide high-quality systematic phonics instruction
in England provides the opportunity to consider its
impacts on a national scale. The evidence from perfor-
mance on the phonics screening check suggests fairly
dramatic year-over-year improvements in children’s
phonic knowledge since 2012, when the test was intro-
duced: 58% passed in 2012, 69% in 2013, 74% in 2014,
77% in 2015, 81% in 2016, and 81% in 2017 (U.K.
Department for Education, 2017). These results suggest
that the policy has increased schools’ compliance in
delivering systematic phonics instruction and has per-
haps improved the quality of its delivery. However, one
important question is whether these gains have influ-
enced literacy achievement more broadly. Inspection of
performance on national standardized tests administered
at the age of 7 show small but significant increases in
reading comprehension associated with the national
improvements observed in phonics knowledge, although
it is not possible to conclude that this association
reflects a causal relationship (Walker, Sainsbury, Worth,
Bamforth, & Betts, 2015).
One approach to determining whether a causal rela-
tionship exists between phonics instruction and broader
literacy performance was described in a report by the
U.K. Centre for Economic Performance (Machin,
McNally, & Viarengo, 2016). Specifically, because the
phonics policy in England was piloted and then imple-
mented across different school districts at different
times, it is possible to assess the impact of this change
on children’s performance on national tests of reading
comprehension administered at ages 5, 7, and 11 rela-
tive to children in “untreated” districts. Using this
approach, Machin etal. (2016) documented strong
impacts of the policy change on reading comprehen-
sion up to the age of 7. There was also a longer-term
benefit at age 11, years after the original intervention
occurred, for those children who had a high probability
of starting school as struggling readers because they
were nonnative speakers of English or were economi-
cally disadvantaged. These results are consistent with
the view that explicit teaching of phonics assists all
children to access text material relatively early in read-
ing instruction and that this explicit instruction is par-
ticularly vital for some children (e.g., C. E. Snow & Juel,
1.4.2. Outstanding questions on phonics instruction.
It will be clear from our review so far that there is strong
scientific consensus on the effectiveness of systematic
phonics instruction during the initial periods of reading
instruction. Despite this, widespread misunderstanding in
the public domain prevails: Some key myths about pho-
nics instruction are addressed in Box 2. In addition, many
outstanding questions remain regarding exactly how
phonics instruction is best implemented in the classroom,
given that there are, of course, multiple ways in which
this could be done. Here, we review here some of the
key questions, all of which in our view require further
research to be resolved (for further discussion, see Stuart
& Stainthorp, 2015). Methods of phonics instruction. One ongoing
debate regarding methods of phonics instruction (par-
ticularly within the United Kingdom) concerns whether
a “synthetic” approach is preferable to an “analytic” one.
Synthetic phonics programs teach grapheme-phoneme
correspondences individually and in a specified sequence,
and children are taught early to blend (synthesize, hence
the term synthetic) individual phonemes together to make
words. In contrast, analytic phonics programs begin with
whole words, and grapheme-phoneme correspondences
are taught by breaking those words down into their com-
ponent parts. On the face of it, synthetic phonics would
seem to have some clear advantages: By introducing
grapheme-phoneme correspondences individually, it is
possible to control the learning environment more effec-
tively and to ensure that each correspondence is taught
explicitly and in an optimal sequence. Empirical support
for synthetic phonics has also come from a longitudinal
study conducted in Clackmannanshire County, Scotland;
Johnston and Watson (2004, 2005) reported strong and
long-lasting gains in reading accuracy and spelling from
a 16-week synthetic phonics intervention relative to two
analytic phonics interventions. However, in our view, the
evidence is not yet sufficient to conclude that a synthetic
phonics approach should be preferred over an analytic
one: Neither the Torgerson et al. (2006) meta-analysis
nor that of the National Reading Panel (Ehri etal., 2001)
found evidence for a difference in effect size across the
two methods. Both of these reviews concluded that the
key ingredient of a successful phonics program is that it
is systematic. Beyond this, further research is required
to determine which implementations are most effective.
A second outstanding question concerns whether
phonics instruction should be limited to individual
graphemes and phonemes, and their most common
mappings, or should be extended beyond this. As noted
earlier, many spelling-sound regularities in English are
not captured by simple grapheme-phoneme rules and
require consideration of other letters and phonemes in
the word (e.g., the vowel sound associated with “oo”
often changes when followed by “d,” as in hood, good,
and stood; Kessler & Treiman, 2001). Thus, there may
be a case for extending phonics programs to include
instruction on these context-sensitive rules once chil-
dren have mastered the basic mappings (Vousden, Ellef-
son, Solity, & Chater, 2010). However, it is also possible
that a limited set of grapheme-phoneme correspon-
dences taught early will put children on a
14 Castles et al.
path to independent reading and that more complex
context-sensitive mappings will then be acquired
through text experience (e.g., Stuart, Masterson, Dixon,
& Quinlan, 1999; Ziegler, Perry, & Zorzi, 2014). A small
body of research compares phonics programs that teach
single grapheme-phoneme mappings (e.g., “oo” is pro-
nounced as in spook) with programs that teach multiple
mappings (e.g., “oo” can be pronounced as in spook or
hood; see Shapiro & Solity, 2016). However, we believe
that a systematic investigation of the optimal number
and complexity of phonics rules to be taught is needed. Teaching “sight words” along with phonics. Mas-
tery of alphabetic decoding skills allows children to translate
the spellings of most words they encounter into sound. How-
ever, as we have discussed, most alphabetic writing systems
have at least some degree of spelling-to-sound irregularity,
and English includes a number of high frequency words that
Box 2. Some Myths About Phonics Instruction
Myth Evidence References
Phonics teaches
children to read
The aim of phonics instruction is to equip children with the skills to
sound out independently. Nonwords are primarily used not
for teaching but for assessment, to index children’s phonics skills
independently of their word knowledge. An analogy would be
measuring heart rate to assess cardiovascular fitness: We don’t
train the heart to beat more slowly, but we assess this function to
measure how effective a fitness training program has been.
Castles et al.
Phonics interferes
with reading com-
At a basic level, phonics supports comprehension by allowing the
child to link an unfamiliar printed word with a familiar word in oral
vocabulary. Phonics also supports the development of fluent word
reading ability, which in turn frees up the child’s mental resources
to focus on the meaning of a text. Ehri et al.’s (2001) meta-analysis
found that children taught by a systematic phonics method made
gains in text comprehension as well as in word reading and
Perfetti &
Hart (2002)
Ehri et al.
3. English is too “irreg-
ular” for phonics to
be of value
It is true that the English writing system is complex, and many
words violate typical letter-sound mappings. However, learning
phonics will still take a child a long way: More than 80% of mono-
syllabic words are completely regular and, for those that are not, a
“partial decoding” will often bring a child close to the correct pro-
nunciation, which can then be refined using oral vocabulary
Share (1995)
Phonics is boring for
children and turns
them off reading
Phonics instruction is often portrayed as robotic and mechanical,
but this is at odds with the array of engaging and enjoyable struc-
tured phonics programs currently available. And, through its posi-
tive effects on reading attainment, phonics instruction is associated
with greater motivation to read, more extensive reading for pleas-
ure, and higher academic self-esteem.
Kirsch et al.
Anderson et
al. (1988)
McArthur &
Reading Acquisition 15
are highly unusual (e.g., eye, friend). Many teachers address
this problem by teaching these kinds of words as “sight
words” or “tricky words” together with phonics instruction.
Sight words are introduced in a range of ways, and this var-
ies across classrooms. Teachers may use flash cards with
single words printed on them for children to name, activity
sheets involving the words, or weekly word lists for children
to take home. In all cases, the intention is that, through rep-
etition and feedback, children learn to recognize and name
these tricky words fluently. However, this practice is con-
troversial: Many phonics advocates argue that it is not only
ineffective but also dangerous, causing children to become
confused about letter-sound mappings and setting them up
with bad reading habits that interfere with their ongoing
phonics instruction (e.g., A. Clarke, 2012; Potter, 2012).
In our view, this concern is unwarranted, and the
judicious selection of a small number of sight words
for children to study in detail has its place in the class-
room alongside phonics. As we have discussed, teach-
ing phonics is crucial because it gives children the skills
to translate orthography into phonology and thereby
to access knowledge about meaning. However, when
this is difficult because of spelling-to-sound complexi-
ties, there would seem to be a case for teaching chil-
dren the pronunciations of a small number of such
words directly, particularly those that they are likely to
see very frequently in the texts they are reading (such
as the, come, have, and said). In effect, this ensures that
children can relate the visual symbols of writing to
spoken language for as many words as possible and as
early in their schooling as possible. Solity and Vousden
(2009) demonstrated that the combination of knowl-
edge of the 64 most common letter-sound mappings of
English, together with familiarity with its 100 or so most
frequent words, allows children to read aloud 90% of
words in texts they typically encounter—putting them
very efficiently on the path to independent reading.
It would be a different story if teaching sight words
interfered with children’s acquisition of alphabetic
decoding skills, but evidence is lacking. In a large inter-
vention study, McArthur etal. (2015) found that strug-
gling readers who received mixed phonics and
sight-word instruction made just as strong gains in their
alphabetic decoding ability as those receiving phonics
instruction alone. There was also no evidence from this
study that sight-word teaching caused the children to
become confused or to “unlearn” phonics rules that they
had already acquired. Indeed, children who received an
intensive period of sight-word instruction immediately
after an intensive period of phonics instruction showed
no deterioration in their alphabetic decoding ability and,
in fact, continued to show improvements.
The McArthur etal. (2015) study was carried out with
older struggling readers, all of whom had at least some
phonics knowledge. What is known about beginning
readers? Shapiro and Solity (2016) compared the effec-
tiveness of two phonics programs being implemented in
the first (Reception) year of schooling in the United
Kingdom: Letters and Sounds (U.K. Department for Edu-
cation and Skills, 2007), which teaches multiple letter-
sound mappings and no sight words, and Early Reading
Research (Shapiro & Solity, 2008), which teaches only
the most consistent letter-sound mappings plus high-
frequency sight words. Follow-up of reading and phono-
logical awareness outcomes at the end of the second and
third years of schooling revealed that the two programs
were equally effective, indicating that the presence of
sight words did not interfere with phonics learning. In
fact, there was a tendency for children with low initial
phonological awareness scores to do better with the Early
Reading Research program, which suggests that being
exposed to multiple alternative sound mappings for the
same graphemes, rather than sight words, may have been
a source of confusion for these children.
In summary, teaching phonics provides children with
the principal means of getting from the printed form of
a word to its spoken form but, given the depth of the
English orthography, teaching some sight words can
assist here as well. That said, many questions remain
about the teaching of sight words. Most importantly,
what method of teaching sight words is most effective?
Successful methods are likely to involve engaging chil-
dren in detailed study of the letters in the word and
their sequence—with a focus on the difficult parts—and
linking this with the word’s pronunciation, but this has
not been explored systematically. Moreover, what is the
minimum level of alphabetic skill that beginning read-
ers need in order for sight-word teaching to be effec-
tive? Sight-word learning is likely to be most successful
when children have basic letter knowledge (Levin &
Ehri, 2009); however, this does not mean that the intro-
duction of sight words should be delayed until children
have an extensive knowledge of many specific grapheme-
phoneme correspondences. Finally, what is the optimal
number of sight words to teach at different points in
reading acquisition and with what intensity? Research
is needed to answer these questions. A final important
point to note, as we discuss in detail in Section 2.4.1,
is that children learning “sight words” should not be
seen as analogous to them learning to read “by sight.
As we will see, the latter is a much more complex and
protracted developmental process. A role for “decodable” books? Decodable books
are texts written for children that consist primarily of
words that they can read correctly using the grapheme-
phoneme correspondences that they have learned (with
the exception of a few unavoidable irregular words such
16 Castles et al.
as the and said). These kinds of books provide children
with an opportunity to practice what they have been
taught explicitly in the classroom and to allow them to
experience success in reading independently very early
in reading instruction, albeit with a rather restricted word
set. These books also allow teachers to effectively struc-
ture and sequence children’s exposure to grapheme-
phoneme correspondences in text. Evidence suggests
that phonics teaching is more effective when children
are given immediate opportunities to apply what they
have learned to their reading (Hatcher, Hulme, & Ellis,
1994); so, for these reasons, we believe that there is a
good argument for using decodable readers in the very
early stages of reading instruction.
Beyond the initial stages of reading, however, the
case for decodable books weakens. First, evidence indi-
cates that once children have learned a core set of
grapheme-phoneme correspondences, they get no
more opportunity to practice these in decodable books
than they do in other books they might be reading (i.e.,
books not specifically written with decodability in
mind). Solity and Vousden (2009) analyzed the vocabu-
lary within three sets of books in the United Kingdom:
two structured reading schemes consisting of specially
written books for school children containing high-
frequency and phonically regular words and one set of
story books found in typical Year 1 and 2 classrooms
(i.e., children ages 5–7). They found that the percentage
of monosyllabic words within the books that would be
decodable by children knowing 64 grapheme-phoneme
correspondences was equal across the three sets
(approximately 75%). A second issue with decodable
books is that they are likely to be somewhat restricted
in word choice and so may tend to be inferior to real
books in (a) maintaining children’s interest and motiva-
tion to read and (b) in achieving the broader goals of
building children’s vocabularies and knowledge. Solity
and Vousden (2009) give the example of the words used
in the book The Three Billy Goats Gruff (Sharratt &
Tucker, 2004) with the analogous decodable reader
Billy the Kid (Miskin, 2008). The only word used to
describe the characters speaking to each other in Billy
the Kid is said, which is repeated 11 times. In contrast,
in the book The Three Billy Goats Gruff, the word said
is also used 11 times, but eight other words and phrases
are used to describe how the different characters speak
(e.g., shouted out, grunted, replied, roared, snapped,
and spluttered). As we discuss later in this review, expo-
sure to complex words and nuanced meanings is impor-
tant. Therefore, in our view, once children move beyond
the very early stages of reading, the benefits of decod-
able readers are likely to be outweighed by their limita-
tions. More research is needed to determine when this
tipping point occurs.
2. Becoming a Skilled Word Reader
We have argued that cracking the alphabetic code is
essential for learning to read and that assisting children
to do so is a nonnegotiable part of teaching them to
read. It is this initial knowledge of spelling-sound rela-
tionships that allows children to access the meanings
of printed words and thus gain the text experience that
is essential for the acquisition of higher-level reading
skills. However, the acquisition of phonic knowledge
is by no means all there is to learning to read, even at
the single-word level. In our view, one of the impedi-
ments to the translation of research into teaching prac-
tice and to the resolution of the reading wars has been
a relative lack of attention to aspects of reading acquisi-
tion that go beyond alphabetic decoding, which give
rise to arguments that “reading is more than phonics.
This is a statement of the obvious to any reading sci-
entist. Yet such statements are often used in public
debate to undermine the case for the use of phonics in
the initial stages of learning to read. In this section, we
discuss how children move beyond alphabetic decod-
ing to develop the ability to recognize words accurately
and with ease. We begin with a review of what is
known about the word-reading system and how it oper-
ates in skilled readers, making the case for processes
beyond alphabetic decoding.
2.1. Word-reading processes
in skilled reading
We have discussed how the process of alphabetic
decoding is essential for learning to read, but it is
important to note that even skilled adult readers con-
tinue to use alphabetic decoding and phonological
processes as a matter of routine. The most obvious
evidence of this is that skilled readers can generalize:
They can read not only words with which they are
highly familiar but also new words that they have never
seen before (or indeed nonwords, such as slint and
vib). There is also substantial evidence that alphabetic
decoding processes affect skilled readers’ word recogni-
tion and comprehension (Rayner, Schotter, Masson,
Potter, & Treiman, 2014). One powerful demonstration
of the impact of phonological decoding on skilled word
recognition is the pseudohomophone effect. The letter
strings feal and feep are both nonwords, but skilled
readers find it more difficult to judge the former as not
being a real word (see, e.g., Ziegler, Jacobs, & Klüppel,
2001). Both of these letter strings are different from the
word feel by just one letter, so the only explanation for
this result is that readers are translating the letter strings
to sound. Likewise, participants who were asked to
judge whether a printed word was a member of a
Reading Acquisition 17
particular semantic category made more false-positive
errors in response to homophones of correct responses
(e.g., responding that the word rows is a type of flower)
than in response to similarly spelled control words
(e.g., robs). This result indicates that the participants
had translated rows into a phonological code, for only
by doing so could they mistake this word for a type of
flower. It is also important to note that the translation
into a phonological code actually hurt performance in
this task, but participants could not “turn off” that pro-
cess. Further research suggests that this translation from
spelling to sound occurs very rapidly in skilled readers
and indeed is apparent even in cases in which partici-
pants are not aware that a stimulus has been presented
(for reviews, see Rastle & Brysbaert, 2006; Leinenger,
Thus, skilled readers of alphabetic writing systems
continue to draw on the systematic relations between
letters and sounds when they read and understand
words. These skills alone, however, are not sufficient
for fluent word reading. A simple example serves to
illustrate this point: Readers of this article will be able
to reliably distinguish the meanings of the two printed
words sail and sale, even if they are presented in isola-
tion with no contextual support. Yet readers cannot
achieve this via alphabetic decoding alone because it
would produce exactly the same pronunciation for each
word. They can also immediately recognize and under-
stand irregular words such as have, come, and eye,
despite the fact that they cannot reach the meanings of
these words via alphabetic decoding alone (and, in the
case of come, despite the fact that alphabetic decoding
actually leads to an incorrect meaning, that of a hair
implement). Such words would place heavy demands
on a reading system reliant purely on alphabetic decod-
ing, requiring extra time and effort and perhaps the
harnessing of additional top-down support from oral
vocabulary or sentence context. But there is no evi-
dence that this is so for skilled word readers: They can
recognize and identify highly familiar irregular words
just as efficiently as they can regular ones (Seidenberg,
Waters, Barnes, & Tanenhaus, 1984).
These examples are taken from English, which is
arguably an “outlier” orthography because of the high
degree of inconsistency of its spelling-to-sound map-
pings (Share, 2008; see Section 1.1). Maybe expert read-
ers of shallow orthographies continue to read words
primarily via alphabetic decoding? This does not appear
to be the case. Alphabetic decoding is a process of
mapping graphemes onto phonemes, and it has been
argued that this is carried out in a serial, left-to-right
manner (Rastle & Coltheart, 1999, 2006; Rastle, Havelka,
Wydell, Coltheart, & Besner, 2009). Therefore, if this
process is being relied on, longer letter strings will be
slower to read than shorter ones. For nonwords, which
are unfamiliar to all readers and so must be read via
alphabetic decoding, this is indeed the case: Long non-
words produce much longer reading latencies than
short nonwords (Weekes, 1997). However, when skilled
readers are reading familiar words, length has little or
no effect on their reading latencies, and this is the case
in English orthography (Weekes, 1997) and in a range
of other orthographies, including Spanish, French, and
German (Acha & Perea, 2008; Juphard, Carbonnel, &
Valdois, 2004; Ziegler, Perry, Jacobs, & Braun, 2001).
The fact that word reading involves more than just
alphabetic decoding is reflected in all major theories
of skilled reading. Theories of skilled reading are
among the most elaborate and well-specified in the
field of psychological science. Indeed, several have
been expressed as computer programs known as com-
putational models that describe the precise cognitive
operations involved in visual word recognition and
reading aloud (e.g., Coltheart etal., 2001; Harm &
Seidenberg, 2004; Perry, Ziegler, & Zorzi, 2007, 2010;
Plaut, Mcclelland, Seidenberg, & Patterson, 1996). Box
3 provides an introduction to these computational mod-
els, although our review is agnostic as to which pro-
vides the most successful account of skilled reading
performance. The important point is that all of the
models converge in that they represent two key cogni-
tive processes in word reading: one that involves the
translation of a word’s spelling into its sound and then
to meaning, and one that involves gaining access to
meaning directly from the spelling, without the require-
ment to do so via phonology.
That these two broad mechanisms should emerge in
readers of alphabetic orthographies makes perfect
sense: Together, they allow optimal processing of words
across the full spectrum from being new and unfamiliar
to a reader, where alphabetic decoding is critical, to
highly familiar, where direct access to meaning is more
efficient (Share, 2008). Regardless of the particular
orthography being read, it appears that a direct path-
way from print to meaning is preferred for familiar
words, most probably because the alphabetic decoding
mechanism is slow, attention demanding (Besner,
Reynolds, & O’Malley, 2009; Paap & Noel, 1991), and
therefore not optimal for supporting the fast and effi-
cient word reading that characterizes skilled readers.
This dual-pathway architecture for deriving meaning
from printed words is also apparent in the neural imple-
mentation of the reading system, as described in Box 4.
In summary, cognitive models converge in repre-
senting the fluent reading of familiar words as proceed-
ing directly from print to meaning, without the
requirement for alphabetic decoding. Knowing this is
important because it maps out for us what the child
18 Castles et al.
Box 3. Computational Models of Reading
Computational models of reading are computer programs that describe in detail the cognitive operations
proposed to underpin particular reading tasks, such as recognizing a word and reading it aloud. By
writing a theory of reading as a computer program, one can make sure that the theory is complete and
can be evaluated rigorously against human data. Development and testing of computational models has
had a huge impact on our understanding of skilled reading and has informed theories of related reading
phenomena, including reading acquisition, dyslexia and its remediation, and the genetic and neural ba-
ses of reading.
Three main computational models have been proposed: the DRC model (Coltheart, Rastle, Perry, Lang-
don, & Ziegler, 2001); the Triangle model (Harm & Seidenberg, 2004; Plaut, McClelland, Seidenberg, &
Patterson, 1996); and the CDP+ model (Perry, Ziegler, & Zorzi, 2007, 2010). These models accept a
printed letter string as input, and transform it to a pronunciation, or to the activation of stored knowledge
of words. Researchers study the accuracy and speed with which these transformations are accom-
plished. The models are used to simulate typical reading, but can also be “lesioned” to simulate types
of dyslexia acquired through brain injury or atypical development.
The DRC model is a static model of the skilled,
adult reading system. The Triangle model simu-
lates the process of learning to read as well as the
adult system, and the CDP+ model is a hybrid that
combines features of the other two models. All
three models propose that reading involves stored
knowledge of learned words, as well as knowledge
of the relationship between spelling and sound.
Using this latter type of knowledge allows the mod-
els to read both words and nonwords, such as
or vib.
Triangle Model
Phoneme Nodes
O1 O2 O3 V1 C1 C2 C3 C4
Grapheme Nodes
O1 O2 O3 V1 C1 C2 C3 C4
Letter Nodes
L1 L2 L3 L4 L5 L6 L7 L8
Feature Detectors
F1 F2 F3 F4 F5 F6 F7 F8
Rule System
DRC Model
Reading Acquisition 19
needs to learn to become a skilled word reader and
what the ultimate goal of educational instruction
should be. It would be a mistake, however, to assume
that knowledge of how the skilled system works is all
that is needed to inform instruction. On the contrary,
the assumption that the endpoint of learning to read
determines how it should be taught was precisely the
error made by theorists such as Goodman (1967).
These theorists observed rapid construction of mean-
ing for texts in skilled adult readers and concluded that
instruction should focus on these skills. But such a
conclusion is analogous to observing skilled concert
pianists and concluding that piano instruction should
involve putting a child in front of a Tchaikovsky score.
The missing piece of the puzzle here is how these
processes develop in children, so we turn now to
reviewing the science on this question.
2.2. The development of fluent
word-reading skills
As children progress toward becoming skilled readers,
their heavy reliance on alphabetic decoding gradually
decreases (Doctor & Coltheart, 1980; Harm & Seidenberg,
2004; Zoccolotti etal., 2005). That is, children make the
transition from being “novices,” reading words primarily
via alphabetic decoding, to “experts,” recognizing familiar
written words rapidly and automatically, mapping their
spellings directly to their meanings without recourse to
decoding, a process we have referred to as orthographic
learning (Castles & Nation, 2006; Nation & Castles, 2017).
It is important to note that phonological processes still
exert an influence on reading at this point, but they do
so in a less overt way. For example, from as young as 7
years old, children reading sentences process nonwords
that sound like words (e.g., gerl) more efficiently than
control nonwords (e.g., garl). This shows that even in
children’s silent reading, phonological processing is at
play (e.g., Blythe, Pagán, & Dodd, 2015; Jared, Ashby,
Agauas, & Levy, 2016).
Orthographic learning is an umbrella term that encom-
passes both the acquisition of the word-specific knowl-
edge required to access a particular word’s meaning from
print and also the accumulation of more general knowl-
edge about orthographic regularities within the writing
system (for example, in English, double letters such as
“ll” tend to appear at the ends of words but not the
beginnings; Cassar & Treiman, 1997; Pacton, Perruchet,
Fayol, & Cleeremans, 2001). In the sections below, we
explore what is known about this important, but less
well understood, aspect of reading acquisition.
2.2.1. Self-teaching during independent reading. The
most influential theory of the transition to skilled word
reading has been Share’s self-teaching hypothesis, which
sets out a theoretical framework (Jorm & Share, 1983;
Share, 1995) and provides an experimental paradigm for
exploring it (Share, 1999, 2004). The self-teaching hypoth-
esis has alphabetic decoding at its core, the so-called sine
qua non of reading acquisition. As we have explained,
alphabetic decoding provides children with a means of
accessing the spoken form of a word from its written
form. But Share further proposes that, by requiring the
child to engage in the effortful process of translating print
to sound and therefore to focus on the letters in the word
and their sequence, the act of decoding also provides an
opportunity to acquire orthographic knowledge. This
knowledge is then available on future encounters with
the word, lessening the reliance on alphabetic decoding.
Thus, through the combination of alphabetic decoding
and repeated exposure, children are able to self-teach
through their independent reading.
Share provided evidence for his hypothesis in an
innovative series of experiments with children learning
to read in Hebrew (Share, 1999, 2004). In his 1999
study, 8-year-old children independently read short sto-
ries aloud, each of which contained novel words (an
English example is the item Yait, and children might
read a story about how Yait is the coldest city in the
world). Several days later, the children demonstrated
substantial learning about the orthography of these new
words: They were well above chance at selecting the
correct spelling of the word (Yait) from alternative
spellings that consisted of a homophone (e.g., Yate)
and two visually similar items (e.g., Yiat, Yete). The
inclusion of the homophone is important here because,
as with our sale-sail example above, the children would
not have been able to reliably distinguish the correct
word from its homophone by relying on phonological
decoding alone. The children also named the novel
items faster than the homophones and, in a spelling
task, were more likely to use the spelling of the word
to which they had been exposed than that of the homo-
phone. Thus, these results provide clear evidence of
orthographic learning beyond alphabetic decoding: The
children had learned something specific about the
orthographic form of the words that they experienced
during their independent reading. There have now been
several similar demonstrations in deeper alphabetic
orthographies, such as English (Cunningham, Perry,
Stanovich, & Share, 2002; Kyte & Johnson, 2006; Wang,
Castles, & Nickels, 2012; Wang, Castles, Nickels, &
Nation, 2011), providing evidence of the generality of
the self-teaching mechanism.
The self-teaching hypothesis provides a powerful
paradigm for representing how children move from
novice to expert. More generally, it has been influential
in focusing attention squarely on learning and on the
20 Castles et al.
importance of understanding how learning takes place
if reading development is to be understood. Key to this
is the insight that the process of acquiring direct map-
pings between printed words and their meanings pro-
ceeds in an item-based fashion: At any particular point
in time, a child may be reading some words slowly and
with great effort while recognizing and understanding
other words rapidly and efficiently, with less reliance
on alphabetic decoding (Castles & Nation, 2006; Share,
1995). Indeed, this is even true for adult skilled readers,
who must apply their orthographic learning processes
to the numerous novel printed words they will encoun-
ter throughout their lifetimes (think Google, blog, and
selfie). An item-based learning mechanism is now widely
reflected in computational models of reading acquisition
(e.g., Grainger, Lété, Bertand, Dufau, & Ziegler, 2012;
Harm & Seidenberg, 2004; Pritchard, Coltheart, Marinus,
& Castles, 2018; Ziegler etal., 2014).
Box 4. The Neural Bases of Reading
The past 20 years have seen increasing interest in how the brain supports skilled reading and its devel-
opment. A recent meta-analysis bringing together neuroimaging studies of reading in alphabetic writing
systems has yielded strong support for the proposal that there are two pathways to computing meaning
from print (Taylor, Rastle, & Davis, 2013). The neural model of reading resulting from this meta-analysis
is presented below.
A dorsal pathway underpins
phonologically mediated reading, and a ventral pathway
underpins direct access to meaning from print. This model is also supported by neuropsychological data.
For example, patients with damage to areas of the dorsal pathway have difficulty reading nonwords
(e.g., Woollams & Patterson, 2012), whereas patients with damage to areas of the ventral pathway have
particular difficulties reading words with atypical spelling-sound mappings (e.g., Woollams, Ralph, Plaut,
& Patterson, 2007).
Regions within the left-hemisphere ventral
pathway dubbed the “visual word form area
have been of particular interest to reading re-
searchers (for review, see Dehaene & Cohen,
2011). This region appears to be tuned to
written language; for example, it responds
more strongly to words and nonwords than to
consonant strings (Cohen et al., 2002). Fur-
ther work characterizing this region has re-
vealed a posterior-to-anterior gradient, with
increasing sensitivity to higher-level proper-
ties of words (e.g., letters, bigrams, quadri-
grams; Vinckier et al., 2007).
Neural Pathways of Skilled Reading
(adapted from Rastle, 2018)
Much less research has considered how the brain changes through reading development. Nevertheless,
a recent meta-analysis of neuroimaging studies of reading in children revealed a network of dorsal- and
ventral-pathway brain regions similar to that observed in adults (Martin, Schurz, Kronbichler, & Richlan,
2015). One interesting proposal that is consistent with the characterization of reading acquisition that
we have put forward is that reliance gradually shifts with increasing reading skill from the dorsal to the
ventral pathway (Pugh et al., 2000; Shaywitz et al., 2002). This is consistent with longitudinal data
suggesting that areas of the ventral pathway continue to increase in sensitivity to printed words into
adolescence (Ben-Shachar, Dougherty, Deutsch, & Wandell, 2011) and that this increase is associated
with speeded word reading performance, but not nonword reading performance or phonological pro-
cessing skill.
Reading Acquisition 21
However, there are some important aspects of the
transition from novice to expert word reading on which
the self-teaching hypothesis is largely silent. As dis-
cussed, central to the hypothesis is that exposure is key
to this transition: Orthographic learning occurs as a
function of alphabetic decoding together with repeated
exposure to novel words in print. But what, precisely,
does this exposure achieve? What changes in children’s
orthographic knowledge as a result of their experiences
with printed words, and how does this lead to the
changes in the nature and the efficiency of word rec-
ognition that are observed? And are all types of expo-
sure equally valuable? To answer these questions, we
need to move beyond the self-teaching hypothesis to
more detailed theories of word-reading development.
2.2.2. Building expertise through experience with
print. In his influential theory, Perfetti (1992, 2007;
Perfetti & Hart, 2002) provides one answer to the ques-
tion of what changes as a result of exposure to printed
words: lexical quality. Perfetti defines lexical quality as
the extent to which a stored mental representation of a
word specifies its form and meaning in a way that is both
precise and flexible. Precision of the representation—
knowledge of the exact spelling—is important because it
allows a child to distinguish a written word from similar-
looking words, permitting direct access to its meaning
(e.g., to differentiate face from fact, fame, and lace). Flex-
ibility of the representation is important because it allows
a child to adapt dynamically to different print-meaning
combinations (such as reading about eating jam versus
reading about getting in a jam; see Box 1). Once again,
lexical quality applies at an item level: For any given
reader, some frequently encountered words in their lexi-
con will be high in quality, whereas other less well-known
words will be low in quality. But note that as children
build their experience with print, the average quality of
the words in their lexicon steadily increases.
Why is lexical quality so important for the transition
from novice to expert reader? According to Perfetti and
others (e.g., Ehri, 2005b), the answer to this question
is that, as lexical quality builds, cognitive resources are
freed up for comprehension. As we will see later in our
review (Section 3.1), understanding text is a complex
task that places heavy demands on attention, memory,
and high-level language processes. When lexical quality
is high, a reader’s cognitive resources can be largely
directed toward this challenging task because individ-
ual words are recognized rapidly, automatically, and
with minimal conscious effort. In contrast, when lexical
quality is low, some of the reader’s limited cognitive
resources must be directed to the more basic task of
word recognition, and comprehension is compromised
as a result. Thus, as with so many aspects of learning,
“low-level” processes underpin, and are an essential
foundation for, the high-level ones: Through repeated
exposure to words, a child develops specialized and
efficient basic word-recognition mechanisms that are
optimized for reading for meaning.
Given the importance of these automatic and effi-
cient word-recognition processes for skilled reading, a
key question to ask is what promotes their emergence.
Is it driven simply by the total number of exposures a
child has had to a given word? Certainly, there is a
positive association between indices of children’s over-
all exposure to print and their reading ability (Mol &
Bus, 2011; Stanovich & West, 1989). However, the
answer appears to be more nuanced than this and, once
again, to draw on considerations of the nature of the
writing system. Consider once again the example of the
word face. Successful discrimination of this word from
the many other words in English that differ from it by
only one letter (e.g., fact, lace, fame) requires the
reader to develop a very precise recognition mecha-
nism, one that attends to all of the letters in the word
and their order. Otherwise, identification accuracy and
access to meaning will be compromised. However, now
consider the word bird. Few other four-letter words in
English differ from this word by only one letter, so the
discrimination challenge is substantially easier. A lexical
recognition mechanism for bird that allows it to be
efficiently and reliably identified can afford to be con-
siderably less precise than one for face. Thus, overall
print exposure may interact with the nature of the
orthography to shape the development of a child’s
word-recognition system—a mechanism we refer to as
lexical tuning (Castles, Davis, Cavalot, & Forster, 2007;
Castles, Davis, & Letcher, 1999).
There is evidence for a lexical-tuning process playing
out across reading development. For example, Castles
etal. (2007) used a technique known as masked prim-
ing to probe how the precision of children’s automatic
word-recognition mechanisms changes between Year 3
and Year 5 (approximately between ages 8 and 10 in
Australia). Masked priming involves the presentation of
a prime stimulus very briefly before a target word to
which the participant must respond in some way.
Although the prime is presented so briefly that partici-
pants can rarely report seeing it, it nevertheless can
affect performance on the target; for example, the
prime word face, presented in lowercase, facilitates
responses to the identical uppercase target word, FACE
(Forster & Davis, 1984). Thus, manipulating the prime
and its similarity to the target probes the mechanisms
that underpin automatic word recognition. They found
that, in Year 3, these mechanisms were quite “loosely”
tuned. The children’s responses to a word such as FACE
were facilitated by a one-letter-different prime (e.g.,
22 Castles et al.
dace), indicating that the prime was sufficiently similar
to the target to activate its recognition mechanism.
However, once the children had reached Year 5, this
was no longer the case. The recognition mechanism
was more finely tuned for those same words, and only
a prime that was an exact match (i.e., face itself) was
sufficient to facilitate performance.
Note that what is likely to be critical in the tuning
of lexical representations is not age per se but reading
experience (which is naturally correlated with age). In
line with this, Andrews and colleagues (Andrews &
Hersch, 2010; Andrews & Lo, 2012)—also using masked
priming techniques—have reported variation in markers
of lexical tuning in skilled readers, even among univer-
sity students. Those who show evidence for high lexical
quality, as indexed by their spelling skills, appear to
show more precise tuning than those with less well-
specified orthographic representations. This variation
is associated with performance on measures of reading,
spelling, and vocabulary in these adult participants.
These data suggest that even in adults, there are sub-
stantial individual differences in the precision of the
orthographic representations necessary for rapid word
recognition and comprehension, reflecting variation in
a person’s literacy experiences over time. These influ-
ences are seen not just in isolated word-reading tasks
but also in silent text reading, as revealed by eye-
movement studies (e.g., Veldre & Andrews, 2015, 2016).
Thus far, we have discussed how the orthographic
representations used in skilled reading are sharpened
through an individual’s literacy experiences over time.
Because individuals do not experience all words in the
same manner, it follows that there may be item-level
variation in the nature of orthographic representations.
One variable that has been particularly well studied in
the skilled-reading literature is word frequency. It has
long been thought that words that occur frequently
have particularly robust orthographic representations
and can thus be processed more rapidly (e.g., Forster
& Chambers, 1973; for review, see Brysbaert, Mandera,
& Keuleers, 2018). However, Zevin and Seidenberg
(2002) make the point that word frequency is not just
a variable relevant to skilled reading but also reflects
the accumulation of instances in lexical memory over
time. On that basis, they argue that the best reflection
of experience in skilled reading is not actually fre-
quency (i.e., how many times a word occurs in a cor-
pus) but cumulative frequency (i.e., number of instances
of experiencing a word through the whole of reading
The number of times that someone encounters a
particular word throughout a lifetime is the most basic
characterization of lexical experience. However, some
researchers have argued that lexical experience is more
nuanced than a simple accumulation of instances; some
kinds of instances are more important than others in
shaping orthographic representations. One account
posits that the age at which people experience particu-
lar words is important, such that experiences early in
reading acquisition have greater impact on the develop-
ment of orthographic representations than those late
in reading acquisition (Morrison & Ellis, 1995). This
age-of-acquisition effect is not yet well understood, but
computational work suggests that it may reflect a fun-
damental property of systems that learn incrementally
over time (Monaghan & Ellis, 2010). The lexical legacy
hypothesis developed by Nation (2017) provides another
account of the accumulation of experience, positing
that the linguistic nature of people’s experiences with
particular words is also important (see also Baayen,
2010). For example, words that people experience in a
range of different semantic and syntactic contexts might
yield stronger orthographic representations than words
that are repeated in the same contexts. The premise of
this theory, demonstrated through behavioral and com-
putational studies simulating the learning process, is
that change is important for supporting learning (e.g.,
Jones, Dye, & Johns, 2017).
There is not yet consensus on which (if any) of these
accounts provides an accurate characterization of the
accumulation of lexical experience. Indeed, cumulative
frequency (Zevin & Seidenberg, 2002), age of acquisi-
tion (Ghyselinck, Lewis, & Brysbaert, 2004; Juhasz &
Rayner, 2006), and semantic and contextual diversity
(Adelman, Brown, & Quesada, 2006; Jones, Johns, &
Recchia, 2012; Plummer, Perea, & Rayner, 2013) have
all been shown to affect skilled performance when
reading words in isolation and in sentences. In addition,
semantic properties of words have been demonstrated
to influence skilled reading behavior: Words that have
multiple meanings, a high degree of imageability (i.e.,
the degree to which a word can be visualized), or rich
semantic features also enjoy an advantage in word rec-
ognition (Pexman, 2012; Taylor, Duff, Woollams,
Monaghan, & Ricketts, 2015). It is possible that these
effects also reflect the influence of these semantic prop-
erties on orthographic learning across development,
shaping lexical quality (Nation, 2009). Further work will
be necessary to discover how people’s experiences with
words accumulate over time to shape orthographic rep-
resentations and how this learning is ultimately reflected
in skilled reading behavior.
2.2.3. Morphology: Acquiring links between spelling
and meaning. So far, we have described the formation
of direct connections between print and meaning as pro-
ceeding in an item-based manner; children recognize
some words very rapidly and with ease and continue to
Reading Acquisition 23
rely on alphabetic decoding processes for other words.
Indeed, for the vast majority of printed words that chil-
dren are exposed to in reading materials used in the ini-
tial years of instruction, this learning must proceed item
by item because these are mostly short words contain-
ing only a single morpheme (Masterson, Stuart, Dixon, &
Lovejoy, 2010). Unlike the systematic relationships between
spelling and sound in an alphabetic language, there is no
relationship between spelling and meaning where single
morphemes are concerned. Although words that look sim-
ilar (e.g., cat, can, cut) are similar in sound, they are not
similar in meaning. This means that learning the meaning
of one word does not usually assist in learning the mean-
ing of another. Thus, the relationship between print and
meaning needs to be learned one word at a time.
Sometimes, these regularities between spelling and
meaning can lead to inconsistencies between spelling
and sound, as in the case of magical and magician (e.g.,
Treiman & Bourassa, 2000). Once readers start to gain
experience with these types of morphologically complex
words, they may learn that particular groups of letters
are associated with particular meanings. This knowledge
then allows them to interpret or produce new words that
they may not have seen before (e.g., George W. Bush’s
“I’m the decider and I decide what’s best”; Rastle &
Davis, 2008). Such generalization would be impossible
in the case of novel words with a single morpheme (e.g.,
determining the meaning of slint or vib).
Acquiring knowledge of how morphology underpins
the mapping between spelling and meaning is an
important process in the development of skilled read-
ing. Once morphological regularities between spelling
and meaning are discovered, orthographic learning
does not need to proceed one item at a time. Instead,
for those words comprising more than one morpheme,
recognizing and getting to the meaning of printed
words can be based on analysis of the constituents
(e.g., recognizing darkness through analysis of its com-
ponents {dark} + {-ness}). English is thought to be a
morphologically sparse language, but even so, around
80% of words in the English language are built from
more than one morpheme (e.g., darkness, cleanliness,
blackbird; see Baayen, Piepenbrock, & Van Rijn, 1993).
Thus, the acquisition of morphological knowledge pres-
ents a dramatic advantage in acquiring the mapping
between spelling and meaning (Rastle, 2018).
What, then, is known about how children learn map-
pings between spelling and meaning? By the time chil-
dren start school, they have rich morphological
knowledge that they use in their own language produc-
tion and comprehension (e.g., Berko, 1958; Carlisle,
1995). But when and how does this become intimately
linked with orthography? There has been a great deal
of research investigating the development of children’s
explicit knowledge of morphological relationships and
how this knowledge relates to reading ability. This
explicit knowledge is known as morphological aware-
ness. It refers to a child’s ability to reflect on and manip-
ulate the morphological structure of words (Carlisle,
1995) and is typically measured using oral tasks. For
example, a child might be asked to produce the appro-
priate word in a question such as “farm: My uncle is a
_____” (Mahony, 1994). Very young children can per-
form simple versions of such tasks (e.g., “This is a wug;
now there are two of them; these are two _____”;
Berko, 1958). Substantial research suggests that chil-
dren’s success in performing these explicit, oral tasks
is associated with success in reading aloud and reading
comprehension (e.g., Carlisle, 2000; Deacon & Kirby,
2004; Singson, Mahony, & Mann, 2000), although these
associations often become apparent only in the later
years of primary school.
Morphological knowledge also has clear impacts on
spelling in the primary school years, although there is
debate regarding the age at which these effects become
evident. In an important longitudinal study, Nunes,
Bryant, and Bindman (1997) showed that children dem-
onstrate morphological knowledge in their spellings, but
that the quality of this knowledge changes substantially
between the ages of 6 and 10. Although children adopt
morphological spelling patterns relatively early, they
apply them incorrectly to irregular verbs (e.g., keped for
kept) and even words that are not verbs (e.g., sofed for
soft). It is not until a later stage of acquisition that children
can apply this knowledge appropriately. Further, although
Treiman and Cassar (1996) found evidence that children
as young as 7 years old could use rudimentary morpho-
logical knowledge in their spelling performance, this has
not always been replicated (e.g., Larkin & Snowling, 2008;
for discussion, see Pacton & Deacon, 2008).
Although evidence suggests that children’s explicit
morphological knowledge is associated with reading
performance (e.g., Carlisle, 2000; Singson etal., 2000),
research is still needed to understand precisely how the
reading process itself is influenced by morphological
knowledge at different points in reading acquisition.
Substantial evidence indicates that children between the
ages of 7 and 11 analyze the morphological structure
of printed letter strings during word-recognition tasks,
at least to some degree. Children read aloud nonwords
with a morphological structure more rapidly than those
without one (Burani, Marcolini, & Stella, 2002), and they
read aloud morphologically complex words with a high-
frequency stem (e.g., locally) more quickly than those
with a lower-frequency stem (e.g., avidly; Deacon,
Whalen, & Kirby, 2011). Likewise, research suggests that
24 Castles et al.
children have difficulty classifying morphologically
structured letter strings such as quickify as nonwords
(relative to nonwords without morphological structure;
e.g., quickilt), a finding replicated in Italian (Burani
etal., 2002), French (Casalis, Quémart, & Duncan, 2015),
and English (Dawson, Rastle, & Ricketts, 2017).
However, research using masked priming has shown
that morphemic analysis of printed words is not fully
automated in children. For example, Beyersmann,
Castles, and Coltheart (2012) found that although
10-year-olds showed facilitation in masked priming for
morphologically related pairs of words (e.g., golden
primed recognition of GOLD), there was no priming
between pairs of words sharing pseudo-morphological
overlap (e.g., corner-CORN). This effect is routinely
seen in skilled adult readers (Rastle, Davis, & New,
2004) and reflects their ability to analyze the morpho-
logical structure of a word rapidly, arising before the
analysis of whole words (Taft, 1994; Taft & Forster,
1975). Further research, including with participants dur-
ing the period of secondary education, is needed to
determine when and how abstract morphological rep-
resentations used during word recognition are instanti-
ated and in what ways these change over the course of
reading acquisition.
2.3. Becoming a skilled word reader:
We have reviewed the evidence that expert readers can
gain access to the meanings of many words directly
from their printed forms and that reading progress is
characterized by a gradual transition from a profile of
reading words primarily via alphabetic decoding to one
of heavy reliance on this direct mechanism. Acquiring
knowledge of morphological regularities is an impor-
tant part of this transition, allowing the child to capital-
ize on systematic mappings between spelling and
meaning. The process by which this transition from
novice to expert word reader occurs is complex, and
many questions remain. However, it is clear that reading
experience matters. Exposure to print provides the
dynamic database from which children can accumulate
detailed orthographic knowledge, supported by a foun-
dation of alphabetic decoding skill.
What, then, are the implications for teaching? What
can be done in an educational setting to promote this
transition? The answers to these questions are less
straightforward than in the case of phonics and alpha-
betic decoding. In the next section, we consider some
of the misunderstandings and controversies in relation
to teaching fluent word-reading skills, and we provide
guidance based on the implications of the scientific
2.4. Implications for the classroom
2.4.1. Sight words revisited. A natural first response
to the question of how to promote fluent word-reading
skills might be to propose extensive teaching of sight
words in the manner described in Section Such a
response, however, is overly simplistic. First, the fact that
children can successfully say the name of a sight word
when they see it does not mean that they have acquired
the kind of sophisticated orthographic knowledge about
that word that supports fluent word recognition. In other
words, teaching a “sight word” does not guarantee read-
ing “by sight.” As we have discussed, word-reading exper-
tise develops over time and typically rests on a foundation
of alphabetic decoding together with broader reading
experience. Second, learning individual sight words could
only ever be a drop in the ocean in terms of children’s
orthographic learning: It is estimated that from the middle
of childhood onward, children learn approximately 3,000
new words per year (Nagy & Herman, 1984). Clearly,
teaching each of those new words as sight words would
be an insurmountable task for both teacher and student.
This does not mean, however, that teaching sight
words makes no contribution to building fluent word-
reading skills. On the contrary, it plays a part in what
we see as the deeper response to the question of how
to promote fluent word reading, which is to get children
as quickly as possible to a point where they can read
independently. Reading for themselves allows children
to build their experience with printed words, which, as
we emphasize in our key message for this section, is
crucial for building word-reading fluency. Once chil-
dren can read even simple texts on their own—either
for pleasure or for learning—their exposure to words
grows rapidly. Ultimately, it is children’s own extensive,
varied, and rich experience in reading that undoubtedly
plays the most important role in their transition from
novice to expert readers (Willingham, 2017a). Thus,
again we argue that there is a case for judicious instruc-
tion on high-frequency, difficult-to-decode words as
part of a comprehensive and phonics-rich reading-
instruction program.
2.4.2. Teaching morphological skills. We have argued
that morphology provides an important degree of regular-
ity in the relationship between print and meaning (Plaut &
Gonnerman, 2000; Rastle, Davis, Marslen-Wilson, & Tyler,
2000) and that coming to appreciate morphological rela-
tionships may therefore be an important part of becom-
ing a skilled, fluent reader (Rastle, 2018). Likewise, Kirby
and Bowers (2017) conceptualize morphology as a “bind-
ing agent” (p. 439) that relates orthography, phonology
and semantic information and thus enhances representa-
tional quality (see also J. S. Bowers & Bowers, 2017).
Reading Acquisition 25
Many children may acquire morphological knowledge
implicitly through their language and reading experience.
However, we believe that, because of the importance of
morphology in relating word forms to their meanings,
there is an argument for explicit instruction on this aspect
of the writing system (for a fuller discussion of this issue as
it applies to classroom practice, see, e.g., Kirby & Bowers,
2017; Nunes & Bryant, 2006).
The concept of morphological instruction in reading
goes back at least to Webster’s spellers, which were
published continuously through the 18th and 19th cen-
turies (Webster, 1787). For example, the 1824 edition
of the speller includes explicit instruction on individual
prefixes and suffixes, along with their roles in word
formation (e.g., how to use -ess to denote the feminine
gender; how to use -ly to denote a quality or manner
of action). Morphological instruction continues to fea-
ture in literacy curricula today. For example, the
National Curriculum in England specifies in some detail
the prefixes and suffixes that must be taught during
primary schooling, their roles in word formation, and
the way in which they modify the spelling patterns of
stems (U.K. Department for Education, 2014). However,
despite the long history of morphological instruction
in literacy curricula, there has been less research on
the nature of this form of instruction and its effective-
ness than there has on methods of instruction that focus
on communicating the nature of the primary spelling-
sound regularities in alphabetic writing systems. Fur-
ther, research has shown that teacher knowledge of
morphology is sparse and patchy, and many teachers
are unaware of the ways in which morphemes com-
municate meaning and govern spelling construction
(Hurry etal., 2005). This seems to be a critical gap in
teacher knowledge.
Several studies have attempted to assess the impact
of morphological training interventions on literacy out-
comes (for reviews, see, e.g., P. N. Bowers, Kirby, &
Deacon, 2010; Goodwin & Ahn, 2013). These studies
have used a range of morphological interventions, age
groups, and outcome measures. Encouragingly, they
have often found an impact of morphological instruc-
tion on some measures, including vocabulary, reading
aloud, reading comprehension, and spelling. For exam-
ple, the meta-analysis reported by Goodwin and Ahn
(2013) found significant effects of morphological
instruction on decoding, vocabulary, spelling, phono-
logical awareness, and morphological awareness but
not on reading comprehension or fluency. However,
the limited number of studies and their heterogeneity
makes it difficult to draw specific recommendations for
the classroom. For example, in contrast to most studies
of phonics interventions that are focused on the initial
stages of learning to read, the meta-analysis reported
by Goodwin and Ahn (2013) included participants from
preschool through high school.
It is also important to consider what form of inter-
vention is being compared with the morphological
instruction. P. N. Bowers etal. (2010) reported moderate
effect sizes for morphological instruction compared
with regular classroom instruction but noted that these
effect sizes fall substantially compared with alternative
treatments mostly consisting of phonological interven-
tions. Of course, the nature of regular classroom instruc-
tion almost certainly differs across studies (see also
Kirby & Bowers, 2017). Research comparing morpho-
logical instruction with systematic phonics instruction
in young children is very limited. Devonshire, Morris,
and Fluck (2013) reported that morphological instruc-
tion improved young children’s literacy skills compared
with an approach that they described as “traditional
phonics” (p. 85). However, although the phonics con-
trol condition in their study did provide systematic
instruction on grapheme-phoneme relationships, it
appeared to mix this instruction with rote learning of
whole words and encouragement to guess words from
context or picture cues, features that may not character-
ize effective systematic phonics programs.
In summary, though we believe that explicit instruc-
tion on the nature of morphological relationships in the
writing system is likely to benefit the acquisition of
literacy, the form of instruction likely to be most effec-
tive remains unclear. One important question is this:
When should morphological instruction linked to
printed words begin? Some researchers have argued
that it should be introduced at the earliest stages of
learning to read, before alphabetic knowledge is firmly
established (e.g., J. S. Bowers & Bowers, 2017; Devonshire
etal., 2013). However, this suggestion awaits evidence.
Analyses of the Children’s Printed Word Frequency Data-
base (Masterson etal., 2010) suggest that children’s text
experience in the first year of reading instruction con-
sists overwhelmingly of words with a single morpheme
(Rastle, 2018). Thus, morphological instruction can play
only a limited role and may detract from vital time spent
learning spelling-sound relationships. Instead, we
would predict that the benefits of explicit morphologi-
cal instruction are more likely to be observed somewhat
later in reading development, promoting learning as
children accumulate the experience necessary to
accomplish the direct mapping between spelling and
meaning (Rastle, 2018). That is not to say that classroom
instruction should not include activities to support the
development of rich vocabulary knowledge, which of
course will include morphologically complex words.
This can be achieved via listening activities, storytelling,
and so on (see Section 3.4). When and how explicit
instruction regarding orthography-morphology links
26 Castles et al.
should be introduced are important questions for future
2.4.3. Motivating children to read. As we have discussed,
the single most effective pathway to fluent word reading
is print experience: Children need to see as many words
as possible, as frequently as possible (Stanovich & West,
1989). Teachers can seek to provide as much exposure to
print as they can during classroom activities and in home-
work, but what they can achieve will be minuscule com-
pared with the exposure that children can attain for
themselves during their independent reading. Anderson,
Wilson, and Fielding (1988) monitored the out-of-school
reading habits, both of books and of other kinds of text,
of a group of U.S. Grade 5 children (ages 10 and 11). On
the basis of the amount of time the children reported
spending reading per day, Anderson etal. estimated the
number of words that the children would have been
exposed to over a year. Those at the 10th percentile of
time spent reading were estimated to be exposed to
approximately 60,000 words per year; those at the 50th
percentile, 900,000 words; and those at the 90th percen-
tile, more than 4 million words. This study was con-
ducted before the digital era, and modern children’s
habits are likely to have changed somewhat; however, it
is unlikely that the staggering variability in children’s
print exposure during their independent activities has
altered greatly. And these differences in exposure have
cumulative effects on reading ability over time, with the
rich getting richer and the poor getting poorer—the so-
called Matthew effect (Stanovich, 1986).
Such statistics point to the huge value of fostering a
love of reading in children and a motivation to read
independently. But how is this to be achieved? This ques-
tion has plagued educators (and parents) for decades,
and there are no easy answers. In his book The Reading
Mind, Daniel Willingham (2017a) discusses a range of
strategies and the evidence for their efficacy. He begins
by noting that one widely used method—rewarding chil-
dren for reading—may paradoxically have a negative
impact on their motivation to read. Although provision of
a reward will induce a desired behavior in the short term,
the long-term impact is to lead children to believe that
the behavior must have no intrinsic value in its own right,
and they are therefore less likely to engage in it in the
absence of a reward than if they had never been rewarded
in the first place (see Deci, Koestner, & Ryan, 1999).
Potentially more effective strategies for increasing
children’s motivation to read that are suggested by Will-
ingham fall into two broad categories: maximizing the
value of reading and making the choice to do so easy.
Children will value the activity of reading more if they
have opportunities to read texts that they are interested
in, that their friends are reading, or that are of some
practical use to them. For example, comics, books of
song lyrics, movie novelizations, or sporting skill manu-
als are all texts that—although they do not fall into the
category of great literature—may be intrinsically moti-
vating to a child. In relation to making the choice easy,
Willingham notes that the amount of personal time that
children spend reading depends not just on whether
they want to read but also on whether they want to do
it more than all the other available options. He refers
to a recent survey in which 30% of teenagers reported
that they enjoyed reading “a lot” but also reported that
they enjoyed other activities such as watching videos
and gaming more (Rideout, 2015). To shift the decision
in favor of reading, Willingham suggests making that
option as available as possible, noting that even small
increases in availability have been shown to affect
choices in other contexts; for example, moving the
salad bar closer to restaurant diners by just 10 inches
is enough to make them more likely to select food from
it (Rozin etal., 2011; see Halpern, 2015). Therefore,
Willingham recommends making sure that reading
material is highly visible—in every classroom, in mul-
tiple rooms in the house, in the car, and so on—to
maximize the chance that children will pick something
up and read it. This “nudge” practice is nicely illustrated
by an airline that has initiated a children’s book club,
complete with “flybraries”—mobile libraries of chil-
dren’s books on holiday flights (see Brown, 2017).
A final point to note here is that the desire to read is
integrally linked with reading ability itself: Children are
more motivated to read, and engage in it more, when
they are good at it (Mol & Bus, 2011; Willingham, 2017a).
Therefore, the question of how to best motivate children
to read should not be seen as divorced from the ques-
tion of how best to teach them. On the contrary, one
clear and achievable means of maximizing motivation
is to ensure that children have solid basic skills and
consider being “a reader” a key part of their identities.
Skilled alphabetic decoding and fluent word reading are
fundamental to achieving this outcome, but they are not
all there is to it—as we see in the next section.
3. Learning to Comprehend Text
Children need to be able to identify the majority of
words contained in a written text if they are to com-
prehend it. Clearly, however, text comprehension
requires much more than the capacity to identify and
read individual words. Indeed, these simple but impor-
tant insights are the basis of the highly influential Sim-
ple View of Reading (Gough & Tunmer, 1986; Hoover
& Gough, 1990; for a discussion, see Box 5).
A glance back to Box 1 reminds us that reading
comprehension is complex, even for a simple
Reading Acquisition 27
two-sentence text. The multifaceted nature of reading
comprehension means that no single unified model or
account details all that happens as a person reads a
text, letalone how a child develops the capacity to
understand written language. In its broadest sense,
understanding comprehension requires us to describe
how people construct meaning from information in
their environment—a huge topic that is not restricted
to written language and that is well beyond the scope
of this article. Instead, we will constrain our review
to key factors that influence the development of read-
ing comprehension and those aspects of the literature
that are most relevant for teaching and classroom
Box 5. The Simple View of Reading
The Simple View of Reading (Gough & Tunmer, 1986; Hoover & Gough, 1990) posits that reading com-
prehension is the product of two sets of skills, “decoding” and “linguistic comprehension” (R = D × C ).
The logical case for the Simple View is clear and compelling: Decoding and linguistic comprehension
are both necessary, and neither is sufficient alone. A child who can decode print but cannot comprehend
is not reading; likewise, regardless of the level of linguistic comprehension, reading cannot happen
without decoding. This simple framework has had influence both within and beyond the scientific com-
munity: Its clarity is appreciated by practitioners and it has formed the basis of national reading reforms
in England (Rose, 2006).
The Simple View of Reading
Support for the Simple View
Measures of decoding and of linguistic comprehen-
sion each predict reading comprehension and its de-
velopment, and together the two components ac-
count for almost all the variance in this ability (e.g.,
Lervåg, Hulme & Melby-Lervåg, 2017). Early in de-
velopment, reading comprehension is highly con-
strained by limitations in decoding. As children get
older, the correlation between linguistic and reading
comprehension strengthens, reflecting the fact that
once a level of decoding mastery is achieved, reading
comprehension is constrained by how well an indi-
vidual understands spoken language (LARRC, 2015).
Limitations of the Simple View
Although the Simple View is a useful framework, it can only take us so far. First, it is not a model: It does
not tell us how decoding and linguistic comprehension operate or how they develop. Second, in testing
predictions of the Simple View, the field has been inconsistent in how the key constructs are defined
and measured. In relation to decoding, as Gough and Tunmer (1986) themselves noted, it can refer to
the overt “sounding out” of a word or to skilled word recognition, and measures vary accordingly. In
relation to linguistic comprehension, measures used have ranged from vocabulary to story retell, infer-
ence making, and verbal short-term memory. To fully understand reading development, we need more
precise models that detail the cognitive processes operating within the decoding and linguistic compre-
hension components of the Simple View.
Poor Good
Decoding Decoding
28 Castles et al.
3.1. Reading comprehension: A view
from skilled reading
As for word reading (see Section 2.1), much is known
about the processes involved in reading comprehension
in skilled adult readers. The sentence processing litera-
ture is rich and extensive, much of it informed by
experiments that monitor eye movements as people
read text silently (for review, see Rayner etal., 2016).
Complementing this is the large discourse processing
literature (for review, see Schober, Rapp, & Britt, 2018).
Alongside eye-movement studies that monitor reading
as it happens on-line, much has been learned using
methods that probe comprehension off-line—that is,
after the material has been read. Standard paradigms
for this include probing memory for text or asking
participants comprehension questions after they have
read a passage. This evidence base from adults is
important because it identifies what needs to develop,
so we begin by summarizing some findings from this
literature (for detailed reviews, see Kintsch, 1998;
Kintsch & Rawson, 2005; McNamara & Magliano, 2009;
O’Brien, Cook, & Lorch, 2015; Zwaan & Radvansky,
1998). Another important point to note at the outset is
that many of the cognitive operations involved in read-
ing comprehension are not specific to reading, but
serve language comprehension more generally.
There is general consensus that as people read, they
construct a mental representation of the situation being
described by the text, linking information from the text
with relevant background knowledge. The product of
comprehension is not a verbatim record of what has
been read, replicating its form and structure; instead,
meaning emerges from the formation of a situation
model (e.g., Kintsch, 1998; Zwaan & Radvansky, 1998)
that builds dynamically as people read, culminating in
a rich representation of the text that goes beyond what
is stated explicitly. The foundation of the situation
model is delivered by incremental analysis of words and
their syntactic roles in phrases or sentences. This con-
nects with knowledge drawn either from information
provided explicitly in the text or from readers’ relevant
background knowledge. Knowledge is broadly con-
ceived and may include information such the meanings
of words, rules of grammar, knowledge of events and
temporal relations, episodes, scenarios, emotions, and
characters. Inferences need to be made beyond what is
overtly stated to establish meaning within and between
sentences and need to draw on background knowledge
(see Box 1, in which we infer that Denise was in a car
and on her way to work). Good evidence suggests that
important aspects of reading comprehension and infer-
ence generation happen automatically, but readers can
also deploy strategies to support comprehension (for
relevant discussion, see Cook & O’Brien, 2015). Together,
these allow people to construct meaning actively as they
read, adapting their strategies and focus according to
the properties of the text (e.g., its difficulty) and their
goals (e.g., reading for pleasure versus reading for
In summary, reading comprehension is not a single
entity that can be explained by a unified cognitive
model. Instead, it is the orchestrated product of a set
of linguistic and cognitive processes operating on text
and interacting with background knowledge, features
of the text, and the purpose and goals of the reading
3.2. Factors influencing development
of reading comprehension in children
Having set out some of the steps involved in skilled
reading comprehension, we turn to consider what
might be important for its development. By the time
children learn to read, they already have a sophisticated
language system that allows them to produce and com-
prehend oral language; this oral language system con-
tinues to develop during the primary school years. This
system and the linguistic knowledge derived from it
serve reading comprehension, once children can read
for themselves. As we shall see, oral language sets a
vital foundation for reading comprehension and its
Perfetti and Stafura’s (2014) Reading Systems Frame-
work identifies three constructs that underpin reading
comprehension. The first is concerned with knowledge,
be it linguistic knowledge, orthographic knowledge, or
general knowledge. The second describes processes
involved in reading, in which they include decoding,
word identification, meaning retrieval, sentence pars-
ing, inferring, and comprehension monitoring, along
with the interaction of these processes with each other,
and with knowledge. The third factor captures general
cognitive resources such as memory. All of these factors
matter. Consider, for example, poor comprehenders—
children who read words at age-appropriate levels but
have difficulty understanding what they have read (or
heard—listening comprehension also tends to be low).
A common research strategy is to compare the perfor-
mance of poor comprehenders and skilled compre-
henders on a particular task hypothesized to be relevant
to explaining individual differences in reading compre-
hension. Broadly speaking, poor comprehenders show
weaknesses on measures that tap all three of Perfetti
and Stafura’s constructs—knowledge, processes impli-
cated in reading, and general cognitive factors (for
review, see Nation, 2005; Oakhill, Cain, & Elbro, 2014).
Importantly however, no “magic profile” captures why
Reading Acquisition 29
an individual child might struggle. Given the complexi-
ties of comprehension, this is perhaps not surprising:
As Perfetti (1994) notes, “there is room for lots of things
to go wrong when comprehension fails” (p. 885).
Another important lesson from the literature on poor
comprehenders is that even when a group-level differ-
ence is seen on a particular task, it does not follow that
the factor manipulated in that task is the underlying
cause or explanation for the reading comprehension
problem. Although knowledge, processing, and general
cognitive factors are ostensibly separable, the reality is
that they are difficult to disentangle, as Perfetti and
Stafura (2014) recognize. For example, how well a child
knows a word influences how efficiently it is processed,
and this, in turn, influences the demands placed on
general resources such as working memory (defined as
the mechanisms or processes involved in the control,
regulation, and active maintenance of task-relevant
information in the service of complex cognition; Bad-
deley, 2012). Thus, a group difference in working mem-
ory might be observed for verbal information, but this
might not reflect a memory problem per se; it might be
a consequence of differences in vocabulary knowledge.
Low vocabulary constrains comprehension, as we dis-
cuss shortly, but low knowledge itself might be a con-
sequence of differences in processing. For example,
children who struggle to generate inferences are less
able to use context to discover the meaning of new
words (Cain, Oakhill, & Lemmon, 2004), and this might
lead to differences in vocabulary knowledge over time,
as children get older. Thus, not only is comprehension
multifaceted (i.e., the factors interact in multiple ways
during the process of reading), it is also complex devel-
opmentally. With this complexity in mind, we now dis-
cuss what is needed to bring about effective reading
comprehension, guided by our brief overview of the
processes involved in reading comprehension and the
principles set out by the Reading Systems Framework
(Perfetti & Stafura, 2014).
3.2.1. Knowledge. Knowledge is fundamental to com-
prehension. Perfetti and Stafura (2014) highlight ortho-
graphic, linguistic, and general knowledge as key sources
of knowledge to be acquired. Given our overview of word-
reading development in earlier sections, orthographic
knowledge requires no further consideration, other than to
reiterate that reading comprehension cannot happen with-
out adequate levels of word-reading skill.
What types of linguistic knowledge are important?
Overwhelming evidence indicates that vocabulary
knowledge matters: Understanding the majority of
individual words within a text is a prerequisite to
understanding that text. Vocabulary correlates with
reading comprehension (for review, see M. Spencer,
Quinn, & Wagner, 2017). This tight association might
reflect bidirectional influences: Oral vocabulary sets the
foundation for reading comprehension and successful
reading itself and then provides opportunities to expand
vocabulary. For younger children, at least, vocabulary
seems to drive the development of reading comprehen-
sion. Quinn, Wagner, Petscher, and Lopez (2015) ana-
lyzed longitudinal data from U.S. children between
Grades 1 and 4 (approximately ages 7–10) to investigate
the nature of the developmental correlation. They
found that vocabulary had a strong effect on growth in
reading comprehension, but not vice versa. This is not
to say that children do not learn new words via reading.
Once children can read, reading provides the major
substrate for vocabulary growth (Nagy & Herman,
1984), but variations in word learning might be driven
more by factors associated with vocabulary learning
itself, rather than reading comprehension.
Rich vocabulary knowledge subsumes not just the
number of individual words known, but how well they
are known and how flexibly they can be used in a given
context (this is critical given that the majority of words
are polysemous—i.e., they have multiple meanings or
“senses” to a greater or lesser extent; Rodd, in press).
Beyond single words, text comprehension demands
knowledge of multiword utterances (e.g., the meaning
of the phrase “by the way” cannot be deduced from the
meaning of its individual words); idioms (e.g., “kick the
bucket,” “break the ice”), and other figurative expressions
that occur frequently in text. Poor comprehenders show
reduced knowledge of idioms and figurative expressions
(Cain & Towse, 2008; Nation, Clarke, Marshall, & Durand,
2004), as do some children who are reading in their
nonnative language (Murphy, 2018; S. A. Smith & Murphy,
2015). For second-language learners, reading compre-
hension processes are not deficient in themselves, but
limitations in reading comprehension might follow from
differences in knowledge relative to children whose first
language is the majority language.
Alongside lexical knowledge, children need to know
how words in a sentence operate together. It is not
surprising, then, that performance on tasks that tap
syntactic comprehension or awareness of morphology
in spoken language is associated with reading compre-
hension (e.g., Lervåg, Hulme, & Melby-Lervåg, 2017;
Muter, Hulme, Snowling, & Stevenson, 2004), and chil-
dren with poor reading comprehension tend to perform
less well than their peers on morphological awareness
measures similar to those discussed earlier in Section
2.2.3 (Nation etal., 2004; Tong, Deacon, Kirby, Cain, &
Parrila, 2011). Children need to know how cohesive
devices such as anaphor (i.e., words that refer to earlier
antecedents, such as how she and her refer to Denise
in Box 1) and connectives (e.g., so, because, but) work
30 Castles et al.
because these allow information and ideas to be inte-
grated across phrases and sentences. This is essential
for a coherent and cohesive situation model to be con-
structed. Children with poor reading comprehension
are less skilled at dealing with anaphor and other cohe-
sive devices (e.g., Cain, Patson, & Andrews, 2005;
Ehrlich & Remond, 1997).
Like vocabulary, knowledge of grammar and syntax
is part of a child’s spoken-language repertoire. Many
longitudinal studies show that oral language proficiency
at school entry predicts later reading comprehension
(e.g., Hulme, Nash, Gooch, Lervåg, & Snowling, 2015;
Lervåg et al., 2017). Likewise, poor comprehenders
have weaknesses in oral language that predate the
onset of reading (Catts, Adlof, & Ellis-Weismer, 2006;
Elwér etal., 2015; Nation, Cocksey, Taylor, & Bishop,
2010), consistent with the view that oral language is at
the foundation of reading comprehension. We agree
with this conclusion. It is important to add, however,
that written language is different from spoken language
(e.g., Olson, 1977, 1996), meaning that the task of read-
ing comprehension brings its own challenges. There
are differences in formality and tone, and, strikingly,
even books written for beginning readers contain lan-
guage that is quite different from what is heard in
ambient conversation in terms of content and complex-
ity (see Box 6). Thus it follows that once children can
read, they have the opportunity to learn new aspects
of language via engagement with written text.
Turning to knowledge more broadly, higher levels
of relevant background knowledge are associated with
higher levels of comprehension (e.g., Barnes, Dennis,
& Haefele-Kalvaitis, 1996; Kendeou & van den Broek,
2007). As with vocabulary, the availability of back-
ground knowledge in long-term memory allows rele-
vant knowledge to be activated as the situation model
builds during reading. This provides a coherent repre-
sentation of the text and is required for the formation of
many types of inference (e.g., Kintsch & Rawson, 2005);
it also serves to enrich the situation model. Willingham
(2017a) illustrates the importance of background
knowledge by inviting his readers to consider the fol-
lowing text:
Carol Harris was a problem child from birth. She
was wild, stubborn, and violent. By the time Carol
turned eight, she was still unmanageable. Her
parents were very concerned about her mental
health. There was no good institution for her
problem in her State. Her parents finally decided
to take some action. They hired a private teacher.
(p. 122)
This makes perfect sense as a text, but imagine that,
instead of Carol Harris, the protagonist is in fact Helen
Keller, the well-known writer who was both deaf and
blind from a young age. This knowledge changes one’s
perspective on the text or, as Willingham tells his read-
ers, “Your situation model is colored by information
outside the text, namely, other relevant knowledge from
your memory. If that knowledge is missing, the situation
model won’t be the same.” Poor readers tend to have
less background knowledge and are less likely to draw
on it as they read (for review, see Compton, Miller,
Elleman, & Steacy, 2014).
3.2.2. Processing. Knowledge is clearly important, but
knowledge needs to be activated and processed during
the course of reading comprehension. Several processes
are engaged as people read. In this section, we focus
briefly on three: meaning activation, inference genera-
tion, and comprehension monitoring.
We discussed earlier how the nature of the writing
systems dictates how children get from print to meaning
when reading words (see Section 1.1). Reading experi-
ence allows words to be identified rapidly and accu-
rately and for their meanings to be activated and
integrated during sentence processing. Children are
known to vary in word-reading skill and in vocabulary
knowledge. But are there variations in the processes
that allow meaning to be activated that cannot be
explained by differences in word-reading skill and
vocabulary knowledge? This is a hard question to
answer given the difficulty of separating knowledge
and processing, as discussed earlier in our introduction
to Section 3.2. Children with lower levels of reading
comprehension are slower to make semantic judgments
about words, and they show different patterns of
semantic priming for some stimuli (e.g., Henderson,
Snowling, & Clarke, 2013; Nation & Snowling, 1999).
These findings are consistent with the idea that word
knowledge is not all or nothing: Even if a word is
known by a child, it might be known less well or in a
way that is less connected to other words, relative to
the connections that other children might form. A con-
sequence of this might be less rich input into the situ-
ation model and, in turn, reduced comprehension.
Once activated, word meanings also need to be inte-
grated into the text representation as reading unfolds.
Perfetti and Stafura (2014) describe this as word-to-text
integration. They also note that skilled readers are bet-
ter able to integrate words into the situation model, a
finding they attribute to differences in “the knowledge
of word meanings or the use of this knowledge during
text reading” (p. 32). Information that is activated but
not needed for the situation model needs to be disre-
garded. Some evidence demonstrates that less-skilled
comprehenders are not as adept at suppressing or
inhibiting out-of-date information (Gernsbacher &
Faust, 1991; Pimperton & Nation, 2010), influencing
Reading Acquisition 31
how well the situation model is updated. However, this
might reflect limitations in background knowledge as
well (e.g., McNamara & McDaniel, 2004).
Comprehension is fundamentally about making
inferences. Children make inferences in spoken lan-
guage from a young age. This capacity continues to
develop through the school years (e.g., Barnes etal.,
1996; Currie & Cain, 2015) and predicts reading
comprehension (e.g., Language and Reading Research
Consortium [LARRC] & Logan, 2017; Lervåg et al., 2017).
For some children, inference generation is a problem.
Poor comprehenders find it difficult to integrate ideas
across a text and are less skilled at answering questions
that require an inference to be made (for review, see
Box 6. The Language of the Book
context, meaning that some cues that are present in speech (e.g., prosody, gesture, tone of voice, facial
expression) are absent in writing. To compensate, written language draws on a much larger vocabulary
and more complex grammar: Noun phrases and clauses are longer and more embedded, and the passive
voice is much more common.
Comparing Novels and Films
Baines (1996) analyzed the language content of three novels (Wuthering Heights, Of Mice and Men, and
To Kill a Mockingbird ) and their film scripts. He randomly sampled 25 passages of 100 words from each
and found differences in language content and structure. Films contained far fewer polysyllabic words,
suggesting lexical content that is morphologically less rich. Vocabulary was also less diverse. For exam-
ple, in the script extract from To Kill a Mockingbird, only 7 words began with the letter “u” (ugly, under
). In contrast, the novel extract contained 17 words (
). The two genres also differed in sentence complexity. Seeing the film or even reading the
script is no substitute for reading the novel.
Learning About the Differences Between Spoken and Written Language Starts Early
Strikingly, even books written for prereaders contain language that is quite different from what is heard
in ambient conversation.
uncrossed, under, undress, unhitched, unique, unless, unlighted, unpainted, until, up, upon, upstairs
Montag, Jones, and Smith (2015) analyzed the vocabulary in 100 children’s
books, selected from those recommended for preschoolers aged 0 to 60 months and typically used by
parents in shared reading. They compared their content with the vocabulary used by caregivers in child-
directed conversations. The books included a larger number of unique words, showing that the vocab-
ulary encountered via shared reading is more diverse. Children with more shared book experience have
the opportunity to develop a larger and more diverse vocabulary.
Differences in Syntax, Not Just Vocabulary
Cameron-Faulkner and Noble (2013) analyzed the content of 20 picture books aimed at 2-year-olds and
compared this with child-directed speech. Books contained many more complex utterances (e.g., two
verb sentences, subject-predicate sentences), which suggests that shared book reading may be an im-
portant source of language experience for children. Turning to books that children might read them-
selves, Montag and McDonald (2014) also found greater syntactic complexity. Complex sentences seen
in written language such as object-relatives (e.g.,
) and passive-relatives are virtually absent in child-directed speech; they are rare too in
adult speech, but they do feature in children’s reading. Reading thus provides the opportunity to learn
new syntactic forms—those that characterize the “language of the book.”
until, up, upstains, us, used unceiled, uncontrollable,
the student who the teacher scolded finally finished
the assignment
us, use, used
32 Castles et al.
Cain & Oakhill, 2009). It is difficult to determine
whether these difficulties reflect stable and reliable
individual differences (a) in the process (or processes)
of inference generation itself, (b) in knowledge (e.g.,
inadequate vocabulary or background knowledge), or
(c) awareness of when it is necessary or helpful to make
an inference. Limitations in working memory may also
affect the integration process; words and sentences
might be understood and relevant knowledge might be
available, but limitations in cognitive resources prevent
information from being integrated during the course of
processing (see Section 3.2.3).
Another skill that has been implicated in reading
comprehension is comprehension monitoring. This is
typically defined as the collection of strategies or skills
used to evaluate one’s own comprehension, to identify
when comprehension has gone astray, and, where
appropriate, to repair any misunderstanding. It has
been measured using tasks in which children are asked
to underline meaningless words or phrases in a text or
by asking children whether a story containing incon-
sistencies makes sense and, if not, asking them to
explain what was wrong (e.g., Oakhill, Hartt, & Samols,
2005). Performance in comprehension monitoring
increases during the primary school years and is associ-
ated with reading comprehension ability, arguably
because it taps the capacities needed to monitor,
update, and integrate information as the situation model
builds (e.g., LARRC & Geomans-Maldonado, 2017).
These findings are difficult to interpret because it is not
clear what traditional tasks of comprehension monitor-
ing are measuring. In one sense, they tap the product
of comprehension: the extent to which children have
understood what they have read well enough to be able
to reflect on its fidelity. It is not clear whether this is
akin to the more automatic processes that happen as
long-term memory is activated during the course of
normal reading.
A different approach is to measure comprehension
monitoring more directly, during reading itself, rather
than relying on a metacognitive task that taps children’s
ability to reflect on their cognitive processes after read-
ing has happened. In adults, reading times (as measured
by monitoring eye movements during silent text reading)
are influenced by plausibility. For example, in the sen-
tence John used a knife [an axe] to chop carrots, reading
and rereading times are longer for the axe version of the
sentence (Rayner, Warren, Juhasz, & Liversedge, 2004).
Children are also sensitive to plausibility when read-
ing (Joseph etal., 2008), and individual differences in
oral language (specifically, a variable comprising vocab-
ulary, verbal knowledge, and story recall) predict the
extent to which 7- to 12-year-old children show longer
rereading times when plausibility is violated (Connor
etal., 2015). Note that this study showed that Grade 5
children (approximately age 10) noticed the implausi-
bility, in that initial reading times were longer for
implausible targets than for plausible targets. However,
only those children with higher levels of oral language
skill showed longer rereading times on implausible tar-
gets, which is consistent with an attempt to integrate
and make sense of the text. These eye-movement data
reflect fast and perhaps largely automatic processing.
Likewise, Eilers, Tiffin-Richards, and Schroeder (2018)
found that 9-year-old children are sensitive to discourse-
level expectations when reading, showing surprise (i.e.,
longer reading times) when they encountered a
repeated name (e.g., Peter gets up from his bed. Right
away Peter makes breakfast), rather than the expected
anaphor (i.e., he rather than Peter in the second sen-
tence). More generally, the finding that oral language
and verbal knowledge predict reading strategies is con-
sistent with the close connection between language
proficiency and reading comprehension. This is likely
to be relevant both for in-the-moment updating and
rereading during sentence processing and for the more
active monitoring that occurs when reflecting on com-
prehension or when a text is long, complex, or lacking
in coherence.
Related to notions of comprehension monitoring is
the concept of standard of coherence, defined as a
person’s criteria for coherent understanding of a text
and therefore the extent of their motivation to make
sense of what they are reading (e.g., van den Broek,
Bohn-Gettler, Kendeou, Carlson, & White, 2011). It is
not clear whether individual differences in an overall
standard of coherence explain individual differences in
reading comprehension, but it seems unlikely. Standard
of coherence is likely to vary for everyone, depending
on the purpose of reading, their motivation to read,
their knowledge and interest in the topic, the quality
of the text, and so on (Graesser, Singer, & Trabasso,
1994). Likewise, skilled readers flexibly adapt their
reading behavior depending on their task, whether it
is reading for meaning or proofreading, for example
(Kaakinen & Hyönä, 2010; Schotter, Bicknell, Howard,
Levy, & Rayner, 2012). However, little research has
explored the factors that promote what is sometimes
referred to as purposeful reading or how the current
standard of coherence set by a child influences his or
her reading behavior. We consider this to be an impor-
tant avenue for future work. The notion that successful
reading always results in a complete and fully specified
interpretation of the text is misguided. What matters is
being able to adjust one’s reading to suit one’s reading
purpose, given the demands of the task, among other
Reading Acquisition 33
factors (for further information, see discussion of “good-
enough” and aligned perspectives, e.g., Christianson,
2016; Ferreira, Bailey, & Ferraro, 2002; Wonnacott,
Joseph, Adelman, & Nation, 2016).
In closing this section, it is worth emphasizing again
that the critical determiner of reading comprehension
in the early years is word-reading skill. Although we
know quite a lot is known about how word-reading
skill develops, as reviewed in the first part of this arti-
cle, far fewer studies have investigated how word read-
ing plays out during the process of reading
comprehension itself, given that words are normally
read silently and in meaningful sentences. As technol-
ogy has advanced, more is being learned about this
from studies of children’s eye movements as they read.
Having established many of the basic parameters in
children’s eye-movement control while reading (for
reviews, see Blythe, 2014; Blythe & Joseph, 2011;
Reichle etal., 2013), the field is well poised to learn
more about how word-, sentence-, and discourse-level
factors interact as children read for meaning.
3.2.3. General cognitive resources. Our review of read-
ing comprehension so far has emphasized the linguistic
knowledge and resources needed to construct an ade-
quate situation model. What is the role of general factors
such as executive functions? This term refers to a set of
cognitive processes that allow people to plan, organize,
control, and regulate resources to achieve a goal. Work-
ing memory, cognitive flexibility, and inhibitory control
are examples of executive skill, and all have been impli-
cated in reading comprehension. We will focus here on
working memory because this has been discussed most in
the literature on children’s reading development. Working
memory training is also an approach to intervention that
we review later (Section 3.4.3), and it is thus important to
consider its theoretical basis (for a discussion of execu-
tive skills more broadly in relation to reading compre-
hension, see Sesma, Mahone, Levine, Eason, & Cutting,
As noted earlier, working memory can be defined as
the mechanisms or processes involved in the control,
regulation, and active maintenance of task-relevant
information in the service of complex cognition
(Baddeley, 2012). It is easy to generate hypotheses
about why working memory might matter for reading
comprehension. For example, people with greater
working memory resources might be at an advantage
because they can retain more information. This might
allow more inferences to be generated and connections
to be made. Additional processing resources may also
assist with reactivating relevant information from the
text itself or from background knowledge; effective
control of working memory may allow irrelevant
information to be deactivated or suppressed, freeing
resources for ongoing comprehension.
In short, the availability of working memory resources
should facilitate the building of a detailed, rich and
well-connected situation model. In line with this predic-
tion, a strong relationship exists between reading com-
prehension and individual differences in working
memory tasks across the life span (e.g., Daneman &
Merikle, 1996). Longitudinal work has shown that work-
ing memory performance is associated with vocabulary
and inference making—key factors that influence read-
ing comprehension (e.g., Currie & Cain, 2015; Daugaard,
Cain, & Elbro, 2017). Poor working memory has been
considered a cause of impairments in children’s reading
comprehension, and ample evidence suggests that poor
comprehenders perform less well on a listening span
task. This complex working memory task requires
the simultaneous storage and processing of verbal
information—for example, listening to a series of
unconnected sentences and answering questions about
them while remembering the final word of each sen-
tence, and then reporting those words in correct serial
order (e.g., Carretti, Borella, Cornoldi, & De Beni, 2009;
Nation, Adams, Bowyer-Crane, & Snowling, 1999). Poor
comprehenders also perform less well on tasks tapping
more specific components of working memory for ver-
bal material, such as interference control, suppression,
and updating (e.g., Pimperton & Nation, 2010).
The interplay between memory and reading compre-
hension is nicely illustrated in a study by Hua and
Keenan (2014). They asked children to read a text and
then asked them questions about it. Some questions
required an inference to be made; in line with the
results of many other studies, children found these
questions harder to answer than literal questions that
could be answered by direct reference to the text. Hua
and Keenan also analyzed what information needed to
be remembered from the text to answer each question.
Inference questions required more text premises to be
remembered than did literal questions. This increases
the complexity of the integration processes required to
answer such questions. The children were also asked
what they could remember from the text. If the relevant
premises were remembered, the question could be
answered, regardless of whether it required an inference
to be made or not. Less-skilled comprehenders in this
study answered fewer questions correctly than did skilled
comprehenders, but memory for text premises accounted
for differences in comprehension performance.
These findings highlight the role of memory in read-
ing comprehension. But why do children differ in text
memory? Are there differences in the working memory
that constrain comprehension? Or are differences in
memory a natural consequence of how well the
34 Castles et al.
children understand the material in the first place, in
line with the perspective that domain-free working
memory does not exist as a separate construct (e.g.,
MacDonald & Christiansen, 2002; Van Dyke, Johns, &
Kukona, 2014)? Relevant to this question, there is strong
evidence for a close association between verbal work-
ing memory and comprehension but not for an associa-
tion between nonverbal working memory and
comprehension. For example, Yeari (2017) found that
adults who performed better on tasks that measure
working memory span were better able to retain, reac-
tivate, and inhibit textual and inferential information
when reading. However, these findings held only when
listening span was used to estimate working memory
span. When working memory was indexed using tasks
that placed fewer demands on verbal skills (memory
span tasks comprising digits or visuospatial informa-
tion), there was no relationship between working mem-
ory and reading comprehension. This observation is in
line with findings from the literature on poor compre-
henders, in which deficits in verbal working memory
are clear (Carretti etal., 2009; Pimperton & Nation,
2010). Evidence for deficits in nonverbal working mem-
ory tasks is less robust, which casts doubt on the
hypothesis that global aspects of working memory play
a major causal role. Whether it is meaningful to talk
about verbal memory capacity independent of language
processing itself remains an open question.
3.3. Learning to comprehend text:
The Reading Systems Framework (Perfetti & Stafura,
2014) helps set out the complexities of reading com-
prehension and how this interfaces with the word-
reading system. Word recognition and high-quality
lexical knowledge provide the necessary input to read-
ing comprehension, but knowledge and processes
beyond the individual word level are vital too. These
aspects are not all specific to reading but are features
of language comprehension more broadly. As we have
noted, by the time children learn to read, they already
have in place a sophisticated language system, setting
the critical foundation for reading comprehension. Con-
sistent with this, a range of oral language skills mea-
sured in preschool are closely associated with later
reading comprehension, and this relationship continues
through the primary school years (e.g., LARRC & Logan,
2017; Lervåg etal., 2017). Reading brings additional
challenges—not just the need to learn how to read
words but also the fact that written language has com-
plexities that are less evident in conversational lan-
guage (Box 6). In the early years of reading development,
reading comprehension is constrained by limitations in
word-reading ability, for obvious reasons: Comprehen-
sion will suffer if a child cannot read the words in a
text. As word-reading skills strengthen, reading com-
prehension becomes constrained by limitations in
knowledge and the capacity to build a rich and coher-
ent representation of language, regardless of whether
the language is heard or read (LARRC, 2015). This
demands a range of spoken-language skills, often sub-
sumed under the general construct of “listening com-
prehension” (see Box 5); in skilled readers, the
correlation between listening comprehension and read-
ing comprehension is almost perfect (e.g., Gernsbacher,
Varner, & Faust, 1990).
Our key messages highlight the complex and multi-
faceted nature of reading comprehension and the asso-
ciated difficulty of separating knowledge, processing,
and general resources such as memory. High-quality
knowledge promotes efficient processing, which places
fewer demands on resources. Taking a developmental
perspective adds further complexity as we try to explain
why children might have difficulty with reading com-
prehension. What might start as a processing difference
(e.g., the ease of word identification) might escalate to
differences in knowledge (e.g., vocabulary), and vice
versa. Undoubtedly, other factors beyond the scope of
this review—such as motivation to read, attitudes about
reading, or knowledge about reading for different
purposes—also contribute in complex and important
ways (for review, see Willingham, 2017a).
3.4. Reading comprehension:
Implications for the classroom
Our review has made clear that reading comprehension
is complex and multifaceted. Its foundation is in lan-
guage more generally, but written language presents
additional challenges for the reader, including but not
limited to the need to identify and recognize printed
words. We have described how comprehension comes
about through the interaction of knowledge (e.g.,
vocabulary, background knowledge), processes that
operate on text (e.g., meaning activation, inference
generation), and general cognitive factors (e.g., work-
ing memory). With this as a backdrop, we consider
implications for the classroom.
The appreciation that reading comprehension is a
complex construct leads quickly to the realization that
improving reading comprehension is unlikely to be
simple. The literature on reading comprehension
instruction is vast, and its methodological quality varies.
We focus on some key messages here because a com-
prehensive review is beyond the scope of this article.
Fortunately, however, some of the literature has been
expertly synthesized into accessible accounts and
Reading Acquisition 35
practical guides, including recent books by Oakhill
etal. (2014), Stuart and Stainthorp (2015), and P. J.
Clarke, Truelove, Hulme, and Snowling (2013).
3.4.1. Assessing reading comprehension. Assessment
has its place in the classroom, allowing teachers to iden-
tify children who may need additional support. This is
important because some children find reading compre-
hension difficult, despite being able to read words at an
age-expected level; these children can go unnoticed in
the classroom, and their needs can go unmet. Likewise,
some children get off to a good start but reading compre-
hension plateaus—the so-called fourth-grade slump (e.g.,
Leach, Scarborough, & Rescorla, 2003). Assessment also
matters when it comes to evaluating an instructional
approach. A typical research strategy is to deliver a theo-
retically motivated intervention to a group of children
and test its efficacy by determining whether it leads to
improvement on a standardized assessment relative to a
control group.
One lesson from the literature on reading-
comprehension assessment is that it is not easy to mea-
sure: It is not a single entity that can be cleanly and
reliably captured by a “gold-standard” test. Indeed,
standardized tests that are marketed as reading com-
prehension assessments can vary enormously. At one
extreme, some tests place heavy demands on word-
level reading rather than understanding (Nation &
Snowling, 1997). At the other, some contain questions
that can be answered correctly without even reading
the text (Keenan & Betjemann, 2006). Neither of these
extremes are helpful, of course, but even well-validated
and reliable instruments vary in the aspects of reading
comprehension they tap. Some of this variation is asso-
ciated with factors such as the length of the text, its
format, and the age of the reader. It is not surprising,
then, that across children, the correlation between per-
formance on one comprehension test and another is not
always high (e.g., Keenan & Meanan, 2014). And for
everyone, reading comprehension varies as a function
of knowledge—even a strong reader will struggle if the
content of the text is largely unfamiliar.
It follows that educators need to be aware of what
a particular test is measuring, and this requires some
knowledge about what reading comprehension is and
why it can vary. To this end, it is helpful to consider
the definition of reading comprehension established by
the RAND Reading Study Group (C. Snow, 2002). This
group was asked to establish a research and develop-
ment agenda to improve reading comprehension stan-
dards in U.S. schools. They defined reading comprehension
as the “process of simultaneously extracting and con-
structing meaning through interaction and involvement
with written language” (p. 11) and argued that this
demands an appreciation of the reader (e.g., individual
capacities of the child), the text (e.g., complexity, genre),
and the situation (e.g., skimming, studying, reading for
pleasure). Although devised to guide a research agenda,
this definition is highly relevant for those involved in
education too.
3.4.2. Reading comprehension instruction: Lessons
from the National Reading Panel. What instructional
approaches best help children to extract and construct
meaning from text? The National Reading Panel (2000)
considered this question at length, reviewing hundreds of
studies. Not all provided the information needed to gener-
ate effect sizes, and some were of low quality in terms of
methodology or scientific relevance; for some instruction
approaches, the evidence base was not large enough to
warrant firm conclusions. Nevertheless, the National
Reading Panel identified the benefits of explicitly teach-
ing children strategies to prompt active engagement with
text. Some key strategies emerge from the principles of
reciprocal teaching (e.g., Palinscar & Brown, 1984), in which
children are encouraged to discuss a text with peers and
teachers using methods such as clarification, summariza-
tion, prediction, and question generation. These strategies
tended to generate large effect sizes when comprehension
was assessed using measures designed by the experiment-
ers. Such measures are typically quite close to the interven-
tion in content or style. However, some (but not all) studies
also reported encouraging medium effect sizes on more
general assessments of reading comprehension, which sug-
gests that strategy instruction can promote learning that
Another encouraging finding is that the benefits of
strategy instruction appear to emerge after relatively
little instruction: There is little evidence that longer or
more intensive strategy interventions lead to greater
improvements in reading comprehension. As discussed
by Willingham (2006), this makes sense if strategies are
thought of not as skills that keep developing but as
“tricks” that, once explained and discovered, are avail-
able for children to use in other situations. In this view,
explicitly teaching a strategy helps children to under-
stand the purpose of reading more quickly than they
would otherwise, via self-discovery; although strategies
can be learned quickly and to good effect, continued
instruction and practice does not yield further benefits.
Willingham (2006) also drew our attention to the fact
that more consistent effects are seen when strategy
instruction is applied in later grades (approximately
fourth grade onward in the United States). This prob-
ably reflects the fact that a reasonable level of reading
fluency is needed before children can benefit properly
from text-level strategy instruction. How much instruc-
tion and when it is best delivered are important
36 Castles et al.
questions for further research, and both have clear
implications for the classroom. Explicit strategy instruc-
tion is effective, it can be short (Willingham suggests
five or six sessions), and it works best once the basics
of word-reading fluency are in place.
Reciprocal teaching strategies are important and
effective, but no amount of strategy instruction can
bring about successful comprehension if the text cannot
be understood because of limitations in knowledge or
difficulties with activating knowledge in the service of
comprehension. As Willingham (2006) notes,
to “summarize,” you need to comprehend enough
to differentiate the main idea from subordinate
ideas. For “comprehension monitoring” to be
useful, not only do you need to recognize that
you don’t understand a passage, but also to be
able to comprehend the material when you reread
it.” (p. 44)
Strategy instruction depends on content, and an
appreciation of content demands knowledge. The
National Reading Panel considered one type of knowl-
edge instruction in detail—vocabulary. Since then, how-
ever, two large meta-analyses have been published on
the topic of whether vocabulary instruction improves
passage comprehension (Elleman, Lindo, Morphy, &
Compton, 2009; Wright & Cervetti, 2017), so we focus
on these more recent reviews in the next section.
3.4.3. Vocabulary. The observation that children with
good and richly connected word knowledge are better at
reading comprehension (Section 3.2.1) leads to the pre-
diction that teaching vocabulary should improve reading
comprehension. To assess this, Elleman etal. (2009) con-
ducted a meta-analysis of 37 different studies. They found
that although vocabulary instruction led to significant
improvements on custom-made comprehension passages
containing the taught words (effect size: d = 0.50), trans-
fer to standardized assessments of reading comprehen-
sion was less impressive, averaging an effect size of only
d = 0.1. Wright and Cervetti (2017) reported exactly the
same pattern: Children receiving vocabulary instruction
outperformed children in the control group on compre-
hension passages containing instructed words, but transfer
to more general comprehension measures was negligible.
The finding that comprehension of passages contain-
ing taught words improved substantially is an important
one, especially given that the instructional demands of
this approach are relatively minimal. Wright and Cervetti
(2017) reported the number of minutes of instruction
per word associated with successful transfer; it is strik-
ing how low this number was, less than 1 min per word
in some studies. This suggests that even a brief instruc-
tional opportunity to develop word knowledge can
help reading comprehension. This points to the utility
of teaching content-relevant vocabulary before children
are expected to use that vocabulary to learn from text.
Both meta-analyses attempted to address which
types of vocabulary instruction might be most effective.
However, no firm conclusions could be drawn. There
were, however, hints in the data suggesting that more
active approaches might be more beneficial than more
passive ones (e.g., working in small groups and discuss-
ing the words in detail as opposed to reading brief
As noted, vocabulary instruction by itself does not
lead to improvements in passage comprehension, as
assessed by a general standardized test. This suggests
that direct vocabulary instruction alone is insufficient.
This is not surprising given what is known about the
complexities of reading comprehension (Section 3.1
and Box 1) and the fact that learning a set of words
can only have limited utility, given the unconstrained
and unlimited nature of vocabulary. However, both
meta-analyses identified approaches that might lead to
greater transfer. First, instruction that taught multiple
and flexible strategies for establishing word meaning
(e.g., using contextual cues, synonyms, syntactic con-
straints) showed a more general treatment effect:
Children in the intervention group outperformed those
in the control group on standardized reading-
comprehension measures (e.g., Nelson & Stage, 2007).
This finding is consistent with the results of a large
study by P. J. Clarke, Snowling, Truelove, and Hulme
(2010) in which poor comprehenders received training
in oral language, text comprehension, or a combination
of both. All three groups received multiple types of strat-
egy instruction, working with narrative as well as vocab-
ulary, and all three groups showed improvements in
reading comprehension, as assessed by a standardized
test at the end of the intervention. These gains were
maintained 11 months later for children in the oral
language and combined groups. Note that both groups
also showed improvements in expressive vocabulary,
and these improvements mediated improvements in
reading comprehension. In short, intervention improved
vocabulary and growth in vocabulary supported read-
ing comprehension. This finding suggests that vocabu-
lary instruction in the context of broader oral language
is effective in shifting reading comprehension.
A second fruitful approach is to focus on specific
types of words (e.g., those words that are not yet
known but need to be known to comprehend a variety
of texts and curricular topics—akin to so-called Tier 2
words, described by Beck, McKeown, & Kucan, 2013).
Reading Acquisition 37
Likewise, systematic instruction in more formal or tech-
nical academic vocabulary holds promise, especially
because such words are rare in speech. Crosson and
McKeown (2016) described an instructional approach
using explicit instruction of bound Latin roots (e.g.,
spect, as in the words prospect, specimen, spectacles,
inspect, prospector, respect; voc, as in vocal, advocate,
vocalize, vocabulary, vociferous). They found that U.S.
sixth- and seventh-grade students (approximately 11–13
years old) were able to learn about the Latin roots after
fairly minimal instruction and that this helped them
comprehend words containing those roots when read-
ing them in context. Wright and Cervetti also noted the
effectiveness of instructional approaches that focus on
the connectivity of new words to other words (via
semantic categories or synonym games). This fits with
the idea that vocabulary knowledge needs to be flexible
and nuanced to the relevant context (Section 3.2.2).
Words that act as cohesive ties, marking features such
as temporal order (first, initially, before, after) and cau-
sality (because, thus, since), are also important to learn
because they play a critical role in the construction of
a coherent and cohesive situation model, allowing ideas
to be connected across phrases and sentences. Quigley
(2018) provided a comprehensive review of classroom
approaches to support vocabulary growth.
Vocabulary is just one component of knowledge.
C. E. Snow (2017) stresses that other aspects of knowledge
also matter for language and literacy development. The
gradual acquisition of knowledge and cultural literacy—
via teaching, conversations, experiences, and of course
reading itself—is critical (e.g., Hirsch, 2016). Arguably,
however, it is not just knowing things that matters—
children need to bring relevant knowledge to the fore
during the process of reading comprehension, especially
when inferences need to be made that depend on that
knowledge. Is it possible to deliver instruction to target
this critical component of reading comprehension?
3.4.4. Inferences. Many of the instructional strategies
reviewed by the National Reading Panel are implicated in
inference generation in some way. The National Reading
Panel itself did not specifically discuss the impact of
inference instruction on inferential comprehension, but
the literature has been recently reviewed by Elleman
(2017). Inference instruction was shown to benefit read-
ing comprehension (as assessed by standardized tests, d =
0.58); alongside this general effect, performance on infer-
ential aspects of comprehension also improved (d = 0.68).
Not surprisingly, transfer to literal comprehension was
lower. These are encouraging effects; once again, instruc-
tion benefits seemed to follow quickly and more practice
was not associated with greater gains (Willingham, 2017b).
Unfortunately, it was not possible to identify which instruc-
tional approaches are most beneficial because of limita-
tions in the size or quality of the evidence base. In addition,
many of the studies contained multiple components,
which makes it impossible to compare the effectiveness
of specific strategies.
We agree with Elleman’s (2017) call for future studies
to isolate and assess the efficacy of specific instruction
components. This is the only way to truly identify what
works. A good example of this approach is provided
by Elbro and Buch-Iversen (2013), who taught 11-year-
olds to use graphic organizers to explicitly draw on
background knowledge to make a “gap-filling” infer-
ence. Graphic organizers are visual displays, maps, or
diagrams (in this case, a series of connected boxes that
students fill in) that demonstrate the relationship
between ideas. A gap-filling inference requires informa-
tion to be imported from long-term memory to provide
the necessary connection between premises in a text.
After only eight 30-min sessions, children taught to use
graphic organizers out-performed their peers on a
bespoke reading comprehension task (different pas-
sages but with inference demands similar to those of
the training passages; d = 0.92) and a general assess-
ment of reading comprehension (average d = 0.69).
Furthermore, the training advantage was maintained
over time. These findings indicate that children can be
taught to activate background knowledge spontane-
ously and that this capability transfers to new situations.
More generally, the findings point to the utility of com-
bining direct strategy instruction with reading for mean-
ing, using rich texts that place demands on background
3.4.5. Working memory. In addition to the availability
of knowledge in long-term memory, working memory is
implicated in the reading-comprehension process (Section
3.2.3). If working memory resources limit comprehension,
is it possible to improve reading comprehension by
strengthening working memory? The answer to this ques-
tion seems to be “no.” Simons etal. (2016) provided an
extensive review of cognitive training programs in this
journal and found little evidence that such training affects
everyday cognitive performance, including reading. A
meta-analysis focusing specifically on working memory
training came to the same conclusion, finding no evidence
of reliable transfer to reading comprehension (Melby-Lervåg,
Redick, & Hulme, 2016). On the basis of the available evi-
dence, then, current working memory training programs do
not improve reading comprehension. Instead, instruction
should focus on developing lexical quality at the word level
and optimizing children’s knowledge and skills so that lim-
ited working memory resources can be used to best effect.
38 Castles et al.
3.5. Reading comprehension in the
classroom: Summary
Understanding that reading comprehension is complex
and multifaceted is relevant for thinking about assess-
ment and effective instruction. The foundation of read-
ing comprehension is provided by oral language:
Vocabulary, grammar, and narrative skills at school
entry and beyond predict later reading comprehension
(e.g., LARRC & Logan, 2017; Lervåg etal., 2017). Even
before children can read, interventions that target oral
language lead to improvements in reading comprehen-
sion (Fricke, Bowyer-Crane, Haley, Hulme, & Snowling,
2013). This is an important observation and underlines
the idea that not all teaching to improve reading com-
prehension needs to involve written text. While chil-
dren are focusing on the discovery of the alphabetic
principle and learning to read words, for example,
instruction in oral language will bring about gains in
knowledge and enhance the processing skills that will
subsequently serve reading comprehension. Given that
language proficiency at school entry varies enormously
(e.g., Norbury etal., 2016), some children will need
extensive language support.
Comprehension strategies can be taught, and evi-
dence suggests that they can be learned quickly and
applied to new reading material after relatively little
instruction. More evidence is needed to identify which
strategies should be taught, when, and for how long.
While strategy instruction might be quick, the acquisi-
tion of knowledge is gradual and continuous. This can
be assisted by direct teaching and using structured mate-
rials that support the curriculum; ultimately, however,
it relies on rich input, much of which will come from
reading experience itself (e.g., Hirsch, 2016). We dis-
cussed earlier the value of reading experience and the
need to motivate children to read more (Section 2.4.2).
We repeat that message here—teaching children to read
and then providing opportunities for varied, extensive,
and successful reading experience is fundamental.
4. Conclusions
We commenced this review by asking why the reading
wars have continued. Despite extensive scientific evi-
dence, accumulated over decades, for the centrality of
alphabetic decoding skills as a foundation of learning
to read, there remains resistance to using phonics
instruction methods in the classroom. We suggested
that two factors may have contributed to this resistance.
First, limited knowledge about the nature of writing
systems among many practitioners means that they are
not equipped to understand why phonics works for
alphabetic systems. Second, practitioners know that
there is more to reading than alphabetic skills, but a
full presentation of the scientific evidence in relation
to these more advanced aspects of reading acquisition
in a public interest forum has been lacking; as a result,
calls for a greater focus on phonics instruction can seem
We have sought to address both of these issues by
providing a comprehensive tutorial review on the sci-
ence of learning to read that spans from foundational
alphabetic skills right through to the sophisticated set
of processes that characterize skilled reading compre-
hension. We have attempted throughout to explain not
just the whats of the evidence, but also the whys, so
that practitioners are in a position to make informed
judgments about how the evidence we have presented
might be translated into effective classroom practice.
Emerging from these explanations are three central
messages in relation to each of the major aspects of
reading acquisition we have reviewed: that the writing
system matters, that experience matters, and that the
ultimate goal of reading—comprehension—is not a uni-
tary construct but a multifaceted process. Given its
breadth, our review is of course limited in detail; in
Box 7, we make recommendations on further reading
suitable for practitioners that covers many of these
issues in depth.
What then, are the broad implications of our review
for developing instructional principles and for setting
an agenda for ongoing research in reading acquisition?
One clear message is that teaching and research must
be informed by a detailed knowledge of the writing
system being learned and of the broader language sys-
tem it represents. In relation to teaching, teacher train-
ing programs are doing future educators a huge
disservice if they do not equip them with this knowl-
edge. There appears to be a long way to go: Evidence
from studies across a range of countries suggests that
teacher knowledge in these areas is typically very lim-
ited (see, e.g., Aro & Björn, 2016; Fielding-Barnsley,
2010; Hurry etal., 2005; Moats, 2009). In relation to
research, much remains to be learned about how chil-
dren acquire more sophisticated knowledge about the
structure of their writing system and the way in which
it represents sound and meaning, particularly for mor-
phologically complex and polysyllabic words. Ques-
tions about the development of text comprehension
also remain.
A second broad implication of our review is the need
to get the balance right in setting the agenda for instruc-
tion, and for future research. The term balanced literacy
is in widespread use, often to describe programs with
“a bit of everything” and typically involving limited and
nonsystematic phonics instruction (see P. Snow, 2017).
This is unfortunate because it is clear from our review
Reading Acquisition 39
that many different factors come together to produce
a child who reads fluently for meaning and that instruc-
tion needs to consider all of them. In our view, it would
be valuable to reclaim a term such as balanced instruc-
tion and recast it in a more nuanced way that is
informed by a deep understanding of how reading
develops. The guiding principle here would be that
although there are many different aspects of reading
that must be learned—alphabetic decoding, fluent word
reading, text comprehension—this does not mean that
instructional time should be devoted equally to all of
them at all points in reading acquisition. Rather, instruc-
tional regimens to support these various abilities are
likely to be most effective at particular points in devel-
opment, and limited teaching time should be structured
to reflect this. For example, detailed instruction in mor-
phological regularities or strategies for text comprehen-
sion is unlikely to produce maximum benefits before
children have mastered basic alphabetic decoding skills.
From a research perspective, there is much to be learned
about the time-course of acquisition of different reading
skills and how they interact with each other and with the
knowledge they depend on and produce. Further research
is needed to produce a developmentally informed and
balanced literacy instruction program, well-placed to pre-
vent instructional casualties (Lyon, 2005).
In conclusion, the state of the science of learning to
read was reviewed comprehensively in this journal
more than 15 years ago (Rayner, Foorman, Perfetti,
Pesetsky, & Seidenberg, 2001). It is thus surprising and
Box 7. Recommended Further Reading for Practitioners and Parents
Adams, M.J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press.
Carroll, J. M., Bowyer-Crane, C., Duff, F.J., Hulme, C., & Snowling, M.J. (2011). Developing language
and literacy: Effective intervention in the early years. West Sussex, England: Wiley-Blackwell.
Clarke, P. J., Truelove, E., Hulme, C., & Snowling, M.J. (2013). Developing reading comprehension.
West Sussex, England: Wiley.
Dehaene, S. (2009). Reading in the brain. New York, NY: Penguin Viking.
Kilpatrick, D.A. (2015). Essentials of assessing, preventing and overcoming reading difficulties. Hobo-
ken, NJ: Wiley.
Moats, L.C. (2010). Speech to print: Language essentials for teachers. Baltimore, MD: Brookes Pub-
Oakhill, J., Cain, K., & Elbro, C. (2014). Understanding and teaching reading comprehension: A hand-
book. Abingdon, England: Routledge.
Seidenberg, M. (2017). Language at the speed of sight: How we read, why so many can’t, and what
can be done about it. New York, NY: Basic Books.
Stuart, M., & Stainthorp, R. (2015). Reading development and teaching. Thousand Oaks, CA: SAGE.
Willingham, D. (2017). The reading mind: A cognitive approach to understanding how the mind reads.
San Francisco, CA: Jossey-Bass.
Wolf, M. (2007). Proust and the squid: The story and science of the reading brain. New York, NY: Har-
per Collins.
40 Castles et al.
concerning that the reading wars continue. It is our
hope that this review will contribute to ending these
wars, so that a further examination of the status of this
debate 15 years hence will not be required.
We are grateful to our editors, reviewers, and many others
who provided helpful feedback on earlier versions of this
manuscript, including Max Coltheart, Saskia Kohnen, Rauno
Parrila, Charles Perfetti, Valerie Reyna, Roddy Roediger,
Elizabeth Schotter, Maggie Snowling, Rhona Stainthorp,
Rebecca Treiman, and Hua-Chen Wang. We also gratefully
acknowledge research assistance support from Megan Bird,
Benedetta Cevoli, Nardeen Massoud, and Julianne Pascoe.
Declaration of Conflicting Interests
The author(s) declared that there were no conflicts of interest
with respect to the authorship or the publication of this
This work was supported by Australian Research Council
Centre of Excellence in Cognition and Its Disorders Grant CE
110001021 (to A. Castles and K. Nation), Economic and Social
Research Council Grants ES/L002264/1 and ES/P001874/1 (to
K. Rastle), Economic and Social Research Council Grant ES/
M009998/1 (to K. Nation and A. Castles), and The Leverhulme
Trust Grant RPG-2015-070 (to K. Nation).
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