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The literacy abilities of 11 year-old students from sociallydisadvantaged backgrounds
BETH MCINTOSH1,2, MARGARET TAYLOR3, SHARON CROSBIE1,2,
ALISON HOLM1,2, & BARBARA DODD1,2
1Perinatal Research Centre, University of Queensland, Australia, 2Royal Brisbane and Women’s Hospital, Queensland,
Australia, and 3Education Queensland, Queensland, Australia
AbstractThis study investigated the literacy skills of all children in Year 6 of a Queensland school in a socially disadvantaged area whowere exposed to a ‘‘whole language’’ approach to the learning of written language. Standardized tests of non-word spellingand reading comprehension (including written sentence responses) revealed a large group of children with literacydifficulties. This group of 11-year-old children, and a group of matched controls, were further assessed on measures ofphonological awareness and letter sound knowledge. The results indicated that the means of both groups were below those ofthe standardization populations, and that the children had particular difficulty writing short answers to questions. The groupof children identified as performing poorly on the non-word spelling test was heterogeneous. Some had poor phonologicalawareness skills, some had limited sound-letter correspondence knowledge, some children had problems with both skills.The data demonstrated the need for assessment to identify the specific sub-skills with which individuals have difficulty, inorder to allow for appropriate intervention rather than a generic phonological awareness intervention package for all childrenwith literacy difficulties irrespective of age or social status.
Keywords: Literacy, socio-economic background, phonological awareness, language comprehension, upper primary.
Introduction
The academic performance of children entering
secondary schools depends upon their comprehen-
sion of written text and their ability to produce well
structured written language (Leahy & Dodd, 2002;
Roberts, 2004). Poor literacy is associated with acade-
mic failure, behaviour problems and reduced moti-
vation that limits children’s ability to achieve
their potential (High, LaGasse, Becker, Ahlgren, &
Gardner, 2000). While the children reported to be
most at risk for spoken and written language diffi-
culties are those from socially deprived backgrounds
(Bowey, 1995; Burt, Holm, & Dodd, 1999; Dodd &
Carr, 2003; Duncan & Seymour, 2000; Locke,
Ginsborg, & Peers, 2002; Raz & Bryant, 1990),
Coomber (1997) contends that it is simplistic to equate
poverty and illiteracy. Rather, explanations for literacy
failure need to focus on the learning environment.
One aspect of the literacy learning environment is
teaching methodology. For example, research sug-
gests that the whole language teaching approach
adopted by many schools does not explicitly link
speech sounds and letters so that children can acquire
the alphabetic principle (e.g., van Kraayenoord &
Paris, 1994). In addition, some children may receive
little literacy learning experience outside school.
Children from disadvantaged backgrounds are as-
sumed to be at greater risk of not gaining adequate
exposure to written text at home (Adams, 1994;
Fisher, 1992; Moon & Wells, 1979). The study
reported here examines the literacy abilities of all
children, at the end of Year 6, who attend a school in
a socially disadvantaged area, to establish the pre-
valence and nature of any literacy difficulties.
The links between social disadvantage, language
and literacy skills
A US Department of Education (2001) analysis
indicated that 46% of children entering kindergarten
came from family backgrounds with one or more
factors that might affect their skills and knowledge.
The risk factors included were living in a single-
parent household, living in poverty, having a mother
with low education, and coming from a non-English
speaking background. The performance of children
with one risk factor lagged behind that of their
Correspondence: Barbara Dodd, Level 6 Ned Hanlon Building, Royal Brisbane and Women’s Hospital, Herston, QLD 4029, Australia. Tel: þ61 7 3636 4011.
Fax: þ61 7 3636 1769. E-mail: [email protected]
Advances in Speech–Language Pathology, June 2007; 9(2): 181 – 190
ISSN 1441-7049 print/ISSN 1742-9528 online ª The Speech Pathology Association of Australia Limited
Published by Informa UK Ltd.
DOI: 10.1080/14417040600970598
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non-disadvantaged peers on assessments of both
reading and mathematics. Nearly half the children
with multiple risk factors performed in the lowest
quartile, typically not knowing letter names or being
aware of sound-letter associations. Similar results
have been reported for children across the primary
school years, for a range of language and literacy
skills, in both the USA and UK (Burt, Holm, &
Dodd, 1999; Duncan & Seymour, 2000; Hecht,
Burgess, Torgesen, Wagner, & Rashotte, 2000;
Locke et al., 2002). Locke et al. (2002) found that
the spoken language abilities of preschool children
reared in poverty were significantly below those of
the general population, despite the children’s cogni-
tive abilities being comparable. They concluded that
these children may be at risk for delayed develop-
ment of written language skills, which could in
turn affect overall academic progress. Duncan and
Seymour (2000) reported that children entering
school in areas of low socio-economic status (SES)
showed a delay in word recognition tasks. This
finding confirmed previous research indicating that
children from low SES backgrounds had delayed
phonological awareness and literacy development,
in comparison with high SES age-matched peers
(Bowey, 1995; Raz & Bryant, 1990).
Parents and family provide a framework that allows
the child to learn (Fisher, 1992). Preschool children
observe their caregivers’ functional and recreational
interaction with print. The home environment deter-
mines attitudes about literacy and may optimize or
minimize learning. Consequently, children begin
school with very different experiences and attitudes
about print (Moon & Wells, 1979). Some find literacy
work in the first year of school a clarification of what
they already know, while others struggle with minimal
knowledge of print and poor phonological awareness.
Adams (1994) argues that some children can therefore
be expected to learn more slowly and to experience
greater frustration. Statistics from the US Department
of Education (2001) indicate that at school entry,
children from disadvantaged backgrounds are more
likely to have poorer health, to be less socially adept and
to have low motivation to learn. From their first literacy
lesson, they are disadvantaged. The disadvantage
experienced during the first year of school can have
long-term educational implications. For example,
Jefferis, Power and Hertzman (2002) longitudinally
investigated the effect of social class and birthweight on
the cognitive trajectories and educational attainment
(including literacy) of nearly 11,000 children born in
1958. Participants were assessed at 7, 11, 16 and 33
years. The results showed a strong influence of social
class through to adulthood.
Literacy development and the links with phonological
awareness skills
The positive link between literacy development and
phonological awareness (PA) skills has been long
established (Bryant, MacLean, Bradley, &
Crossland, 1990; Hatcher & Hulme, 1999; Høien,
Lundberg, Stanovich, & Bjaalid, 1995; Stahl &
Murray, 1994). Both Høien et al. (1995) and
Hatcher and Hulme (1999) found that it was
possible to split phonological awareness skills into
independent factors—namely syllable level skills,
onset-rime skills and phoneme level skills—and that
phoneme manipulation skills best predicted the
acquisition of literacy. Duncan and Seymour
(2000) stated that letter-sound knowledge—a pho-
neme level task—is an important pre-requisite for
development through three stages of literacy acquisi-
tion: the logographic stage, the alphabetic stage and
the orthographic phase. They argued that the
logographic and alphabetic stages develop in tandem,
before leading on to the orthographic phase, with
letter-sound knowledge essential to the development
of the first two processes. In contrast, Frith (1985)
argued that letter-sound knowledge is not involved in
the logographic phase of reading, and only develops
during the alphabetic phase. Both agree that letter-
sound knowledge is essential for the development of
literacy acquisition, as is phonological awareness.
The two skills allow children to decode words they
have never read before, and to invent spellings for
words (Gillon & Dodd, 2005). Share (1995) argued
that early literacy activities at home (e.g., shared
reading with parents and writing shopping lists),
combined with instruction at school, provide specific
information about phoneme-grapheme relationships
that promotes ‘‘self-teaching’’ in reading.
Literacy development and the links with language
comprehension
The role of reading comprehension is receiving
increasing research attention, since some children
who fail to acquire adequate literacy have phonolo-
gical awareness skills within normal limits (Catts,
Adlof, & Ellis Weismer, 2006). Bishop and Adams
(1990) concluded that although expressive phonolo-
gical skills play a part in the development of literacy
skills, ‘‘the importance of phonological processing
may have been previously overstated’’ (p. 1046).
Their findings indicated that it is language abilities
that exert major influence on reading progress.
Recent studies suggest that reading comprehension
is correlated with spoken language comprehension
(Catts et al., 2006). Some children, despite having
adequate phonological awareness skills, fail to
acquire literacy because they have poor comprehen-
sion, which seems to be due to semantic difficulties
in both spoken and written modalities (Nation &
Snowling, 2000).
Hogan, Catts and Little (2005) reported that while
phonological awareness in kindergarten predicts
word reading 2 years later, it looses its predictive
power once children are older. Current research
therefore suggests that there is a need to identify
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children who are failing to acquire literacy in terms of
their sub-skills. Some children are poor decoders
because they have difficulty with phonological
processing (Hogan et al., 2005). Other children
may have poor comprehension of written text despite
intact phonological processing skills. Catts et al.
(2006) therefore suggested that the best way to
classify poor readers was not on reading comprehen-
sion alone but on children’s strengths and weak-
nesses in word recognition and spoken language
comprehension.
Teaching approach and the development
of literacy
Although many primary school teachers use an
eclectic approach to literacy instruction, teaching
reading has been characterized as following one of
two basic approaches. Current teaching in Australia
predominantly follows a ‘‘whole language’’ approach
where children are immersed in print to gain
exposure to a wide variety of relevant and appro-
priate texts (National Inquiry into the Teaching of
Literacy, 2006). They are expected to abstract the
alphabetic principle without explicit teaching that
involves breaking down words into syllables and
phonemes. In contrast, the phonics approach teaches
children sound-letter correspondences that allow
them to read unknown regularly spelled words
because they have learned the reasonably systematic
relationship between spoken and written words.
Supporters of the phonics approach argue that whole
language is associated with a high level of failure to
acquire literacy skills that allow children to access the
curriculum and particularly disadvantages children
from socially deprived backgrounds (Hempenstall,
2002). The literacy levels of Australian school-
children, however, are reported to be high. The
2000 Program for International Student Assessment
(PISA) evaluated 15 year-old children’s ability to
understand texts in order to achieve goals, develop
knowledge and use literacy effectively in society.
Lockan, Greenwood and Cresswell (2001) reported
that Australian children performed better than those
from many countries in Europe, the Americas and
Asia. Finland was the only country whose children
performed better.
The research reviewed raises some questions. To
what extent are children from a socially deprived
background disadvantaged in the acquisition of
literacy in comparison to their peers in non-socially
disadvantaged areas? Are children who have poor
literacy levels a homogeneous group in that they all
lack understanding of the alphabetic principle, an
essential skill for developing adequate literacy? The
final question addresses an important practical issue
in assessing large numbers of children by class
teachers. Most literacy research involves extensive
individual testing that would be inappropriate for
classroom teachers because it is time consuming and
expensive. Is there a cost-effective way of screening
whole classes to identify those children in need of
intervention before they commence secondary
school? The study reported here investigated these
questions. It was hypothesized that:
1. Children, at the end of Year 6, attending a
primary school in an area of high social
disadvantage in Queensland, would per-
form less well than the standardization sample
for a reading assessment and a spelling
assessment, both normed on Queensland
populations.
2. Children performing more than 1 standard
deviation below the mean of the standardiza-
tion samples on all tests would be a hetero-
geneous group in terms of phonological
awareness, letter-sound matching and quali-
tative analyses of reading and writing.
3. The whole-class Non-word Spelling assess-
ment used would prove reliable and valid in
identifying children with literacy difficulties.
Method
Participants
The study assessed all children (n¼ 112) enrolled in
Year 6 at a school in a socially disadvantaged area in
Queensland using measures taken from subtests of
assessments standardized on children from the same
state, and commonly used by clinicians or teachers.
Children were assessed by their teachers and
experienced paediatric speech and language patholo-
gists. The school was located in an area that had
been identified by Education Queensland as being
an area of low socio-economic status (SES). The
SES of all Queensland schools is based on census
data collected by the Australian Bureau of Statistics
and school principals are informed of their catch-
ment area’s school status. Students were prima-
rily instructed in literacy using whole language.
This was determined by teacher report and at
an in-service session for teachers taught by the
researchers.
The 112 children were in their fourth term of their
6th year in school. There were 53 (47.3%) boys and
59 (52.7%) girls, aged between 10 years 11 months
and 12 years 1 month, the mean age of the group
being 11 years 5 months (SD 3.6 months), with
English being the first language of all the children in
the study. Nine of the children included in the study,
who were receiving mainstream education, had been
ascertained under Education Queensland guidelines
as autistic spectrum disorder. Students ascertained
under the category of intellectual impairment, who
were enrolled in the school’s special education unit,
were excluded. None of the children were currently
receiving intervention for a specific speech or
language difficulty.
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Procedure and materials
The reading and spelling whole class assessments
were administered by the Support Teacher Learning
Difficulties and the Deputy Principal in order to
maintain consistency of presentation. The assess-
ments’ manuals indicate that they were standardized
on children representing all socio-economic back-
grounds.
Reading assessment. All children were assessed in
whole class groups. Their reading was assessed using
the Test of Reading for Inferential Comprehension-TRIC
(Murphy, 2003) since this assessment was recently
standardized on Queensland children. The TRIC
comprises of five factual texts (one for each year level
from Year 3 to Year 7) with an accompanying
response sheet. These expository texts are devel-
opmentally ordered. Students are required to read
the text and then answer seven multiple choice
questions and complete four written responses. They
are able to refer back to the text throughout the test.
Secret Weapon was the text for Year 6. Students were
given a score of one for a correct response and zero
for an incorrect response. Correct responses for both
multiple choice and written responses were tallied
and scores were compared to the mean of 8.2
(standard deviation 1.6) as per the manual. At this
point, any child whose score was more than one
standard deviation below the mean was referred for
further assessment to the school’s leaning support
teacher.
Non-word spelling. Children’s spelling was assessed
by the Non-word Spelling test of the Queensland
University Inventory of Literacy (QUIL) (Dodd,
Oerlemans, MacCormack, & Holm, 1996). This
assessment has been standardized on Queensland
children and requires the application of phonological
awareness skills as well as knowledge of letter-sound
correspondence and spelling rules. Words from the
non-word Spelling test were given to each class
group by the support teacher learning difficulties, for
consistency of presentation.
A non-word spelling was correct if the student had
written a word that represented the pronunciation on
the tape. A score of one was given for a correct
response and zero for an incorrect response. The
total number of correct responses was added to give a
raw score and this was converted to a standard score
using the table for Year 6 students in the QUIL
manual. Standard scores were then used to deter-
mine if further testing was required.
Those children who fell more than one standard
deviation below the mean on the Non-word Spelling
task were subsequently assessed individually on four
PA subtests from the QUIL plus a letter-sound
knowledge task. Thirty-five students performed
below the set criterion and were individually assessed
at school by a speech-language pathologist, support
teacher learning difficulties or teacher aide. Another
35 children (the control group) who performed
within normal limits on the non-word spelling test,
matched for class and gender, were also assessed.
The phonological awareness tasks were:
. Syllable Segmentation. In this task students
were required to analyse words into their
component syllable structure and count the
number of syllables (e.g., How many parts in
candlestick? can/dle/stick).
. Spoken Rhyme Recognition. In this task the
students were required to listen to and make
judgements about the phonological similarity
of word pairs (e.g., Do shell and bell rhyme?).
. Phoneme Segmentation. In this task the
students were required to identify and count
the individual sounds (up to five) in words
presented orally (e.g., the word stamp has five
sounds).
. Phoneme Manipulation. In this task the
students were required to identify a given
sound within a word, remove the sound from
the word and then say the new word (e.g., belt
without the /t/ sounds like bell).
. The letter recognition task is one used regularly
by teachers in schools. Twenty-four conso-
nants, six single vowels and 22 vowel diagraphs
were presented individually to each student.
Students were required to say the sound that
corresponded with that letter.
Reliability
Twelve children were reassessed in a group on the
reading comprehension (TRIC) and Non-word
Spelling assessment 2 months after initial assess-
ment. The results showed a high correlation between
the raw scores at the first and second assessments
for both tasks (TRIC correlation¼ 0.821, p¼ 0.001;
non-word spelling correlation¼ 0.910, p5 0.001).
Repeated measures t-tests showed no significant
difference between the two assessments (TRIC
t(11)¼ 1.318, p¼ 0.214; non-word spelling t(11)¼0.220, p¼ 0.830).
Statistical analysis
The data were analysed in three ways. The first set
of analyses compared the study sample against the
standardization samples, while a qualitative analysis
explored the type of errors made on the non-word
spelling test. The second analysis compared good
and poor spellers (as determined by performance on
the non-word spelling test) on a range of tasks that
measure abilities thought to underlie literacy using a
multivariate analysis of variance. The third set of
analyses evaluated the non-word spelling test as a
screener for literacy difficulties, using a regression
analysis to determine the number of children with
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literacy difficulties correctly identified by the non-
word spelling test.
Results
Comparison of study population and norms
The mean overall score achieved on the TRIC by the
Year 6 group was 6.4 (SD 2.0), as compared to the
standardization population’s mean score of 8.2 (SD
1.6). A one sample t-test, comparing the standar-
dized data and results of the children participating
in the study was significant (t(df 111)¼ 9.352, p50.001), indicating poorer performance by the study
sample. Figure 1 suggests that the children’s group
performance does not reflect the normal curve. This
was confirmed by a nonparametric test (one-sample
Kolmogorov-Smirnov Test¼ 1.581, p5 0.02). The
group’s performance on the TRIC was positively
skewed, suggesting that while many children per-
formed close to the standardized population mean, a
subgroup performed poorly, pulling down the study
sample’s mean score.
Inspection of the two sections of the TRIC
revealed that children performed better on the
multiple choice questions (mean score 5.4 (1.4) out
of 7) than in the section requiring them to write a
sentence (mean score of 1.0 (1.01) out of 4). These
data suggest that children from disadvantaged social
background performed poorly when required to
write answers. For example, in answer to the
question (examples include children’s errors):
‘‘Can the boomerang be used more than once?’’
one child wrote ‘‘yes the boomerang can be used to
cut done fruit from trees. And to catch animals’’. In
answer to the question ‘‘What do you think is the
aborigines opinion of the boomerang?’’ a student
wrote ‘‘it is there main wepon and it is the funnest
and deadliest’’. Another question ‘‘Which type of
boomerang do you think would be used to catch a
wallaby?’’ elicited the written response ‘‘The retern
bommerang because if it reterns and it has blood
on it it tells you that you have hit the animal you
sore’’.
The mean overall raw score on the QUIL’s non-
word spelling test for the Year 6 class was 12.9 (5.0)
out of a possible 24. The normative population’s
mean score was 16 (4.0). A one sample t-test was
significant (t(df 111)¼ 6.534, p5 0.001). Figure 2
suggests that the class showed a normal distribution
and this was confirmed by a nonparametric test (one-
sample Kolmogorov-Smirnov Test¼ 0.699, p¼0.712, NS).
To investigate the nature of the errors being made
in the non-word spelling test, the children’s spelling
errors were scored in three additional ways. In one
analysis the children’s ability to represent the correct
number of syllables in words was assessed. Examples
of errors are: stipdiken for strimperdiction (omits one
syllable), clonderlee for clondly (adds a syllable),
damhop for dramplehoffer (omits two syllables) were
each counted as one error. The mean correct score
for syllable representation was 22.9 (1.9) out of 24
words, indicating that the children were, in general,
representing the number of syllables in words
reasonably accurately. The second analysis found
that the number of consonants represented correctly
was 92.7% (SD 6.5), suggesting that the children’s
ability to represent consonants as graphemes was
very good. A similar count of vowels showed that the
number of vowels represented plausibly to be 83.1%
(SD 11.4). A paired t-test showed that children
performed better on consonants than vowels
(t(111)¼ 14.255, p5 0.001). That is, children’s pri-
mary difficulty when inventing spellings for non-
words appeared to be in selecting plausible spelling
choices to represent vowels.
Comparison of abilities assumed to underlie literacy
Two groups of children, selected according to their
performance on the non-word spelling test, were
compared on a range of measures. Thirty-five children
who scored less than a standard score of 7 (raw score of
10 or less) were compared with a group of 35 children
who had a standard score of 7 or above (raw score of
11 or more). A multivariate analysis of variance
explored the abilities associated with good and poor
non-word spelling. There was a significant difference
in the performance of the groups (F(11, 58)¼ 10.702,
p5 0.001), indicating poorer performance across
tasks by children who performed poorly on the
Non-word Spelling task. Table I lists the variables
included in the analyses. Given that the groups
were selected in terms of their performance on the
Non-word Spelling test, it is not surprising that
all measures derived from their performance on
that assessment differed significantly between the
groups.Figure 1. Performance on the TRIC (n¼112) with fitted normal
curve.
Literacy and social disadvantage 185
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Evaluation of whole class non-word
spelling assessment
A stepwise discriminant analysis was also carried out
on data from these 70 children in their two groups:
one group who scored within normal limits on the
non-word spelling task and one group that per-
formed below the normal range. Discriminant
analysis was used to assess whether group member-
ship, determined by the non-word spelling test,
predicted performance on other measures of literacy.
The dependent variable was, then, grouping and the
independent variables were the QUIL’s syllable
segmentation, rhyme recognition phoneme segmen-
tation and phoneme manipulation subtests as well
as the TRIC and letter knowledge assessments.
After two steps, only two variables were left in the
analyses: rhyme recognition and phoneme manip-
ulation (Wilks’ lambda 0.748, F (2,67)¼ 11.270,
p5 0.001). The scores from these two tasks form
the canonical discriminant function that reflects the
greatest difference between the two groups. Table II
presents the classification results. Overall, the dis-
criminant analysis (based on the QUIL, TRIC and
letter recognition scores) classified 74.3% of cases in
Figure 2. Performance on the non-word spelling test (n¼112) with fitted normal curve.
Table I. Comparison of groups of good and poor non-word spellers, from the same class, on spelling, phonological awareness and reading
measures.
Mean Correct (SD)
Variable F(1,70) Significance Poor Good
Non-word Spelling Measures
Accuracy 109.60 p50.001 7.14 (2.8) 16.03 (4.2)
Syllable representation 17.52 p50.001 21.49 (2.8) 23.54 (0.95)
Per cent vowels correct 21.81 p50.001 72.4 (13.1) 85.83 (10.9)
Per cent consonants correct 33.18 p50.001 86.08 (7.1) 95.38 (6.4)
Phonological Awareness
Syllable segmentation 0.76 p¼0.387 NS 9.57 (2.6) 10.06 (2.01)
Rhyme recognition 5.74 p50.025 10.71 (1.6) 11.43 (0.8)
Phoneme segmentation 0.57 p¼0.455 NS 7.17 (3.1) 7.69 (2.6)
Phoneme manipulation 16.94 p50.001 7.14 (1.9) 8.7 (1.2)
Text
TRIC 2.16 p¼0.15 NS 5.89 (1.9) 6.63 (2.3)
Letter Knowledge 8.83 p50.01 39.69 (4.7) 43.29 (5.4)
*Consonants 3.650 p¼ 0.06 NS 22.2 (1.7) 22.9 (1.4)
*Vowels 3.263 p¼ 0.08 NS 4.06 (1.1) 4.57 (1.3)
*Digraphs 6.421 p50.025 13.43 (3.8) 15.8 (4.1)
*Additional one way ANOVAs investigated the components of letter knowledge scores.
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the same way as the groupings based on non-word
spelling performance. The table shows that 18 out of
70 children were classified differently: 12 children
had poor non-word spelling but adequate phonolo-
gical awareness skills; and six children had good
non-word spelling ability but poor phonological
awareness skills.
A qualitative analysis of the raw data of those
18 children was carried out to account for the
mismatch in categorization. Twelve children were
‘‘false positives’’ i.e., they scored poorly on the non-
word spelling test but within normal limits on the
phonological awareness tasks. A comparison of these
false positive participants and 12 matched children
who performed well on both non-word spelling and
phonological awareness indicated that there was a
significant difference in their vowel recognition
scores on the letter recognition test, with a trend
for poor digraph recognition (see Table III).
A comparison of spelling patterns used by children
who were false negatives (good non-word spelling
and poor phonological awareness) and children who
scored poorly on both sets of measures suggested
that the ‘‘false negatives’’ may have relied on visual
memory to do the task. They seemed more likely to
include real words in their invented spellings (e.g.,
doorf for dorf, beartelephone for beartelfome, shocktiple
for soptiple, shuts for suts). In contrast the children
with both poor non-word spelling and phonological
awareness were less likely to include real words
making errors (e.g., droph for dorf, wobe for wump,
elimeb for elinarm, drphofer for dramplehoffer). This
observation should be treated cautiously because
only six participants were involved in each group.
Discussion
The non-word spelling and reading comprehension
abilities of all children (n¼ 112) in Year 6 who
attended a school in a socio-economically disadvan-
taged area, were assessed on standardized measures
administered to whole classes. The results indicated
that the group means for both reading and spelling
were below that of the standardization populations.
Children revealed to have difficulties (n¼ 35) were
given follow-up assessments of phonological aware-
ness and letter sound knowledge. A group of controls
(n¼ 35) who were performing within normal limits
and were matched for class and sex was also
assessed. The group of children identified as
performing poorly on the non-word spelling test
was heterogeneous. Some had poor phonological
awareness skills, some had limited sound-letter
correspondence knowledge and some children had
problems with both skills. The non-word spelling test
was a cost-time efficient assessment method that
resulted in few false-negative identifications (i.e.,
children who were classified as not having a difficulty
even though further testing indicated phonological
awareness difficulties).
Comparison of study population and norms
On the TRIC (Murphy, 2003), the children’s mean
score was significantly poorer than the standardiza-
tion mean. While they scored well on the multiple
choice questions, as a group the children performed
poorly in the section requiring them to write a
sentence in answer to a specific question. This
finding cannot be attributed to question difficulty.
Standardization of the TRIC, using Rasch metho-
dology, showed that questions in the multiple choice
section were not necessarily easier than short answer
questions. There are a number of other possible
explanations for the findings. The task may have
been unfamiliar and the children unsure of the task
requirements. They may have had difficulty under-
standing the demands of the question. For example
some students failed to completely answer questions
that had two parts (e.g., ‘‘What do you think is the
Aborigine’s opinion of the boomerang? Give a reason
for your answer’’).
Alternatively, the children may have been dis-
advantaged by their language skills as suggested by
Catts et al. (2006). For example, one question asked
the children to find the sentence that did not belong
in the text. Children performed particularly poorly
on this question, indicating a lack of comprehension
of the text read. Lack of comprehension cannot be
attributed to poor phonological processing ability
because there was no significant difference on the
TRIC between good and poor non-word spellers. If
it were a decoding difficulty that accounted for the
TRIC performance, then a difference would be
expected.
Table II. Classification results from discriminant analysis.
Predicted Group Membership
Poor Good
Original Groups
Count
Poor 23 12
Good 6 29
Percentage
Poor 65.7 34.3
Good 17.1 82.9
Table III. False positives: letter recognition.
False
Positives
(n¼ 12)
Matched
Controls
(n¼12)
F(1,23)
Significance
Consonant
recognition
22.5 23.33 3.09 p¼ 0.093 NS
Vowel recognition 3.75 4.83 7.78 p¼0.011
Digraph
recognition
15.92 18.1 3.74 p¼ 0.066 Trend
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Inferencing ability may explain the results better
than either the decoding of written language or
children’s comprehension of what was required to
answer the questions. The TRIC actively explores
children’s search for meaning. In school, children
require inferencing skills to become independent
learners. Inferencing skills depend on the ability to
use general knowledge and contextual information to
draw assumptions. Some of the children’s answers
simply paraphrased what they had read. This may
indicate that they understood the question but didn’t
know how to answer it.
Performance on the non-word spelling subtest of
the QUIL was significantly poorer than that of the
standardization sample. Qualitative analysis sug-
gested adequate representation of syllables and
consonants but considerably more difficulty with
vowels. Children’s primary difficulty when inventing
spelling for non-words appeared to be in selecting
appropriate representations of vowels. This difficulty
is particularly important in written English since
vowels in English carry a heavy functional load.
Many words in English are discriminated only by
their vowel, e.g., pit, pat, pot, pet, putt, pert, part, peat,
port, pout. Children’s difficulties may stem from the
inconsistent way spoken vowel sounds are repre-
sented in written English. Vowel symbols are
ambiguous in that a particular grapheme or digraph
can represent a different sound according to the
lexical item (e.g., moth, mother, motive; deaf, deal; ball,
ballet, balm) and the same vowel can be represented
in a number of different ways (e.g., paw, pore; pour,
poor). Teaching reading and spelling is consequently
difficult and it seems unlikely that either ‘‘whole
language’’ or ‘‘phonics’’ approaches can solve this
inherent difficulty. Complex spelling rules need to be
abstracted, analogies drawn and specific word
spellings learned by rote (e.g., yacht, unique). That
is, learning to spell words requires integration of both
phonological and orthographic (visual) information.
Comparison of abilities assumed to underlie literacy
Two groups of children, selected according to their
performance on the non-word spelling test, were
compared on a range of measures. Children who
scored below normal limits on the non-word spelling
assessment also performed less well on measures of
rhyme recognition, phoneme manipulation and recog-
nition of vowel digraphs. What is surprising is that the
two groups did not differ on measures of syllable or
phonological segmentation. While the results sug-
gested that poor spellers were good at representing
the number of syllables in words, they scored poorly
on phoneme representation despite their phoneme
segmentation ability. This finding provides evidence
against the idea that poorer spellers are unable to
identify the constituent phonemes of words. It would
seem, however, that they have difficulty assigning
plausible graphemes to phonemes.
Although the sound-letter task showed that the
poor spellers had more difficulty when recognizing
vowel digraphs, their ability to recognize consonants
and simple vowels did not differ from controls.
Inspection of their non-word spelling errors clearly
showed that not all their errors could be explained in
terms of vowel digraph difficulties such as syllable
deletion, cluster reduction and incorrect consonant
digraphs. Taken together, these two findings suggest
that the children may have difficulty applying their
phonological awareness to the task of spelling non-
words. The task requires children to hear the
non-word, correctly discriminate the constituent
phonemes, store the word in short term (phonolo-
gical working) memory, apply phoneme grapheme
correspondence rules and/or knowledge of analogy
and then write the word. Poor performance might,
then, reflect a range of impairments including
hearing loss, auditory processing impairment, mem-
ory constraints, phoneme-grapheme/analogy con-
straints or difficulty writing. The task is a screening
tool, not a differential diagnosis of literacy disability.
Nevertheless, it provides a means of identifying
difficulty with a skill that teachers and students rely
on once children reach secondary school—the ability
to write down unfamiliar words.
Evaluation of the whole class non-word spelling
assessment
Non-word spelling does not, then, simply reflect
phonological awareness skills. It assesses a range of
abilities and is, perhaps, an accurate reflection of
children’s literacy functioning in the classroom.
Nevertheless, a stepwise discriminant analysis of
other literacy measures classified 74.3% of cases in
the same way as the groupings based on non-word
spelling performance. This finding reflects the strong
relationship between non-word and phonological
awareness.
While false positive identifications are acceptable,
the six children who were false negatives are of
concern because they might be overlooked for
intervention. Inspection of these children’s standard
scores on the non-word spelling task revealed all six
children had a standard score of 7 (i.e., the lowest
score that placed them in the normal range).
Children scoring a standard score of 7 should,
perhaps, be considered ‘‘borderline’’ cases that
should be included in further testing to ensure that
no child with literacy difficulties is overlooked.
Interpretation
The study reported had three aims. The first was to
investigate whether children from socially deprived
areas, nearing the end of primary school, had lower
levels of literacy than their more advantaged peers.
Their group means were significantly lower for both
reading and spelling. Just under one-third of children
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were performing below the normal range for non-
word spelling and just over one-third were below the
normal range on the reading assessment. Given the
social and economic consequences attached to low
literacy, these figures are of concern.
The second aim was to investigate the nature of
the underlying difficulties associated with literacy
performance below the normal range on the non-
word spelling test. These results are of particular
interest given the current debate concerning ap-
proaches to literacy instruction. It was surprising that
the children’s ability to segment words into consti-
tuent syllables and phonemes did not differ from
controls, nor did their ability to recognize consonants
and simple vowels. In general, their difficulties
seemed to lie in applying that knowledge (phoneme
manipulation and awareness of rhyme and conse-
quently the ability to use analogy) and in their grasp
of the relationship between speech sounds and vowel
digraphs. It is important to recognize, however, that
the children were not a homogeneous group. Some
children were poor at one set of skills but had
adequate performance on the other, while other
children performed poorly on both sets of skills.
Intervention should be planned to suit the needs of
groups of children with similar difficulties.
The third aim of the investigation was to evaluate
the usefulness of the QUIL’s non-word spelling test
as a screening tool for literacy difficulties. It is a
‘‘whole class’’ assessment, and takes little time to
administer. The results of the discriminant analysis
suggest that it is a valid and reliable first step in the
identification of children with literacy difficulties.
References
Adams, M. (1994). Beginning to read: Thinking and learning about
print. Cambridge, MA: MIT Press.
Bishop, D., & Adams, C. (1990). A prospective study of the
relationship between language impairment, phonological dis-
orders and reading retardation. Journal of Child Psychology &
Psychiatry, 31, 1027 – 1050.
Bowey, J. A. (1995). Socioeconomic status differences in pre-
school phonological sensitivity and first-grade reading achieve-
ment. Journal of Educational Psychology, 87, 476 – 487.
Bryant, P. E., MacLean, M., Bradley, L., & Crossland, J. (1990).
Rhyme and alliteration, phoneme detection and learning to
read. Developmental Psychology, 2, 429 – 438.
Burt, L., Holm, A., & Dodd, B. J. (1999). Phonological awareness
skills of 4-year-old British children: an assessment and
developmental data. International Journal of Language and
Communication Disorders, 34, 311 – 335.
Catts, H., Adlof, S., & Ellis Weismer, S. (2006). Language deficits
in poor comprehenders: A case for the simple view of reading.
Journal of Speech, Language, and Hearing Research, 49, 278 –
294.
Coomber, B. (1997). Literacy, poverty and schooling: Working
against deficit equations. English in Australia, 119(20), 1 – 16.
Dodd, B., & Carr, A. (2003). Young children’s letter-sound
knowledge. Language, Speech, and Hearing Services in Schools,
34, 128 – 137.
Dodd, B., Oerlemans, M., MacCormack, M., & Holm, A. (1996).
The Queensland University inventory of literacy. Brisbane:
University of Queensland.
Duncan, L. G., & Seymour, P. H. K. (2000). Socio-economic
differences in foundation level literacy. British Journal of
Psychology, 91, 145 – 166.
Fisher, R. (1992). Early literacy and the teacher. New York: Hodder
& Stoughton.
Frith, U. (1985). Beneath the surface of developmental dyslexia.
In K. Patterson, J. C. Marshall, & M. Coltheart (Eds.), Surface
dyslexia: Neuropsychological and cognitive studies in phonological
reading (pp. 301 – 330). Hillsdale, NJ: Erlbaum.
Gillon, G., & Dodd, B. (2005). Understanding the relationship
between speech-language impairment and literacy difficulties:
The central role of phonology. In B. Dodd (Ed.), Differential
diagnosis of speech disorder (pp. 289 – 304). London: Whurr.
Hatcher, P. J., & Hulme, C. (1999). Phonemes, rhymes and
intelligence as predictors of children’s responsiveness to
remedial reading instruction: Evidence from a longitudinal
intervention study. Journal of Experimental Child Psychology, 72,
130 – 153.
Hecht, S., Burgess, S., Torgesen, J., Wagner, R., & Rashotte, C.
(2000). Explaining social class differences in growth of reading
skills from beginning kindergarten through fourth-grade. The
role of phonological awareness, rate of access, and print
knowledge. Reading and Writing: An Interdisciplinary Journal,
12, 99 – 127.
Hempenstall, K. (2002). Phonological processing and phonics:
Towards an understanding of their relationship to each other
and to reading development. Australian Journal of Learning
Disabilities, 7, 4 – 29.
High, P. C., LaGasse, L., Becker, S., Ahlgren, I., & Gardner, A.
(2000). Literacy promotion in primary care pediatrics: Can we
make a difference? Pediatrics, 105, 927 – 934.
Hogan, T. P., Catts, H. W., & Little, T. D. (2005). The
relationship between phonological awareness and reading:
Implications for the assessment of phonological awareness.
Language, Speech, and Hearing Services in Schools, 36, 285 –
293.
Høien, T., Lundberg, I., Stanovich, K. E., & Bjaalid, I. (1995).
Components of phonological awareness. Reading and Writing:
An Interdisciplinary Journal, 7, 171 – 188.
Jefferis, B., Power, C., & Hertzman, C. (2002). Birthweight,
childhood socioeconomic environment and cognitive develop-
ment in the 1958 British birth cohort study. British Medical
Journal, 325, 305 – 307.
Leahy, M. M., & Dodd, B. (2002). Why should secondary schools
come second? RCSLT Bulletin, May, 11 – 13.
Lockan, J., Greenwood, L., & Cresswell, J. (2001). How literate
are Australia’s students? The PISA 2000 survey of students
reading, mathematical and scientific literacy skills. Camberwell:
ACER.
Locke, A., Ginsborg, J., & Peers, I. (2002). Development and
disadvantage: Implications for the early years and beyond.
International Journal of Language and Communication Disorders,
37, 3 – 15.
Moon, C., & Wells, G. (1979). The influence of home on learning
to read. Journal of Research in Reading, 2, 53 – 62.
Murphy, J. (2003). The development of a reading test for
inferential comprehension. Unpublished PhD thesis, Univer-
sity of Queensland.
Nation, K., & Snowling, M. J. (2000). Factors influencing
syntactic awareness skills in normal readers and poor compre-
henders. Applied Psycholinguistics, 21, 229 – 241.
National Inquiry into the Teaching of Literacy (2006). Accessed
24 April 2006, available at: http://www.dest.gov.au/sectors/
school_education/policy_initiatives_reviews/key_issues/literacy_
numeracy/national_inquiry/.
Raz, I. S., & Bryant, P. (1990). Social background, phonological
awareness and children’s reading. British Journal of Develop-
mental Psychology, 8, 209 – 225.
Roberts, J. (2004). Jury out on literacy row. The Australian, 22
November.
Share, D. (1995). Phonological recoding and self-teaching: Sine
qua non of reading acquisition. Cognition, 55, 151 – 218.
Literacy and social disadvantage 189
Int J
Spe
ech
Lan
g Pa
thol
Dow
nloa
ded
from
info
rmah
ealth
care
.com
by
Mcg
ill U
nive
rsity
on
11/2
4/14
For
pers
onal
use
onl
y.
Stahl, S. A., & Murray, B. A. (1994). Defining phonological
awareness and its relationship to early reading. Journal of
Educational Psychology, 86, 221 – 234.
United States Department of Education, National Center for
Education Statistics (2001). Entering kindergarten: A portrait of
American children when they begin school: Findings from the
condition of education 2000. Accessed 3 November 2002,
available at: http:/nces.ed.gov.
van Kraayenoord, C. E., & Paris, S. G. (1994). The literacy
challenge: Strategies for early intervention for literacy and
learning for Australian children. The Reading Teacher, 48,
218 – 228.
190 B. McIntosh et al.
Int J
Spe
ech
Lan
g Pa
thol
Dow
nloa
ded
from
info
rmah
ealth
care
.com
by
Mcg
ill U
nive
rsity
on
11/2
4/14
For
pers
onal
use
onl
y.
