2011. Vol.2, No.2, 109-116
Copyright © 2011 SciRes. DOI:10.4236/psych.2011.22018
Morphological Knowledge and Decoding Skills of
M. Diane Clark, Gizelle Gilbert, Melissa L. Anderson
Science of Learning Center on Visual Language and Visual Learning, Washington, DC, USA
Department of Educational Foundations and Research, Gallaudet University, Washington, D.C., USA.
Received January 4th, 2011; revised February 9th, 2011; accepted February 14th, 2011.
Many studies have reported the necessity of phonological awareness to become a skilled reader, citing barriers to
phonological information as the cause for reading difficulties experienced by deaf individuals. In contrast, other
research suggests that phonological awareness is not necessary for reading acquisition, citing the importance of
higher levels of syntactic and semantic knowledge. To determine if deaf students with higher language skills
have better word decoding strategies, students responded to a morphological test, where monomorphemic words
and multimorphemic words were matched to their definitions. Two studies are reported, one focusing on English
placement levels and a second with formal measures of both ASL and English language proficiency. Results in-
dicated that performance on the morphological decoding test was related to language proficiency scores, but not
to phonological awaren e s s scores.
Keywords: Deaf, Reading, Morphology
Research on the reading achievement of deaf individuals in-
dicates that deaf readers tend to lag behind their hearing peers,
with an average reading level equivalent to the fourth grade
(Allen, 1986; Conrad, 1979). Unfortunately, this achievement
gap between deaf and hearing readers has remained fairly stable
over the past 30 to 40 years (e.g. Strong & Prinz, 1997; Mus-
selman, 2000). To explain this issue a number of researchers
have hypothesized the cause of deaf individuals’ reading diffi-
Phonologi cal Awarenes s and Reading Skill
One commonly cited hypothesis suggests that phonological
awareness is required to become a skilled reader (Colin, Mag-
nan, Ecalle, & Leybaert, 2007; Luetke-Stahlman & Nielsen,
2003; Paul, Wang, Trezek, & Luckner, 2009; Perfetti & Sandak,
2000; Wang, Trezek, Luckner, & Paul, 2008). The phonologi-
cal coding deficit hypothesis theorizes that lower reading levels
for prelingually deaf readers are primarily a failure to effec-
tively process written text at the lexical level (e.g., Kelly &
Barac-Cikoja, 2007). The central claim underlying this view is
that, due to a lack of auditory stimulation, prelingually deaf
readers do not develop phonemic awareness (e.g., Charlier &
Leybaert, 2000; Dyer, MacSweeney, Szczerbinski, Green, &
Campbell, 2003; Hanson & Fowler, 1987; Hanson & McGarr,
1989; Miller, 1997, 2006a, 2006b; 2007a; Sutcliffe, Dowker, &
Campbell, 1999; Transler, Leybaert, & Gombert, 1999). In turn,
this problem of ineffective phonological knowledge prevents
rapid and accurate phonological decoding of written words (e.g.,
Leybaert, & Alegria, 1993; Perfetti & Sandak, 2000). As a
consequence, the integration of the meaning of such words into
broader ideas via their structural (syntactic) and semantic proc-
essing is also limited and likely to fail.
Advocating a lexical/phonological coding deficit hypothesis
for the explanation of reading failure in prelingual deaf readers
intuitively makes sense given that specific reading disorders in
hearing readers coincide with marked deficits in the phono-
logical domain (Ehri, Nunes, Stahl, & Willows, 2001b; Frost,
1998; Hulme, Snowling, Caravolas, & Carroll, 2005; Report of
the National Reading Panel, 2000; Snow, Burns & Griffin,
1998; Share, 1995, 2004, 2008; Shaywitz & Shaywitz, 2005;
Troia, 2004; Vellutino, Fletcher, Snowling, & Scanlon, 2004).
Moreover, predictions made by the hypothesis are in accor-
dance with evidence obtained from short-term recall experi-
ments suggesting that better deaf readers tend to recode written
stimuli into a phonological code–as indicated by their sensitiv-
ity to phonological manipulations introduced into the phono-
logical properties of the to-be-recalled written stimuli (letters or
words) (e.g., Conrad, 1979; Hanson, 1982; Hanson, Liberman
& Shankweiler, 1984; Hanson & Lichtenstein, 1990; Harris &
Moreno, 2006; Krakow & Hanson, 1985).
In contrast, some recent lines of research suggest that pho-
nological awareness is not the only route to becoming a skilled
deaf reader (Allen, Clark, del Giudice, Lieberman, Mayberry, et
al., 2009; Izzo, 2002; Miller, 2005a; Miller & Clark, in press).
A project by Izzo (2002), on the comprehension of written ma-
terials, found that deaf college students did not rely on phono-
logical knowledge when reading. Rather, it seemed that skilled
deaf readers relied on other higher-order metacognitive skills to
decode words. Additionally, Schirmer and Williams (2003)
found that highly-skilled deaf readers had more developed
metacognitive abilities than less-skilled deaf readers, suggesting
*Data for this paper was collected with the support of the Gallaudet Re-
search Institute (GRI) Priority Grant Program, a GRI Small Grant to Jona-
than Penny and NSF’s Science of Learning Center on Visual Language and
Visual Learning (VL2) grant number SBE-0541953.Part of this research
was presented at the 2008 Association for Psychological Sciencemeeting in
Chicago, Illinois and the 2009 Association for Psychological Science meet-
ing in San Francisco.
M. D. CLARK ET AL.
a relationship between reading skills and higher-order metacog-
nitive skills. Findings like these, as well as those reported by
Narr (2008), seem to imply that phonology per se does not
enhance reading comprehension in individuals with significant
prelingual hearing losses. A similar conclusion has been drawn
from a systematically conducted large scale meta-analysis of 58
studies (2145 tested individuals) designed to clarify the contri-
bution of prelingually deaf readers’ phonologi- cal processing
skills to their reading comprehension (Mayberry, Del Giudice,
Lieberman, 2011). Findings from this meta-analysis strongly
suggest that phonological coding is not the cause of low read-
ing ability in the deaf population.
Morphological Awareness and Reading Skill
One metacognitive skill that has been found to play a role in
reading achievement is morphological knowledge. The afore-
mentioned research by Izzo (2002) indicated that deaf individu-
als rely on fingerspelling to identify words, suggesting that the
reading abilities of deaf students are accounted for by their
decoding skills at both the letter and morpheme levels. Indeed,
morphology has often been suggested to be important for
learning basic reading skills for both hearing and deaf children.
The morphographic model for word identification identifies
three stages of visual analysis in the decoding of hearing chil-
dren: logographic, alphabetic, and orthographic (Frith, 1985).
The logographic stage involves the use of visual skills, mean-
ingful exposure to print, and word knowledge to supply the
reader with contextual information necessary for word decod-
ing. Visual discrimination is also a key element of the alpha-
betic, or “sounding out,” stage, which relies on phonological
awareness for decoding. The third and final stage is the analysis
of words into larger orthographic units, which Ehri (1992) la-
bels “cipher sight word reading.”
However, it is important to note that these three types of vis-
ual analysis may not apply to readers who lack easy access to
phonology for word decoding. Rather, deaf individuals who
lack access to phonological information may not rely on
“sounding out” for decoding; instead they could use contextual
information and sight word identification. Indeed, Gaustad
(2000) reported that deaf individuals who are unable to recode
to speech primarily use sight word identification to identify
monomorphemic words. Gaustad further theorized that deaf
readers approach reading using three strategies: “1) the intent to
analyze words, 2) well-developed visual skills and segmental
awareness (morphological and orthographic), and 3) experience
with the connections between printed (morphographic) seg-
ments of words and the meanings they encode” (2000, p. 66).
Additionally, she suggests that deaf students first learn to use
morphographic analysis when they are exposed to multimor-
As morphology is visually accessible, it can serve as an al-
ternate strategy to phonology for deaf readers acquiring vo-
cabulary knowledge and higher-order reading skills. In support
of this idea, Ehri (1992) reported that individuals who are
skilled readers of English pay more attention to the visual
composition of words than their phonological composition.
This switch may be due to the finding that phonological re-
coding is a slower process than sight word reading for a reader
who has yet to ma ster the phonologic al system (Ma rslen-Wilson,
Komisarjevsky, Waksler, & Older, 1994). While phonological
recoding is a slow process for these individuals, it is possible to
increase use of the visual channel for word identification by
increasing knowledge of the morphological structure of words.
Indeed, with this knowledge of morphological structure, in-
cluding awareness of negation, tense, and possession, young
deaf children are capable of manipulating basic English text
Decoding is an important component of reading that permits
moving from the printed form to the internal lexicon. The use
of morphology facilitates word decoding in two ways: 1) through
a direct link between orthographic strings and their corre-
sponding lexical meaning, and 2) through the ability to decode
novel mulitmorphemic strings into their individual components
(Gaustad, 2000). The current project sought to investigate if
deaf college students use contextual information present in
multimorphemic low-frequency words to determine their defi-
nitions. As one component of this contextual information, pho-
nological word-decoding strategies were also investigated as
they related to English placement levels.
Research Question and Hypotheses
The first portion of this study investigated whether English
placement levels predict deaf college students’ morphological
and phonological word-decoding strategies.
Hypothesis 1: Deaf students with higher English placement
levels will exhibit increased morphological decoding skills,
demonstrated by higher levels of accuracy on a morphological
Hypothesis 2: Deaf students with higher English placement
levels will exhibit increased phonological decoding skills,
demonstrated by higher levels of accuracy on a phonological
English Placement. A proxy for English fluency was devel-
oped based on the level of English placement assigned to each
student as they matriculated into the university. The four groups
of English placement are as follows: Developmental, Entry
Level, Advanced, and Honors. Placement is determined by the
Degrees of Reading Power exam (DRP), a test designed to
measure students’ strengths and weaknesses in reading. More
importantly, the DRP is designed to measure students’ expertise
in reading under “real life” conditions (Department of Program
Services–Student Assessment Office, 2003). The criterion va-
lidity of the DRP has been established through positive correla-
tions with both the Nelson-Denny Reading Test and ACT
composite scores (Wood, Nemeth, & Brooks, 1985).
Phonological Awareness. Phonological awareness was meas-
ured using the Phoneme Detection Test administered via com-
puter (Koo, Crain, LaSasso, & Eden, 2008). For this test, par-
ticipants are instructed to determine whether a presented word
includes the sound of the letter presented (e.g. Does it have a
/k/?). Prior to beginning the test, each participant completes a
set of four practice trials. Next, the participant is presented
M. D. CLARK ET AL. 111
individually with 30 high-frequency words with multiple or-
thography-to-phonology correspondences, and is required to
identify whether the targeted phoneme is included in each of
the words. Responses were recorded by pressing 1 on the key-
board if the word included the target phoneme or 2 if it did not
have the target phoneme.
Morphological Knowledge. The Guessing Game test was
developed to evaluate deaf individuals’ ability to use morpho-
logical knowledge when identifying words and their meanings.
To test this question, both high and low frequency words
(monomorphemic and multimorphemic words) were selected
from Thorndike and Lorge’s (1972) The Teacher’s Word Book
of 30,000 Words. Twenty-eight words were selected from
Thorndike and Lorge: seven high frequency, monomorphemic
words; seven high frequency, multimorphemic words; seven
low frequency, monomorphemic words; and seven low fre-
quency, multimorphemic words. Participants were presented
with a worksheet in matching format, asked to pair the words
with their definitions, and instructed to use their decoding
strategies with novel words. The name “Guessing Game” was
utilized to encourage participants to engage in the test, rather
than to give up by saying that they did not know the words.
Pilot testing demonstrated that using words with a frequency
of one instance in a million were not decoded above chance
levels within the general college population. Therefore, words
with a frequency between 50 and 99 per million were selected.
These changes lead to above chance responding in the second
pilot test conducted with the new words.
Fifty deaf and hard-of-hearing participants were recruited for
Study 1 by posting flyers at Gallaudet University. There were
19 men (mean age = 21.2 years) and 31 women (mean age =
21.1 years). Eighteen students were people of color, 29 were
European Americans, and three students declined to report their
race. With respect to English placement, 11 students were in
Developmental English, 13 in Entry Level, 14 students in Ad-
vanced, and 12 students in Honors. Two testing sessions were
employed, leading to missing data on some tests.
Participants were given both written instructions and ASL
instructions about the purpose of the study. In addition, students
were made aware that the study consisted of three components:
the Guessing Game; the Phoneme Detection Test; and a back-
ground questionnaire that queried their language background
and previous school experience. Students took all three portions
of the study after reading and signing an informed consent
There were approximately equal numbers of participants in
each of the four English placement levels, as reported above.
Summary statistics for the Phoneme Detection Test, Guessing
Game total number of words correct, Guessing Game total
number of monomorphemic words correct, and Guessing Game
total number of multimorphemic words correct can be seen in
One-way ANOVAs were performed to investigate the impact
of English placement on phonological and morphological de-
coding skills. Four dependent variables were investigated: per-
cent correct on the Phoneme Detection Test, Guessing Game
total number of words correct, Guessing Game total number of
monomorphemic words correct, and Guessing Game total
number of multimorphemic words correct. ANOVA results are
listed in Table 2.
Two of the four variables showed significant differences
between levels of English placement. The total number of
words correct on the Guessing Game was significantly related
to English placement levels, F(3, 28) = 4.83, p = .008, r2 = .34.
As seen in Table 3, LSD post-hocs indicated that students with
Developmental English placement matched significantly fewer
words to their definitions than did those with Honors English
placement, p = .02. Additionally, participants with Entry Level
placement scored significantly lower than those with either
Advanced placement (p = .012) or Honors placement (p = .002).
Additionally, the total number of correct monomorphemic
words on the Guessing Game was significantly related to Eng-
lish placement levels, F (3, 28) = 5.62; p = .004, r2 = .38). LSD
post hocs revealed differences among the group means, with
those in Developmental English scoring significantly lower
than those in Honors English, p = .006. Participants with Entry
Level placement were significantly lower than those with either
Honors (p = .001) or Advanced levels of English placement
(p = .014).
The number of correct multimorphemic words on the Guess-
ing Game was not significantly related to the English placement
levels (p = .078), but the results were in the expected direction.
More importantly, scores on the Phoneme Detection Test were
not significantly related to variation in levels of English place-
Hypothesis 1 stated that Deaf students with higher English
placement levels would exhibit increased morphological de-
coding skills, demonstrated by higher levels of accuracy on the
Guessing Game. The results of Study 1 support this hypothesis,
Descriptive statistics for Study 1.
Measure Mean SD Range
Phoneme Detection Test score 18.71 4.84 11-28
GG: Total Number of Words Correct 10.32 4.78 2-24
GG: Total Number of Multimorphe mic Words Correct 5.68 2.52 1-11
GG: Total Num ber of Monomorphemic Words Correct 4.63 2.72 1-14
M. D. CLARK ET AL.
Summary of ANOVAs comparing levels of English placement levels on the phoneme det ection test and the Guessing Game.
Sum of Squares df Mean Square F p
Between Gr oups 794.167 3 264.722 0.811 0.494
Within Groups 15008.413 46 326.270 PDT: % Correct
Total 15802.580 49
Between Gr oups 100.557 3 33.519 5.615 0.004
Within Groups 167.162 28 5.970
GG: Total Monomorphemic Correct
Total 267.719 31
Between Gr oups 50.349 3 16.783 2.521 0.078
Within Groups 186.370 28 6.656 GG: Tot al Multimorphemic Correct
Total 236.719 31
Between Gr oups 288.449 3 96.150 4.829 0.008
Within Groups 557.551 28 19.913
GG: Total Words W ords Correct
Total 846.000 31
Descriptive statistics for the Guessing Game, split by English place-
Placement n per group GG
Developmental 11 8.7 3.3
Entry Leve l 13 6.9 2.7
Advanced 14 12.4 5.6
Honors 12 14.8 7.3
with students in higher English placements exhibiting better
Although word-decoding strategies did vary significantly with
total number of words correct and total number of monomor-
phemic words correct on the Guessing Game, the total number
of multimorphemic words correct was not significantly related
to English placement levels (p = .078). However it is important
to note that this finding did approach a marginal level of sig-
nificance; given the low statistical power in this project, it is
possible that increasing the number of participants would make
this finding significant. Another possible explanation for the
lack of significance is that multimorphemic words were se-
lected based on English norms. In English those words have a
high frequency of use; however, English words do not map to
ASL signs on a one-to-one basis.
Hypothesis 2 stated that Deaf students with higher English
placement levels would exhibit increased phonological decod-
ing skills, demonstrated by higher levels of accuracy on a pho-
nological awareness task. This hypothesis was not supported, as
English placement levels were not related to scores on the
Phoneme Detection Test. Two issues were identified among the
current sample of participants with respect to the Phoneme
Detection Test. First, the participants had a wide range of cor-
rect responses, from three to 99 percent correct. Second, the
response time to individual items was longer than normal when
compared to hearing participants who have taken the test. This
long response time suggests that participants understood the
task, but struggled to identify which words included the target
phoneme. Even though some of our participants demonstrated
phonological awareness, this knowledge did not predict success
in reading. Similar to Izzo’s (2002) finding, when comprehen-
sion of English is required, phonological awareness did not
relate to success f ul reading performance.
Interestingly, students mentioned using signs as a means of
decoding novel English words. The spontaneous report of “I
don’t know a sign for that” occurred many times while collect-
ing data. Based on these statements, it appears that knowledge
of ASL may guide English decoding.
Two groups of English users could be identified in the data,
those who had used English for more than 15 years and only
recently started using sign and those that reported using both
English and ASL for more than 15 years. Separate analyses of
these two groups found no difference in their phonological
awareness. These groups were self-identified, therefore it is
difficult to know their actual skills in either English or ASL.
Recent work by Morford, Wilkinson, Villwock, Pinar, & Kroll
(2011) found that many individuals who reported that they were
skilled bilinguals did not demonstrate a balance in language
skills when formally tested. Future work is planned to more
carefully investigate the language background of participants to
determine if this finding will apply to those whose first lan-
guage is English in contrast to those who are truly bilingual.
Given these findings, a second study was conducted to specifi-
cally measure the interaction of ASL skills, English word flu-
ency, morphological knowledge, and phonological awareness.
Research Question and Hypotheses
The second portion of this study investigated the role of bi-
lingual ASL/English abilities, morphological knowledge, and
phonological awareness on deaf individuals’ ability to decode
Hypothesis 1: Deaf students with higher levels of bilingual
ability will exhibit increased morphological decoding skills,
demonstrated by higher levels of accuracy on a morphological
Hypothesis 2: Deaf students with higher levels of bilingual
M. D. CLARK ET AL. 113
ability will exhibit increased phonological decoding skills,
demonstrated by higher levels of accuracy on a phonological
Bilingual Abilities. The American Sign Language–Sentence
Reproduction Test (ASL-SRT) was used to evaluate each par-
ticipant’s ASL proficiency. Using an online video interface, the
ASL-SRT presents participants with 36 ASL sentences signed
by a native signer (Hauser, Paludneviciene, Supalla, & Bavelier,
2008). The participant is required to view each video clip and
then reproduce the sentence exactly as it was presented. The
participants’ reproduction is also recorded through the online
video interface. These sentences progressively increase in
length as well as syntactic, thematic, and morphemic complex-
ity. Inter-rater reliability of the ASL-SRT has been reported to
be r = .83, p < .01(Hauser et al.).
Reading skills were measured using the Woodcock Johnson
III Test of Achievement (WJ III ACH) Reading Fluency. This
subtest requires participants to read and comprehend simple
sentences rapidly. It contains 98 written English “yes/no” ques-
Raw scores from the WJ III ACH Reading Fluency Subtest
and the ASL-SRT were transformed into a combined Bilingual
Abilities score. These raw scores were converted first to
z-scores and then transformed to T scores. Next, multiplying
the two T scores together created a combined Bilingual Ability
Phonological Awareness. Phonological awareness was again
measured using the Phoneme Detection Test (PDT) adminis-
tered via computer (Koo et al., 2008). For a detailed explana-
tion of the PDT, refer to the Measures section in Study 1.
Morphological Knowledge. The Guessing Game test was
again used to evaluate deaf individuals’ ability to use morpho-
logical knowledge when identifying words and their meanings.
The same twenty-eight words were utilized from Thorndike and
Lorge: seven high frequency, monomorphemic words; seven
high frequency, multimorphemic words; seven low frequency,
monomorphemic words; and seven low frequency, multimor-
Fifty-one deaf and hard-of-hearing participants were re-
cruited for Study 2 by posting flyers at Gallaudet University.
There were 15 men (mean age = 20.3 years) and 36 women
(mean age = 20.7 years). Twenty-two participants identified as
people of color, while 29 identified as European American.
Two participants reported mild hearing loss, 10 moderate, 16
severe, and 22 profoundly Deaf with one participant declining
to report their hearing loss. With respect to language preference,
43 participants reported a preference for ASL, 7 for Spoken
English, and 1 for both ASL and Spoken English.
Participants were given written instructions and information
about the purpose of the current study. In addition, students
were made aware that the study consisted of five components:
the WJ III ACH Reading Fluency subtest; the ASL-SRT; the
Guessing Game; the Phoneme Detection Test; and a back-
ground questionnaire that queried their language background
and previous school experience. Students took all five portions
of the study after reading and signing an informed consent
Summary statistics for the WJ III ACH Reading Fluency
subtest, ASL-SRT, Phoneme Detection Test, and Guessing
Game are li s ted in Table 4.
Pearson correlations indicated that the Bilingual Abilities
score was significantly related to the Guessing Game total score,
r = .34, p = .01, with greater bilingual abilities related to in-
creased morphological knowledge. Moreover, the Bilingual
Abilities score was significantly positively related to Guessing
Game monomorphemic and multimorphemic words correct (r
= .30, p = 0.03; r = .35, p = .01).
However, the Bilingual Abilities score was not significantly
correlated with the PDT, r = .10, suggesting little relationship
between bilingual abilities and phonological awareness. It is
also important to note that Deaf participants in the current study
had significantly slower reaction time (mean = 1 755) on this
measure than prior research with hearing participants (mean = 1
145 msec), t(50) = 4.97, p = .000.
Less-skilled and more-skilled readers were compared on the
PDT using an independent t-test to ascertain the contribution of
phonological awareness on fluent reading ability. Results indi-
cate less-skilled readers (i.e., those in the lowest tertile of all
participants (10th grade level and below; n = 17)) and more-
skilled readers (i.e., those in the top tertile (graduate level and
above; n = 19)) did not perform significantly differently on the
PDT, t(32) = –0.88, p = .39. However, it is important to note
that the variability in phonological awareness differed between
these groups. Indeed, the more-skilled readers showed greater
variability in phonological awareness when compared to less-
skilled readers, with interquartile ranges of 23.00 and 10.83,
Hypothesis 1 predicted that Deaf students with higher levels
of bilingual ability in ASL and English would exhibit increased
morphological decoding skills. This hypothesis was supported
by the results of Study 2, as shown by the strong positive cor-
relations between the measure of morphological knowledge and
the Bilingual Abilities variable. Hypothesis 2 predicted that
Deaf students with higher levels of bilingual ability would ex-
hibit increased phonological decoding skills. This hypothesis
was not supported, as shown by the non-significant correlation
between the measure of phonological awareness and the Bilin-
gual Abilities variable. It was also observed that Deaf individu-
als required significantly more time to respond to items on the
phonological awareness task when compared to past research
Descriptive statistics for Study 2.
Measure Mean Range
WJ III ACH Reading Fluency: Grade Equivalent 13.13 4.4-18.8
ASL-SRT: Total Score 23.55 7-33
Guessing Gam e: Total Score 11.7 2-22
PDT: Perce nt Correct 58.8 0-89.3
M. D. CLARK ET AL.
on hearing subjects, suggesting that deaf individuals may ap-
proach the task differently than their hearing peers.
Moreover, less-skilled and more-skilled readers did not show
any significant difference in their ability to use phonological
knowledge, with the 50th percentile of both groups scoring at
chance levels. While there was no significant difference in
phonological awareness between reading skill levels, Deaf in-
dividuals showed variability in their scores of phonological
awareness, with less-skilled readers exhibiting a smaller range
of phonological abilities compared to more-skilled readers. The
greater variability of scores in the more-skilled reading group
allowed for more participants in this group to demonstrate
phonological awareness. Some of the more-skilled readers ex-
hibited high levels of phonological awareness.
Results from these studies do not support the link between
phonological awareness, reading, and decoding skills in “real
life” situations across the deaf population. However, the results
do show that some deaf students are able to perform tasks that
require phonological knowledge and therefore support prior
research suggesting that deaf students do have phonological
awareness (Conrad, 1979; Hanson, 1982; Hanson, Liberman &
Shankweiler, 1984; Hanson & Lichtenstein, 1990; Harris &
Moreno, 2006; Krakow & Hanson, 1985). One possible expla-
nation of these results is the findings of Mayberry et al.’s (2011)
meta-analysis where when phonological awareness was re-
ported in previous studies, it explained less than 15% of the
variance. This effect size suggests that one can find statistical
significance but not practical significance.
In this line, Koo et al. (2008) found that both deaf individuals
who use cued speech and those who label themselves as oral
deaf showed phonological awareness on the PDT. These find-
ings were in contrast to the Koo et al. deaf participants who
were signers and did not show an effect of phonological
awareness of the PDT. It is important to note that all of Koo et
al.’s participants were skilled readers as determined by a
screening evaluation. Therefore, the findings from the current
study, as well as those from Koo et al., suggest that there are
multiple pathways that deaf readers take to become skilled
Despite hypotheses that higher reading levels correlate to
better phonological awareness skills (Paul et al., 2009), the
current study did not find support for this idea. Even though
phonological awareness has not been found to be sufficient for
a deaf person to become a skilled reader (see Allen et al., 2009),
many still hold that phonology is necessary to become a skilled
reader (Paul et al., 2009).
Alternative pathways are suggested by recent findings on
ASL/English bilingualism that have found that native signing
of ASL significantly predicted bilingual abilities in ASL and
written English, implying that having control of ASL as a na-
tive language may act as a bridge to stronger reading abilities
(Freel, Clark, Anderson, Gilbert, Musyoka, & Hauser, 2011).
Previous research conducted by Vernon and Koh (1970),
Strong and Prinz (1997), and Stuckless and Birch (1966)
showed that deaf children of deaf parents perform significantly
better on reading comprehension tests than deaf children of
hearing parents. Therefore, deaf children of deaf parents, who
are raised in an ASL environment and develop ASL as a native
language, have been found to possess stronger reading skills
than deaf children raised by hearing parents, who do not de-
velop ASL as a native language. Freel et al.’s work supports the
idea that establishing ASL as a complete first language can
foster enhanced literacy in written English as a second language.
Similarly, Allen, Hwang, and Stansky (2009) found that deaf
individuals’ ASL scores explained 68% of the variance in
The current study, as well as Izzo (2002), suggests that for
tasks requiring comprehension and decoding skills, visual
strategies lead to more effective results. Here it appears that
phonological awareness may develop as a result of effective
English reading abilities. Future work with young deaf readers
can help determine if this progression–from more visually
based morphographic knowledge to later phonological knowl-
edge–occurs for these readers. Both logographic and orthor-
graphic information is fully accessible to young deaf learners
and would help scaffold ASL knowledge to printed English.
Later, familiarity with the printed English words could help
build phonological skills. Further research is warranted to in-
vestigate the use of ASL as a first language as a means for sec-
ond-language a c q uisition.
Clearly, this work is focused on a sample of deaf individuals
who are bilingual. As such, it cannot explore all possible path-
ways that are used by deaf people to become skilled readers.
Even so, the current study suggests a ‘Yes’ response to the Paul
et al. (2009) question: “Are there skilled deaf readers for whom
phonological coding is a rarely used skill?” (p. 348). In terms of,
“Why is this the case?”, one can only propose that it was not
found to be a necessary or helpful route to reading. With re-
gards to “difference[s] between skilled and unskilled deaf read-
ers,” these results suggest that some deaf skilled and unskilled
readers DO develop phonological awareness. This finding may
be linked to their early language choices, as some of the par-
ticipants in these studies acquired ASL later in life. Regardless,
one can identify both skilled and unskilled deaf readers, with
and without, phonological awareness. Future research needs to
more clearly evaluate why this is the case. On the other hand, it
is possible that younger deaf readers do rely on phonological
information and the alphabetic principle, a finding that was not
captured with the current sample of college students. Current
research is investigating this question in young children aged
three to five years to further clarify these issues.
In conclusion, it appears that phonological awareness is not
necessary for the development of deaf individuals’ English
reading skills and that many deaf individuals utilize morpho-
logical strategies that provide direct access to meaning. These
results, in conjunction with that of Freel et al. (2011) and Allen
et al. (2009), suggest that Deaf students with higher levels of
bilingual ability in ASL and English exhibit increased morpho-
logical decoding skills. Aligning with this work, Gaustad (2000)
emphasized the use of visual strategies as a means of learning
to read in what is termed the morphological reading approach.
Here the focus is geared toward the development of vocabulary
and text comprehension with the general goal of increasing
metacognitive and metalinguistic skills. Therefore, as suggested
by Gaustad, morphographic analysis could be used as an effec-
tive strategy in the classroom when teaching young deaf readers
how to “break the code” of English.
M. D. CLARK ET AL. 115
The following undergraduates were involved in data collec-
tion; Jason Begue, Brianne Weber, Jonathan Penny, Amanda
Krieger, Vivienne Schroeder. In addition, Selina Agyen, the
Database Manager of VL2 was also involved in data collection
and data management. We would also like to thank the partici-
pants for their time and effort.
Allen, T. (1986). Patterns of academic achievement among hearing
impaired students: 1974-1983. In A. Schildroth & M. Karchmer
(Eds.), Deaf Children in America (pp. 161-206). San Diego, CA: Lit-
Allen, T. E., Clark, M. D., del Giudice, A., Koo, D., Lieberman, A.,
Mayberry, R., & Miller, P. (2009). Phonology and reading: A re-
sponse to Wang, Trezek, Luckner, and Paul. American Annals of the
Deaf, 145, 338-345. doi:10.1353/aad.0.0109
Allen, T. E., Hwang, Y., & Stansky, A. (2009). Measuring factors that
predict deaf students’ reading abilities: The VL2 Toolkit-Project de-
sign and early findings. An nu al M ee ti ng of t he Association of College
Educators of the Deaf and Hard of Hearing , New Orleans.
Charlier, B. L., & Leybaert, J. (2000). The rhyming skills of deaf chil-
dren educated with phonetically augmented speechreading. The
Quarterly Journal of Experimental Psychology, 53, 349-375.
Colin, S., Magnan, A., Ecalle, J., & Leybaert, J. (2007). Relation be-
tween deaf children’s phonological skills in kindergarten and word
recognition performance in first grade. The Journal of Child Psy-
chology and Psychiatry, 48, 139-146.
Conrad, R. (1979). The deaf school child: Language and cognitive
function. London: Harper Row.
Department of Program Services – Student Assessment Office. (2003).
Degrees of reading power (DRP) interpretation guide. Retrieved
Dyer, A., MacSweeney, M., Szczerbinski, M., Green, L., & Campbell,
R. (2003). Predictors of reading delay in Deaf adolescents: The rela-
tive contributions of rapid automatized naming speed and phono-
logical awareness and decoding. Journal of Deaf Studies and Deaf
Education, 8, 215-229. doi:10.1093/deafed/eng012
Ehri, L. (1992). Reconceptualizing the development of sight word
reading and its relationship to recoding. In P. Gough, L. Ehri, & R.
Treiman (Eds.), Reading acquisition (pp. 107-143). Hillsdale, NJ:
Ehri, L., Nunes, R. S., Stahl, S., & Willows, D. (2001b). Systematic
phonics instruction helps students learn to read: Evidence from the
National Reading Panel’s meta-analysis. Review of Educational Re-
search, 71, 393-447. doi:10.3102/00346543071003393
Freel, B. L., Clark, M. D., Anderson, M. L ., Gilbert , G. L., Musyoka , M.
M., & Hauser, P. C. (2011). Deaf individuals’ bilingual abilities:
American Sign Language proficiency, reading skills, and family
characteristics. Psychology, 2, 18-23. doi:10.4236/psych.2011.21003
Frith, U. (1985). Beneath the surface of developmental dyslexia. In K.
Patterson, J. Marshall, & M. Coltheart (Eds.), Surface dyslexia:
Neurological and cognitive studies of phonological reading (pp. 301-
330). Hillsdale, NJ: Lawrence Erlbaum.
Frost, R. (1998). Toward a strong phonological theory of visual word
recognition: True issues and false trails. Psychological Bulletin, 123,
Gaustad, M. (2000). Morphographic analysis as a word identification
strategy for deaf readers. Journal of Deaf Studies and Deaf Educa-
tion, 5, 61-80. doi:10.1093/deafed/5.1.60
Hanson, V. L. (1982). Short-term recall by deaf signers of American
Sign Language: Implications for order recall. Journal of Experimen-
tal Psychology: Learning, Memory, and Recognition, 8, 572-583.
Hanson, V. L., & Fowler, C. A. (1987). Phonological coding in word
reading: Evidence from hearing and deaf readers. Memory and Cog-
nition, 15, 199-207. doi:10.3758/BF03197717
Hanson, V. L., Liberman, I. Y., & Shankweiler, D. (1984). Linguistic
coding by deaf children in relation to beginning reading success.
Journal of Experimental Child Psycho logy, 37, 378-393.
Hanson, V. L., & Lichtenstein, E. H. (1990). Short-term memory cod-
ing by deaf signers: The primary language coding hypothesis recon-
sidered. Cognitive Psychology, 22, 211-224.
Hanson, V. L., & McGarr, N. S. (1989). Rhyme generation by deaf
adults. Journal of Speech and Hearing Resea r c h , 3 2, 2-11.
Harris, M., & Moreno, C. (2006). Speech reading and learning to read:
A comparison of 8-year-old profoundly Deaf children with good and
poor reading ability. Journal of Deaf Studies and Deaf Education, 11,
Hauser, P., Paludneviciene, R., Supalla, T., & Bavelier, D. (2008).
American Sign Language–Sentence Reproduction Test: Develop-
ment & implications. In R.M. de Quadros (Ed.), Sign languages:
Spinning and unraveling the past, present and future (pp. 160-172).
Petrópolis, Brazil: Editora Arara Azul.
Hulme, C., Snowling, M., Caravolas, M., & Carroll, J. (2005). Phono-
logical skills are (probably) one cause of success in learning to read:
A comment on Castles and Coltheart. Scientific Studies of Reading, 9,
Izzo, A. (2002). Phonemic awareness and reading ability: An investiga-
tion with young readers who are deaf. American Annals of the Deaf,
Kelly, L. P., & Barac-Cikoja, D. (2007). The comprehension of skilled
deaf readers: The roles of word recognition and other potentially
critical aspects of competence. In K. Cain & J. Oakhill (Eds.), Chil-
dren’s comprehension problems in oral and written language (pp.
244-280). New York: The Guilford Press.
Koo, D., Crain, K., LaSasso, C., & Eden, G. (2008). Phonological
awareness and short-term memory in hearing and deaf individuals of
deaf individuals of different communication backgrounds. Annals of
the New York Academy o f Science, 1145, 83-99.
Krakow, R. A., & Hanson, V. L. (1985). Deaf signers and serial recall
for visual modality: Memory for signs, fingerspelling, and print.
Memory and Cognition, 13, 265-272. doi:10.3758/BF03197689
Leybaert, J., & Alegria, J. (1993). Is word processing involuntary in
deaf children? British Journal of Developmental Psychology, 11,
Luetke-Stahlman, B., & Nielsen, D. C. (2003). The contribution of
phonological awareness and receptive and expressive English to the
reading ability of deaf students with varying degrees of exposure to
accurate English. Journal of Deaf Studies and Deaf Education, 8,
Marschark, M., & Harris, M. (1996). Success and failure in learning to
read: The special case of deaf children. In C. Coronoldi & J. Oakhill
(Eds.), Reading comprehension difficulties: Process and intervention
(pp. 279-300). Hillsdale, NJ: Lawrence Erlbaum.
Marslen-Wilson, W., Komisarjevsky, T., Waksler, R., & Older, L.
(1994). Morphology and meaning in the English mental lexicon. Psy-
chology Review, 101, 3-33. doi:10.1037/0033-295X.101.1.3
Mayberry, R. I., del Guidice, A. A., & Lieberman, A. M. (2011). Read-
ing achievement in relation to phonological coding and awareness in
deaf readers: A meta-analysis. Journal of Deaf Studies and Deaf
Education, 16, 164-188. doi:10.1093/deafed/enq049
Miller, P. (1997). The effect of communication mode on the develop-
ment of phonemic awareness in prelingually deaf students. Journal
of Speech, Language & Hearing Research, 40, 1151-1163.
Miller, P. (2005a). Reading comprehension and its relation to the qual-
M. D. CLARK ET AL.
ity of functional hearing: Evidence from readers with different func-
tional hearing abilities. American Annals of th e D ea f, 150, 305-323.
Miller, P. (2006a). What the word recognition skills of prelingually
deafened readers tell about their reading comprehension problems.
Journal of Development and Physical Disabiliti es, 18, 91-121.
Miller, P. (2006b). What the processing of real words and pseudo-
homophones tell about the development of orthographic knowledge
in prelingually deafened individuals. Journal of Deaf Studies and
Deaf Education, 11, 21-38. doi:10.1093/deafed/enj001
Miller, P. (2007a). The role of phonology in the word decoding skills of
poor readers: Evidence from individuals with prelingual deafness or
diagnosed dyslexia. Journal of Developmental and Physical Dis-
abilities, 19, 385-408. doi:10.1007/s10882-007-9057-5
Miller, P., & Clark, M. D. (in press). Journal of Developmental and
Morford, J. P., Wilkinson, E., Villwock, A., Pinar, P., & Kroll, J. F.
(2011). When deaf signers read English: Do written words activate
their sign translations? Cognition, 118, 286-292.
Musselman, C. (2000). How do deaf children who can’t hear learn to
read an alphabetic script? A review of the literature on reading and
deafness. Journal of Deaf S tu d i es and Deaf Education, 5, 11-31.
Narr, R. F. (2008). Phonological awareness and decoding in deaf/
hard-of-hearing students who use Visual Phonics. Journal of Deaf
Studies and Deaf Education, 13, 405-416.
Paul, P. V., Wang, Y., Trezek, B. J., & Luckner, J. L. (2009).
Phonology is necessary, but not sufficient: A rejoinder. American
Annals of the Deaf, 154, 346-356. doi:10.1353/aad.0.0110
Perfetti, C. A., & Sandak, R. (2000). Reading optimally builds on spo-
ken language: Implications for deaf readers. Journal of Deaf Studies
and Deaf Education, 5, 32-50.
Report of the National Reading Panel (2000). Teaching children to read:
An evidence-based assessment of the scientific research literature on
reading and its implications for reading instruction (NIH Publication
No. 00-4769). Washington, DC: U.S. Government Printing Office.
Schirmer, B. R., & Williams, C. (2003). Approaches to teaching read-
ing. In M. Marschark & P.E. Spencer (Eds.), Oxford handbook of
deaf studies, language, and education (pp. 110-122). New York:
Oxford University Press.
Share, D. L. (1995). Phonological recoding and self-teaching: Sine qua
non of reading acquisition. Cognition, 55, 151-218.
Share, D. L. (2004). Orthographic learning at a glance: On the time
course and developmental onset of self-teaching. Journal of Experi-
mental Child Psychology, 87, 267-298.
Share, D. L. (2008). On the anglocentricities of current reading research
and practice: The perils of overreliance on an “outlier” orthography.
Psychological Bulletin, 134, 584-615.
Shaywitz, S. E., & Shaywitz B. A. (2005). Dyslexia (specific reading
disability). Biological Psychiatry, 57, 1301-1309.
Snow, C. E., Burns, M. S., & Griffin, P. (1998). Preventing reading
difficulties in young children. Washington, DC: National Academic
Strong, M., & Prinz, P. M. (1997). A study of the relationship between
American Sign Language and English literacy. Journal of Deaf
Studies and Deaf Education, 2, 37-46.
Stuckless, E. R., & Birch, J. W. (1966). The influence of early manual
communication on the linguistic development of deaf children.
American Annals of the Deaf, 142, 71-79.
Sutcliffe, A., Dowker, A., & Campbell, R. (1999). Deaf children’s
spelling: Does it show sensitivity to phonology? Journal of Deaf
Studies and Deaf Education, 4, 111-123.
Thorndike, E. L., & Lorge, I. (1972). The teacher’s word book of
30,000 words. New York: Teachers College Press.
Transler, C., Leybaert, J., & Gombert, J. (2005). Do deaf children use
phonological syllables as reading units? Journal of Deaf Studies and
Deaf Education, 4, 124-143. doi:10.1093/deafed/4.2.124
Troia, G. (2004). Phonological processing and its influence on literacy
learning. In C. Stone, E. Silliman, B. Ehren, & K. Appel (Eds.),
Handbook of language and literacy: Development and disorders (pp.
271-301). New York: The Guilford Press.
Vellutino, F. R., Fletcher, J. M., Snowling, M. J., & Scanlon, D. M.
(2004). Specific reading disability (dyslexia): What have we learned
in the past four decades? Journal of Child Psychology and Psychia-
try, 45, 2-40. doi:10.1046/j.0021-9630.2003.00305.x
Vernon, M., & Koh, S. D. (1970). Early manual communication and
deaf children’s achievement. American Annals of the Deaf, 115,
Wang, Y., Trezek, B. J., Luckner, J., & Paul, P. V. (2008). The role of
phonology and phonologically related skills in reading instruction for
students who are deaf or hard of hearing. American Annals of the
Deaf, 153, 396-407. doi:10.1353/aad.0.0061
Wood, P. H., Nemeth, J. S., & Brooks, C. C. (1985). Criterion-related
validity of the Degrees of Reading Power Test (Form CP-1A). Edu-
cational and Psychological Measurement, 45, 965-969.