Visual and Phonological Coding in Working Memory ...

Visual and Phonological Coding in Working Memory and Orthographic Skills of Deaf Children Using Chilean Sign Language Jesús M. Alvarado Aníbal Puente Valeria Herrera American Annals of the Deaf, Volume 152, Number 5, Winter 2008, pp. 467-479 (Article) Published by Gallaudet University Press DOI: 10.1353/aad.2008.0009

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VISUAL AND PHONOLOGICAL CODING IN WORKING MEMORY AND ORTHOGRAPHIC SKILLS OF DEAF CHILDREN USING CHILEAN SIGN LANGUAGE

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JESÚS M. ALVARADO, ANÍBAL PUENTE, AND VALERIA HERRERA ALVARADO IS A PROFESSOR OF PSYCHOLOGY, DEPARTMENT OF METHODOLOGY OF THE BEHAVIORAL SCIENCES, FACULTY OF PSYCHOLOGY, COMPLUTENSE UNIVERSITY OF MADRID, SPAIN. PUENTE IS A PROFESSOR OF PSYCHOLOGY, DEPARTMENT OF COGNITIVE PROCESSES, FACULTY OF PSYCHOLOGY, COMPLUTENSE UNIVERSITY OF MADRID. ALVARADO AND PUENTE ARE ALSO BOTH RESEARCHERS WITH THE INSTITUTE FOR BIOFUNCTIONAL STUDIES, COMPLUTENSE UNIVERSITY OF MADRID. HERRERA IS AN ASSOCIATE PROFESSOR OF EDUCATION, METROPOLITAN UNIVERSITY OF SCIENCE EDUCATION, SANTIAGO, CHILE.

E A F C H I L D R E N can improve their reading skills by learning to use alternative, visual codes such as fingerspelling. A sample of 28 deaf children between the ages of 7 and 16 years was used as an experimental group and another sample of 15 hearing children of similar age and academic level as a control group. Two experiments were carried out to study the possible interactions between phonological and visual codes and working memory, and to understand the relationships between these codes and reading and orthographic achievement. The results highlight the relationship between dactylic and orthographic coding. Just as phonemeto-grapheme knowledge can facilitate reading for hearing children, fingerspelling-to-grapheme knowledge has the potential to play a similar role for deaf readers.

The present study explores the role of sign language in the development of reading and orthographic abilities within deaf populations. During the last two decades, debate surrounding the relevance of speech-based coding versus visual-based and manual-based coding has increased. Diverse factors have the potential to contribute to deaf people’s poor reading performance, including lack of phonological understanding, reduced working memory (WM) capacity, and coding difficulties (Paul, 1998). While the first two factors are generally cited as the most significant to the reading performance of hearing people (Alegria, 2003), specialists point to the importance of the last two factors (reduced WM capacity and coding dif-

ficulties) for the deaf. Many years ago, teachers of deaf students noticed a striking contrast between these students and hearing children in terms of memory. Marschark and Mayer (1998) suggest that this contrast exists because there is an assumption that deaf individuals do not have available the acoustic, articulatory, or phonological codes that underlie WM in hearing individuals. They further suggest that this raises the question of whether there are alternative language codes that support retention over brief intervals. WM is a system that temporarily holds and manipulates information in a wide range of essential cognitive tasks, including reading. However, WM is not a single system but rather a multiple one: It is simultaneously an attention 467

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VISUAL AND PHONOLOGICAL CODING AND ORTHOGRAPHIC SKILLS controller, the central executive, a phonological loop, and a visuo-spatial sketch pad (Baddeley & Hitch, 1974). The phonological loop can store linguistic information, while the sketch pad stores and manipulates visuo-spatial images. WM is not, therefore, exclusively phonological; it coexists with other codes that are independent of speech coding. With respect to fingerspelling (wherein each alphabetic letter is manually represented by a single, discrete handshape), the visuo-spatial sketch pad could play an especially important role for the signing deaf. There are important differences between visual and auditory memory (Wilson & Emmorey, 1997). Auditory memory is superior at preserving sequential information, while visual memory is better for simultaneous information. An additional difference is that the capacity of WM is very limited and varies substantially across individuals, although the exact capacity of visual memory remains a matter of debate, ranging from 1.5 to 5.0 objects, whereas the phonological memory span fluctuates between 5.0 and 9.0 (Brockmole, Wang, & Irwin, 2002; Cowan, 2001; D. A. Miller, 1956; Vogel & Machizawa, 2004). Wallace and Corballis (1973) examined the WM performance of three groups of study participants: deaf individuals taught with oral speech, deaf individuals taught with sign language, and hearing individuals. Their results demonstrate that orally trained deaf people use both phonological and dactylic codes in WM tasks. On the other hand, deaf individuals taught with sign language made exclusive or preferential use of visual and dactylic codes. Other recent studies have confirmed that the signing deaf whose phonological capacity is limited resort to other types of memory coding. The results regarding the role of phonological codes in reading in deaf popu-

lations are controversial. Some find evidence for the use of speech-based coding (Conrad, 1979; Leybaert & Alegria, 1993; Lichtenstein, 1998; Perfetti & Sandak, 2000), while others find evidence of manually based coding (Bellugi, Klima, & Siple, 1975; Grushkin, 1998; Hanson, 1989, 1991; Klima & Bellugi, 1979; Padden & Hanson, 2000; Padden & Ramsey, 1998; Waters & Doehring, 1990). Treiman and Hirsh-Pasek (1983a) suggested that, given the parallels between fingerspelling and orthography, the deaf could make use of dactylic representations in reading tasks. Fingerspelling is part of signers’ natural lexicon, and it has a direct relationship to the printed Latin alphabet. Therefore, it could act as a tool for deaf signers to convert printed words into dactylic code as they read. The one-toone correspondence between letters and handshapes makes fingerspelling the simplest method for transferring printed words into dactylic code. This correspondence is even more consistent than the correspondence between letters and sounds used by hearing people. In recent years, sign language and reading have again become objects of investigation, with important contributions having been made in the specific fields of reading acquisition and American Sign Language (ASL; Chamberlain & Mayberry, 2000; Hoffmeister, Philip, Costello, & Grass, 1997; Padden & Ramsey, 1998; Strong & Prinz, 1997). All these studies have concluded that sign language skills are significantly correlated with reading skills; moreover, Moores (1970) observed that fingerspelling enables deaf children to interact symbolically with their parents and classmates, while Padden and Ramsey (1998) have observed the relevance of fingerspelling to native signers’ ability to read. They propose that fingerspelling is a mediating tool that

provides a platform for the development of rudimentary phonological coding. Fingerspelling interacts with speechreading and mouthing, reflecting awareness of sound segments. Padden and Ramsey (2000) state that alternatives such as visual and sign coding can be used by deaf readers, and Grushkin (1998, p. 186) goes so far as to argue that “phonological strategies are the least efficient strategies available to readers who are deaf.” In the same line of thought, Izzo (2002) found that students’ reading ability was not significantly correlated with phonemic awareness, but that it was significantly correlated with language ability. Izzo’s results also confirmed that phonemic awareness did not significantly contribute to any variance in the reading ability of students. Given these results, Izzo proposed that phonemic awareness may not play a vital role in the reading development of students who are deaf . . . awareness may neither facilitate nor be necessary for the reading development of readers who are deaf, calling into question its necessary but not sufficient status, suggesting that other strategies may be equally, if not more, effective for some readers. (p. 206)

Haptonstall -Nykaza and Schick (2007) have shown that students are better able to recognize and write printed English words and to fingerspell those words when their training incorporates a more lexicalized style of fingerspelling. They conclude that fingerspelling can serve as a visual phonological bridge, as an aid in decoding English. We obtained similar results with a sample of young deaf individuals whose first language was Chilean Sign Language (LSCh). Age group (children versus adolescents) was found to be an important moderating variable that

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29 graphemes. In Latin American countries, the situation changes depending on dialect. The aim of the present investigation was to examine the influence of sign language and dactylic and phonological code use on deaf students’ ability to remember and recall words, and to understand the role sign language and dactylic and phonological code play in deaf students’ reading development. We first constructed a test that allowed us to identify level of sign language command and then carried out two experiments with a sample of Chilean deaf children. In the first experiment, we investigated the influence of dactylic and phonological codes on deaf and hearing participants in a letter recall task. In the second, we evaluated the roles of visual, dactylic, orthographic, and phonological codes in the recognition of graphemes included in signed words. Specifically, our aims were (a) to ascertain whether novice deaf signers, skilled deaf signers, and hearing individuals use different coding strategies in WM, and to study the effect of similarities within stimuli on memory recall, and (b) to study the relationship between different coding strategies and reading skills in Chilean deaf signers. LSCh Test As no established test exists to measure command of Chilean Sign Language, and in order to maintain the completeness and rigor of the present study, an ad hoc test was designed. The design of this test was overseen by experts and educators skilled in LSCh. Like most sign languages, LSCh has some basic, common units that make up the formational parameters of its signs (shape, location, orientation, and facial or corporal expression). That is to say, every sign has a concrete handshape, a definite location in space, a

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explained a large part of dactylic ability and sign language command. In that study (Puente, Alvarado, & Herrera, 2006), whose sample was made up of native signers, we also observed that skill in LSCh, and therefore its use, was much greater in adolescents than in children. Given that the deaf incorporate and use a greater amount of dactylic code in their communication as their command of sign language increases, sign language could be considered an important moderating variable that, as it promotes the use of dactylic code, facilitates the learning of orthographic codes and, consequently, reading. Nevertheless, Spanish differs from English in certain aspects that should be kept in mind: Spanish is formed by 29 graphemes (2 of which are digraphic) and 24 phonemes classified in abstract categories. The correspondence between graphemes and phonemes is rarely inconsistent, but the phonemegrapheme correspondence is more irregular. The former correspondence means that Spanish is a very transparent language for reading, while the latter indicates that it is less transparent for writing. The orthographic difficulties in Spanish come from three sources: (a) digraphics (such as ll and rr), (b) phonemes that are represented by two or more graphemes (/b/ as b, v, and w), and (c) graphemes that can represent two different phonemes. The hearing reader, who has already mastered spoken Spanish, must master the correspondence between 29 graphemes and 24 categories of phonemes, along with all of the inconsistencies, a process that can raise obstacles for some children. Theoretically, a deaf child could bypass the phoneme-grapheme complexity by using the one-to-one relationship between print and fingerspelling. This is the case in Spain, where deaf students use 29 dactylic codes to represent the

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specific movement, a three-dimensional orientation of the palm of the hand, and several nonmanual components. Thus, a combination of signs forms a sentence, and a change in only one of these parameters can give rise to a change in overall meaning.

Construction of the LSCh Test In order to assure the high content validity of the LSCh test, it was necessary that the signs chosen be representative of and relevant to common language. Two criteria were used in the selection of words for the test: 1. Frequency of use. Signs were chosen from among those most common in daily LSCh. A preliminary sample was composed of 85 signs. 2. Distinction and simplicity. It was required that the signs be simple, that is, that they be formed with a single movement of the hand, and that they be clearly different from one another. A preliminary list of 85 signs was given to eight deaf judges fluent in LSCh. They then determined the appropriateness of each based on the criteria, eliminating 35 signs and approving a final list of 50. The definitive version of the LSCh test consists of a book with 50 images representing the 50 selected signs (see Figure 1 for examples) and an answer sheet on which the examiner records each study participant’s personal information, as well as his or her responses to the 50 stimuli, in two columns: a first column to record the quality of participants’ responses (correct or incorrect) and a second in which to note any further observations by the examiner.

Evaluation of the LSCh Test To test scale dimensionality, an exploratory factor analysis with a principal

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VISUAL AND PHONOLOGICAL CODING AND ORTHOGRAPHIC SKILLS Figure 1

Examples of Signs Used in the LSCh (Chilean Sign Language) Test

the 50th percentile formed the novice signers group (-LSCh). Two experiments were then carried out. Method

Participants The present study was done in Santiago de Chile, at the Jorge Otte Gabler public school for the deaf, which for 10 years has been developing a bilingual educative model (sign language and oral language) with its students. The school serves a deaf population of more than 120 students between the ages of 2 and 18 years, the majority from lower-middle-class families. The school’s teachers and teacher’s aides are either deaf or hearing and fluent in LSCh. Tests were administered to a selection of students who met five strictly applied requirements:

component method was applied to the 50 items of LSCh data. The factor analysis identified a first factor accounting for 27% of the variance and multiple residual factors that could be interpreted as an indication of essential unidimensionality: LSCh ability. Consequently, the LSCh test showed a good reliability level, .85 (Cronbach’s alpha). To evaluate external validity, we tested theoretical prediction as the necessary increase in sign language command with age and academic level. Figure 2 shows the scores of the 28 participants in the LSCh test, sepa-

rated by age and academic grade level. One can observe that LSCh command was greater among participants of a higher age and academic level. Therefore, it can be concluded that sign language command improves as a child’s intellectual ability matures. That is, as the child matures, his or her lexicon and use of formational parameters also develop. The LSCh test was used to separate the deaf participants into two groups, based on their scores. Those whose scores were above the 50th percentile formed the skilled signers group (+LSCh), and those with scores below

1. a hearing loss of at least 80 dB or greater in the better ear 2. a lack of other disabilities (children with disabilities other than hearing loss were excluded) 3. use of LSCh as a first language 4. a fingerspelling knowledge of the names of the letters of the printed alphabet 5. a knowledge of the relationship between each printed letter and its dactylic representation (the students’ teachers were consulted in this regard) A sample of 28 deaf students between the ages of 7 and 16 years was taken (13 boys and 15 girls; mean age = 11.43 years, SD = 2.71). Average hearing level in the best ear, at frequencies of 500, 1000, and 2000 Hz, was greater than 92.5 dB.

Procedure The LSCh test was administered to the study participants individually, in the

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Figure 2

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LSCh standarized

LSCh standarized

Average Score and Standard Deviation in the LSCh (Chilean Sign Language) Test by Age Group (Left Side) and Academic Grade (Right Side)

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-3 Children

Jorge Otte Gabler school itself but in a different room from the students’ usual classrooms. The examination took about 20 minutes. Students participated in the test voluntarily, with parental authorization having been previously confirmed with a written authorization form. During the test, the 50 images representing the previously selected signs were shown one by one. The participant was to look at the image and then articulate its corresponding sign. Responses were marked on the response sheet along with any other observations relevant to the test, such as the use of synonyms, compound signs, or descriptions of the image that would demonstrate the individual’s level of signed vocabulary. Experiment 1: Visual and Phonological Coding in a WM Task The goal of the first experiment was to understand the interactions that occur

Adolescents

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in the WM in a task that requires the use of different types of coding, in order to study which coding methods are used in the codification of words by both the hearing and the deaf. We were especially interested in examining the study participants’ ability to recall sequences of phonetically and visually similar consonants as compared to their ability to recall sequences of dissimilar letters (control sequences). We were also interested in learning whether any different effects existed between the three groups (hearing children, deaf novice signers, and deaf skilled signers).

Participants In addition to the 28 children who had taken part in the development of the LSCh test, Experiment 1 included an additional group of hearing participants. This made for a final sample of 43 individuals between the ages of 6 and 16 years, divided into three groups:

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1. 15 hearing children (average age = 10.60 years, SD = 3.02, students in the 2nd through 8th grades) 2. 13 deaf novice signers (-LSCh; average age = 9.38 years, SD = 2.06, students in the 2nd through 5th grades) 3. 15 deaf skilled signers (+LSCh; average age = 13.19 years, SD = 1.82, students in the 3rd through 8th grades) The hearing group was selected from a public school, with careful attention paid to choosing students whose level of academic performance was average for their age group.

Stimuli The stimuli used in Experiment 1 were the letters of the Spanish alphabet. Three sets of four letters each were constructed, with each set differing from the others in two aspects (phonological and dactylic). The first

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VISUAL AND PHONOLOGICAL CODING AND ORTHOGRAPHIC SKILLS set was composed of four phonologically similar consonants (B-C-P-V), the second of four letters that are dactylically similar in the Chilean dactylic alphabet (M-N-A-T), and the third of four letters with neither phonological nor dactylic similarities (F-G-R-L). This last set of letters served as a control set. The selection and classification of letters was done according to the criteria established by Spanish-speaking linguists and LSCh specialists.

Procedure The letters of each set were presented to the study participants in written form on a computer screen, individually and sequentially for 1 second each, such that the total time allotted per letter was 2 seconds (1 second with the letter visible on the screen, 1 second of blank screen). Once each letter had been presented individually, the complete series of four letters appeared and remained on the screen for 5 seconds. The instructions for this task were given in LSCh to the deaf participants and in writing to the hearing participants: In each test you will see four letters, one after the other. You should observe each of the four letters carefully, and when the word WRITE appears, you must type the letters in the same order that they appeared on the screen. Try as hard as possible not to change the order of the letters, and try to write all the letters that you can remember in 5 seconds.

At the end of the 5 seconds, a new test was run with a new, randomly selected set of letters. Responses were recorded on the computer. Before the experiment was begun, two practice runs were performed with letters that did not appear in the actual test.

Results The average rate of incorrect responses for hearing and deaf study participants (both the +LSCh and –LSCh participants) in this serial order recall test was calculated. We observed that the average number of incorrect responses in the recall of these letter sequences was 1.42 sequences for hearing participants, 2.02 for +LSCh deaf participants, and 2.97 for –LSCh deaf participants. In terms of the three sets of letters used, the highest average number of mistakes was observed with the set of phonologically similar letters (2.58 on average), followed by the control set (2.16 on average) and the set of dactylically similar (visually similar) letters (1.56 on average). The complete set of data obtained is detailed in Table 1. A repeated-measures analysis of variance was performed in order to understand the significance of the differences observed in the average number of incorrect responses in the serial-order recall test in terms of subject group (hearing, +LSCh, and –LSCh) and in terms of the similarity of the letter sets (phonological similarity, visuo-dactylic similarity, and control set). The ANOVA revealed the existence of statistically significant differences both between subject groups (F2, 40 = 7.83, p < .01) and between letter sets

(F2, 80 = 16.66, p < .01). The level of interaction between the two variables (subject group and letter set) was not high enough to be considered statistically significant (F4, 80 = 2.01, ns). The Bonferroni test for post hoc analysis produced several findings: 1. A statistically significant difference was found between the deaf novice signers (–LSCh) and the hearing children (␮d = –1.55, p < .01), and a nearly significant difference between the two groups of deaf participants (␮d= –0.95, p = .06). 2. In terms of the similarity of the letter sets, the differences observed were statistically significant: between the control set and the phonologically similar set (␮d= –0.43, p < .05), between the control set and the dactylically similar set (␮d= 0.61, p < .01), and between the phonologically and dactylically similar sets (␮d= –1.04, p < .01). The negative differences between the phonologically and dactylically similar sets and between the phonologically similar and control sets can be interpreted as a reflection of the interference of phonological coding on WM, while the positive difference between the

Table 1

Experiment 1: Average Number of Incorrect Responses in Serial Order Recall Test Type of letter similarity Phonological

Hearing +LSCh –LSCh Total

Visual

Control

M

SD

M

SD

M

SD

1.67 2.53 3.69 2.58

1.40 1.25 0.48 1.38

1.27 1.33 2.15 1.56

1.49 1.18 0.90 1.26

1.33 2.20 3.08 2.16

1.63 1.32 1.04 1.51

Note. LSCh, Chilean Sign Language.

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Discussion The results show that, on the one hand, there are differences in memory, but only between the hearing individuals and novice signers, and, on the other hand, that there seems to be an interference in serial order recall when the letters in the sequence are phonologically similar, whereas a visuo-spatial similarity (or dactylic code similarity) seems to facilitate memory. What is more, the patterns of interference and facilitation are independent of whether the participants were hearing or deaf, as evidenced by the fact that no interaction was observed between these variables. Similar results in experiments involving deaf signers who used ASL were found by Hanson, Liberman, and Shankweiler (1984). The differences between the reading levels of hearing and deaf individuals could, then, be explained in terms of visual WM capacity. If deaf students use more visual strategies than hearing students for coding words, and if visual WM storage capacity is very limited, then the deaf students’ reading performance should be worse. As people who are profoundly deaf have very limited access to phonology, they must use and develop alternative visual storage mechanisms. Wilson and Emmorey (1997) indicate that in the case of sign language users, WM involves visual or quasi-visual representations, which suggests parallels to the visuo-spatial WM.

Experiment 2: Coding Strategies in the Recognition of Signed Words In Experiment 2, we studied the relationship between different coding strategies and the recognition of graphemes in signed words and reading skills. For this task, study participants were asked to determine whether each of the different representations of words they saw was related or not to the written form of the words presented. Based on their responses, it is possible to determine the characteristics of the representations according to the codes that the signing deaf employ. We also tried to establish a hierarchy of code use. If LSCh skills were of a more visual nature, then it could be expected that those deaf readers most skilled in LSCh would demonstrate a preference for the use of codes and metalinguistic skills based principally on their visual experiences with language.

Participants The participants consisted of the 28 deaf students who passed the LSCh test, divided into two groups according to their level of sign language command (+LSCh and –LSCh).

Procedure For Experiment 2, we made a book with 15 images of simple and high-frequency signs representing the following concepts: mom, teacher, table, car, flowers, milk, doctor, ball, cat, chair, television, tree, girl, house, and dad. We made sure that all the pictures used in the task represented signs known to the study participants. The task consisted of observing the sign, then articulating the sign, and, finally, answering questions related to three experimental set conditions: speechreading, dactylic (handshapes), and

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control set and the dactylically similar set can be interpreted as evidence of dactylic coding’s nature as an aid to WM. According to Cowan (2001), the visual WM can store approximately four elements, precisely the number of letters used in Experiment 1.

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orthographic (printed graphemes). The 15 images were presented in all three experimental set conditions, such that each participant responded to 45 questions. The instructions for this task were given in LSCh: “Observe the image carefully, make the sign, and then say whether the indicated letter forms part of the signed word.” To confirm that the study participants understood the instructions, we did several trial runs before beginning the test. For example, a participant was presented with the image milk, then recognized and articulated its sign. He was then asked to look at the examiner’s lips, and the examiner silently formed the phoneme “L.” The examiner then asked the participant if the word milk was spelled with the letter “L” (speechreading condition set), and finally the participant’s response was recorded. The task continued with the presentation of the same image, in this case milk, and the participant was asked to respond to questions using the dactylic or orthographic condition sets. Each set of experimental conditions is described below. 1. Speechreading. Once the study participant has recognized the image and articulated its corresponding sign, he or she is asked to watch the experimenter’s lips as the experimenter silently forms a phoneme. The participant’s task consists of deciding whether that phoneme is present in the written form of the word presented as a sign. For example, for the sign for the word castle, the phoneme “P” is not part of the word, and the correct response would be NO. Once the response (YES or NO) has been given and recorded, the next question is given using the dactylic condition set.

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In addition to these three conditions sets, we also evaluated the study participants’ residual access capacity for phonological codes. For this evaluation, the experimenter made the sound of a specific phoneme while covering her mouth (in order to eliminate visual cues). The participant’s task consisted of deciding whether the phoneme he or she heard appeared in the word. For example, for the sign for castle, the experimenter made the sound “T,” and the participant was asked whether or not this phoneme appears in the word.

Results The average number of correct responses in the speechreading, dactylic, and orthographic code sets for the two groups of deaf participants (+LSCh and –LSCh) was calculated. It was observed that the +LSCh participants managed the different types of codes easily, obtaining correct response rates of over 80% with speechreading, dactylic codes, and orthographic codes. The novice signers group (–LSCh), on the other hand, while obtaining correct response rates of over 58% with dactylic and orthographic codes, responded correctly only 37% of the time when stimuli were presented with speechreading, a type of coding that provides elements necessary for the segmental analysis of words (see Figure 3).

We then performed a repeatedmeasures ANOVA in order to evaluate the statistical significance of the differences observed between the two groups of deaf participants (+LSCh and –LSCh) in their use of the different codes (speechreading, dactylic codes, and orthographic codes). The analysis revealed that the differences observed were statistically significant, both between subject groups (F1, 26 = 31.63, p < .01) and between code sets (F2, 52 = 8.25, p < .01), and that the interaction between the two variables, subject group and code set, was also statistically significant (F2, 52 = 3.59, p < .05). Therefore, the betterskilled signers used more codes (13.0 on average) than the novice signers did (7.9 on average). What is more, we observed an overall lesser use of

Figure 3

Average Number of Correct Responses on Three Tasks, by Group (+LSCh, Dark Gray; –LSCh, Light Gray)

15

12

Average Scores

2. Dactylic. Using the same stimulus as in the previous condition set, the experimenter presents the study participant with the image of a handshape (fingerspelling) corresponding to a letter of the alphabet. The participant’s task is to decide whether that dactylic code is present in the written form of the word presented in fingerspelling. To continue with the above example, an image of the handshape for the letter “S” is shown to the participant, who must decide whether this letter appears in the word castle. Once the response has been recorded, the next question is given, using the orthographic condition set. 3. Orthographic. Using the same stimulus as in the previous conditions set, the experimenter presents the study participant with an image of a printed letter and asks him to decide whether this letter is present in the written form of the word presented. To continue with the above example, the participant is shown a printed letter “F” and asked to decide whether this letter appears in the word castle.

9

6

3

0 Speechreading

Dactylic

Orthographic

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160 Table 2

Reading Levels and Mean Standardized Scores on the LSCh Test and the Coding Tasks Academic grade 1. Very low 2. Low 3. Medium 4. High

2nd 3rd 5th–6th 7th–8th

Age range (years)

LSCh test

Orthographic coding task

Dactylic coding task

Speechreading coding task

Phonological coding task

7–9 8–10 11–15 12–16

–1.50 –0.47 0.34 0.98

–1.45 –0.57 0.48 0.84

–1.63 –0.38 0.51 0.75

–1.49 –1.11 0.55 0.37

–0.43 0.37 –0.33 0.46

Note. LSCh, Chilean Sign Language.

speechreading strategies (9.0 on average) than of dactylic strategies (11.3 on average) or orthographic strategies (11.0 on average), a difference that, as Figure 3 shows, is much more pronounced among novice signers and results in the interaction between the two variables. We then evaluated the study participants’ capacity to access phonological codes directly by making use of any residual auditory capacity they may have possessed. Given that the sample in this experiment was composed of profoundly deaf individuals, our observations coincided with our expectations that their capacity to access phonological coding directly would be quite limited: The average number of correct responses to the 15 stimuli presented was 0.77 for novice sign-

ers (–LSCh) and 1.00 for skilled signers (+LSCh). A new ANOVA showed that this difference between the two groups of deaf participants was not significant (F1, 26 = 0.08, ns), but that the two groups’ average scores, despite being so low, were significantly higher than zero (F1, 26 = 4.79, p < .05).

Correlation and Regression Analyses We did correlations and multiple linear-regression analyses in order to understand how the previously examined variables were related to reading ability. We defined four reading levels according to study participants’ general academic performance and to the reports of the experts and teachers who collaborated in the selection of the sample of 28 profoundly deaf signers

free of any other disabilities, cognitive or physical. Findings from these analyses are shown in Table 2. Table 2 shows that the major problem in estimating reading ability is the potential contamination of results by age. In order to avoid this type of contamination, partial correlations were calculated controlling for age (see Table 3). As Table 3 shows, the factors most strongly correlated to reading level were dactylic ability and performance on the LSCh test. The strong correlations between orthographic and dactylic abilities illustrate the relevant role of sign language in the development of reading skills. Additionally, the nexus of orthographic and dactylic abilities can be explained by a common memory code. (It should

Table 3

Partial Correlations Between Reading Level, LSCh Command, and the Variables Measured in Experiment 1 (Phonological, Visual, and Control Similarity) and Experiment 2 (Phonological, Speechreading, Orthographic, and Dactylic Tasks), Controlled for Age Reading level Reading level — Phonological task Speechreading task Orthographic task Dactylic task LSCh test Phonological similarity Visual similarity Control similarity Note. LSCh, Chilean Sign Language. **p < .01. *p < .05.

Phonological task

Speechreading task

Orthographic task

Dactylic task

.26 —

.28 .24 —

.45* .26 .30 —

.51** .03 .23 .65** —

LSCh test .55** .23 .05 .45* .61** —

Phonological Visual similarity similarity –.04 –.27 –.03 .19 .19 –.02 —

.15 .16 .22 .39* .44* .25 .06 —

Control similarity .05 –.11 –.02 .28 .21 –.19 .40* .40* —

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VISUAL AND PHONOLOGICAL CODING AND ORTHOGRAPHIC SKILLS be noted that, as shown in Table 3, the correlation between the orthographic task and visual memory coding is similar to the correlation between the dactylic task and visual memory coding.) A multiple regression analysis of reading level was performed. Age, LSCh command (as measured by the LSCh test), and performance level in the three condition sets were chosen as possible explanatory variables. The results show that the significant explanatory variables for reading level are age and LSCh command (see Table 4). The small sample used in the present study could affect the power of effect size, although this problem is less relevant when the effect size, at the population level, is large (Cohen, 1988). Because of this, the unusually high value obtained in the present study (R2 = .84) makes it possible to affirm that a substantial portion of the variance on reading level is accounted for by age and LSCh command. The levels for tolerance (T = .36) and the variance inflation factor (VIF = 2.82) showed that a relationship between age and LSCh command does exist, but that this relation does not represent a problem of colinearity because the tolerance was greater than .10 and the VIF was less than 10.00

Discussion Our results are consistent with the supposition that deaf individuals have superior skills with some visual processing tasks and that they use orthographic coding strategies for reading. Investigating the spelling errors of young deaf children whose primary language was ASL, Padden (1993) concluded that these children attempted to reproduce the overall shape of a word, tending to confuse letters of the same height (e.g., t, d, and b) and those with descenders (e.g., p, q, and

Table 4

Multiple Regression Model for Reading Level Model

R2

B

SE (B)

␤

t

Tolerance

VIF

–2.67 0.21 0.07

.54 .50 .02

.55** .42**

–4.92** 4.32** 3.32**

.36 .36

2.82 2.82

.84 (Constant) Age LSCh test

Note. VIF, variance inflation factor. LSCh, Chilean Sign Language. **p < .01.

g), and to be sensitive to double letters (as in green or gutter). These young deaf spellers only produced letter sequences that are possible within the English spelling system, suggesting sensitivity to orthographic information (Quinn, 1981). The sensitivity of the deaf to the features of printed words is confirmed in the present study, in which a moderate but significant correlation between reading and orthography was found. Still more interesting is the strong correlation found in the study between dactylic and orthographic coding, a result that reinforces Musselman’s conclusion (2000) that sign language and fingerspelling are the obvious candidates for the codification of writing in the deaf. Parasnis and Whitaker (1992) compared the effects of phonological and orthographic similarity on verbal processing. They selected only deaf students who were fluent signers. The study participants were asked to judge whether the two words in a pair rhymed. Word pairs were constructed to be either phonologically or orthographically similar. Overall, the deaf signers scored better on the orthographic tasks than on the phonological tasks. Parasnis and Whitaker consequently suggested that fluent deaf signers primarily use an orthographic strategy. Despite all this evidence, however, some specialists maintain that orthographic coding is less effective than a code based on phonology. Nevertheless, in Table 3 it can be seen that the

correlation between the orthographic task and reading ability is greater than the correlation between the phonological task and reading ability. Additionally, the interference of phonological codes in WM is related to phonological access (see the correlation between phonological similarity and the phonological task). These results support the thesis that phonological strategies are less efficient than visual strategies for profoundly deaf readers (Grushkin, 1998; Izzo, 2002; P. Miller, 2005; Musselman, 2000). General Discussion The main goal of the present study was to help clarify the controversy regarding the role of sign language and fingerspelling skills in teaching deaf students to read. Experiment 1 revealed patterns of interference in the task involving phonologically similar sets of letters for both deaf and hearing study participants, a finding that demonstrates the relevance of phonological coding in the processing of words. Nevertheless, Experiment 2 reveals the strong relationship that exists between fingerspelling development and orthographic development, as well as the relevance of sign language to reading development. We can therefore conclude that both phonological and visual codes are activated in the reading process, and that the latter become more relevant as readers’ auditory difficulties increase. The relationship between phonol-

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into discrete components (Fok, van Hoek, Klima, & Bellugi, 1991). It was reported that the hearing children found the task very difficult, while the deaf children appeared to find it simple. The codification process is very different between deaf and hearing individuals. The hearing codify the alphabet using a verbally based WM and process information sequentially, while the deaf codify dactylic forms by taking advantage of the iconic nature of signs and process information in parallel (Flaherty, 2000). We have observed that command of dactylic code, orthographic coding, and reading ability are strongly correlated with each other, and that all three correlate with age, increasing as age increases, among study participants demonstrating similar levels of command with dactylic and orthographic codes (Hanson, 1986; Hirsh-Pasek, 1987; Ross, 1992). The similarity in the development of dactylic and orthographic code could be explained by the fact that deaf students make use of the handshape-grapheme correspondence rules they acquire as they learn to read. As they develop, deaf students become more sensitive to orthographic structures and learn to segment words. Fingerspelling appears to be the nexus for the acquisition of orthographic structures (Musselman, 2000). The relationship between orthographic and dactylic coding thus becomes a crucial element in the codification of words, given that the deaf students’ lack of auditory capacity makes it necessary for them to establish alternative links that allow them to substitute the phonological contrasts of oral language. Specifically, fingerspelling would provide deaf readers who use sign language with a tool, means, or instrument that would allow them to see the relationships of correspondence between graphemes and phonemes by establishing a relation-

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ogy and reading seems unquestionable in hearing. Nevertheless, in the case of the profoundly deaf, whose access to phonology can only be indirect (Conrad, 1979; J. Locke & V. Locke, 1971; Treiman & Hirsh-Pasek, 1983b), other alternatives of a visual nature play a critical role in the development of reading skills. Dodd (1980) hypothesizes that phonological development is not specific to auditory information, but rather can be derived from visual information and other kinetic cues (such as speechreading). A problem with speechreading does, however, exist: A large number of phonemes cannot be seen in lip movements, and speechreading is, therefore, an ambiguous code (Leybaert & Alegria, 1995). In this sense, Cued Speech and fingerspelling are unambiguous when it comes to establishing equivalency rules between visual (manual) information and printed (written) information. It should be observed that Cued Speech and fingerspelling rely on visual information to make phonology “visible.” In spite of the limitations, deaf people show a consistent preference for visual strategies in memory (Flaherty, 2000; Frumkin & Anisfeld, 1977; J. Locke & V. Locke, 1971; Wallace & Corballis, 1973). Indeed, deaf study participants have been found to outscore their hearing counterparts on a number of visual memory tests (Bellugi et al., 1990; Daneman, Nemeth, Stainton, & Huelsmann, 1995). O’Connor and Hermelin (1973) reported that deaf study participants remembered faces better than hearing participants did. When deaf and hearing Chinese children were presented with pseudo-Chinese characters by means of movement patterns in space, the deaf children were significantly better than their hearing counterparts at remembering, analyzing, and decoding the movement patterns

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ship between graphemes and handshapes, which are more closely related to these readers’ visuo-spatial experiences with sign language. The correlation and regression analyses show that the most important skill for reading level is sign language command, as measured by the LSCh test. The analyses also support and reinforce the notion that sign language facilitates the acquisition of high levels of literacy in a second language. In their longitudinal study, Harris and Beech (1998) found that half of their most highly skilled deaf readers had deaf parents. It should be noted that sign language and spoken language differ radically at the level of morphology and syntax. This implies that, in the case of sign languages, facilitation takes place at a rather abstract level which is by no means equivalent to the level at which spoken languages and their printed forms are related, that is to say, at the phonological level (LaSasso & Davey, 1987). Chamberlain and Mayberry (2000) suggest that the relationship between sign language and reading is largely dependent on the early acquisition of a natural language, which allows for timely development of other cognitive skills, including memory for verbal and nonverbal material. Conrad (1979) found that deaf children with deaf parents read at a level approximately two grades above the average level of a carefully constructed control group of deaf children with hearing parents (see also Hanson, Goodell, & Perfetti, 1991; Marschark, 1993; Prinz & Strong, 1997). Such findings have led some authors to propose that early exposure to sign language plays a positive role in reading comprehension because it provides the child with a first language (in this case, sign language) that can facilitate the processing of some aspects of a second (in this case, oral) language. It must be recognized, however, that deaf and

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VISUAL AND PHONOLOGICAL CODING AND ORTHOGRAPHIC SKILLS hearing parents of deaf children differ not only in terms of the extent of their signing ability but also, for example, in more social and cultural terms, a difference that can determine the academic and personal expectations these parents have concerning their children (Marschark, 1993). Padden and Ramsey (2000) propose the possibility that deaf children with deaf parents perform better because, as a group, they comprise a well-defined participant population with similar demographics, in contrast to the population of deaf children with hearing parents, whose backgrounds are more variable. Therefore, the use and mastery of sign language and fingerspelling are shown to be factors that can notably aid in the learning of orthographic codes and reading skills. Fingerspelling involves the development of skills that enable the deaf to sequence and segment graphemes, which undoubtedly strengthens orthographic understanding and, to a lesser degree, phonological understanding. Strangely, fingerspelling is not currently used to this end; deaf students are not formally taught to use this strategy when learning to read. Teachers of the deaf teach their students as though they were hearing, that is, they do not employ pedagogic or didactic strategies specific to the teaching of the deaf, such as strengthening the use of fingerspelling. Finally, investigations into the causes of poor reading achievement by the deaf have cited numerous factors, the normally low level of phonological development being one of the most significant (Waters & Doehring, 1990). However, phonological development cannot be promoted through the use of speech-based strategies except in the case of those deaf who have residual auditory capacity, previous experience with oral language, or cochlear implants, which facilitate access to cer-

tain forms of speech. The alternatives to speech-based strategies should be visual or manual in nature, such as speechreading, Cued Speech, and fingerspelling. Like others, we defend the use of sign language and fingerspelling (Hanson, 1986; Hirsh-Pasek, 1987; Padden & Ramsey, 2000; Ross, 1992), and we propose that intentional and active practice with visual and dactylic vocabulary would be a great benefit to the deaf in the identification of the letters that make up words, thereby supporting the development of their orthographic skills and, consequently, their reading skills. After all, it must be kept in mind that fingerspelling should not be viewed—as it often is—as a system for supplying words to ideas, concept, and objects that “have no signs” (Padden, 2006). This undermines the status of both signs and fingerspelling as rich sources of vocabulary within the language in crucial aspects such as reading and writing. Fingerspelling is more than the sum of its parts. It is not merely a linear means of representing the orthography; rather, it has taken on a rich symbolic content above and beyond the words themselves (Akamatsu, 1982; Moores, 1970). Acknowledgments The research for the present study was supported by the Agencia Española de Cooperación Iberoamericana, Complutense University of Madrid. We are grateful to the staff and students of the Jorge Otte Gabler public school for the deaf, Santiago de Chile. References Akamatsu, C. (1982). The acquisition of fingerspelling in preschool children. Unpublished doctoral dissertation, University of Rochester, Rochester, NY. Alegria, J. (2003). Deafness and reading. In T. Nunes & P. Bryant (Eds.), Handbook of children’s literacy (pp. 459–489). Dordrecht, Netherlands: Kluwer Academic. Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. A. Bower (Ed.), Recent ad-

vances in learning and motivation: Vol. 8 (pp. 468–667). New York: Academic Press. Bellugi, U., Klima, E., & Siple, P. (1975). Remembering in signs. Cognition, 24, 1–30. Bellugi, U., O’Grady, L., Lillo-Martin, D., O’Grady Hynes, M., Vankoek, K., & Corina, D. (1990). Enhancement of spatial cognition in deaf children. In V. Volterra & C. J. Erting (Eds.), From gesture to language in hearing and deaf children (pp. 278–298). Berlin, Germany: Springer. Brockmole, J. R., Wang, R. F., & Irwin, D. E. (2002). Temporal integration between visual images and visual perceptions. Journal of Experimental Psychology: Human Perception and Performance, 28, 315–334. Chamberlain, C., & Mayberry, R. (2000). Theorizing about the relation between American Sign Language and reading. In C. Chamberlain, J. P. Morford, & R. Mayberry (Eds.), Acquisition of language by eyes (pp. 221–259). London: Erlbaum. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Academic Press Conrad, R. (1979). The deaf school child. London: Harper & Row. Cowan, N. (2001). The magical number four in short-term memory: A reconsideration of mental storage capacity. Behavioural and Brain Sciences, 24, 87–114. Daneman, M., Nemeth, S., Stainton, M., & Huelsmann, K. (1995). Working memory as a predictor of reading achievement in orally educated hearing-impaired children. Volta Review, 97, 225–241. Dodd, B. (1980). The spelling abilities of profoundly prelingually deaf children. In U. Frith (Ed.), Cognitive processes in spelling (pp. 423–440). London: Academic Press. Flaherty, M. (2000). Memory in the deaf: A crosscultural study in English and Japanese. American Annals of the Deaf, 145 (3), 237–243. Fok, A., van Hoek, K., Klima, E., & Bellugi, U. (1991). The interplay between visuo-spatial language and visuo-spatial script. In D. S. Martin (Ed.), Advances in cognition, education, and deafness (pp. 38–58). Washington, DC: Gallaudet University Press. Frumkin, B., & Anisfeld, M. (1977). Semantic and surface codes in the memory of deaf children. Cognitive Psychology, 9, 475–493. Grushkin, D. (1998). Why shouldn’t Sam read? Toward a new paradigm for literacy and the deaf. Journal of Deaf Studies and Deaf Education, 3, 179–204. Hanson, V. L. (1986). Access to spoken language and the acquisition of orthographic structure: Evidence from deaf readers. Quarterly Journal of Experimental Psychology, 38 (A), 193–212. Hanson, V. L. (1989). Phonology and reading: Evidence from profoundly deaf readers. In D. Shankweiler & I. Liberman (Eds.), Phonology and reading disability: Solving

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