Examination of the spelling skills of middle school students who are deaf

The Volta Review, Volume 114(1), Spring/Summer 2014, 29–54

Examination of the SpellingSkills of Middle School StudentsWho Are Deaf and Hard ofHearing

Lisa Bowers, Ph.D., CCC-SLP; Jillian H. McCarthy, Ph.D., CCC-SLP;Ilsa Schwarz, Ph.D., CCC-SLP; Hannah Dostal, Ph.D.; Kimberly Wolbers,Ph.D.

Children who are deaf and hard of hearing (DHH) often struggle with spelling,which can have a negative effect on their written expression. Recent research hasshown that linguistic analyses of spelling errors can be used to identify areas of needand guide remediation for spelling success. However, this research has not beenconducted with children who are DHH. This study evaluated the spelling errors ofchildren who are DHH using two measures: the Spelling Sensitivity Score (SSS) anda multi-linguistic coding system (MLC). The coding systems did not provideequivalent results in that the MLC system provided a more sensitive analysis to thespelling errors the children produced. The analyses showed that children who areDHH are most likely to make errors that demonstrate phonological, semantic, ormorphological knowledge deficits.

Introduction

Spelling is a complex linguistic skill that requires a child to understandand integrate knowledge of the structure, orthography, and vocabulary of alanguage (Catts & Kamhi, 1999; Kamhi & Hinton, 2000; Masterson & Apel,2000). Mature, successful spellers can access their linguistic knowledge (i.e.,understanding of language form and content) and, when faced with words

Lisa Bowers, Ph.D., CCC-SLP, is Assistant Professor at the University of Arkansas inFayetteville. Jillian H. McCarthy, Ph.D., CCC-SLP, and Ilsa Schwarz, Ph.D., CCC-SLP, are atUniversity of Tennessee Health Science Center in Knoxville. Hannah Dostal, Ph.D., is at theUniversity of Connecticut in Storrs. Kimberly Wolbers, Ph.D., is at University of Tennessee–Knoxville. Correspondence concerning this manuscript may be addressed to Dr. Bowers [email protected].

Examination of the Spelling Skills of Middle School Students 29

they do not know, choose from a variety of strategies to support theirspelling attempts (Masterson & Apel, 2000). In contrast, poor spellers arelimited in their ability to access different strategies to accurately and

efficiently spell words. Children who are deaf and hard of hearing (DHH)are often poor spellers (Alamargot, Lambert, Thebault, & Dansac, 2007;Sutcliffe, Dowker, & Campbell, 1999) with more phonological (Aaron,Keetay, Boyd, Palmatier, & Wacks, 1998; Allman, 2002) and morphological

(Leybaert & Alegria, 1995; Olson & Caramazza, 2004) errors than childrenwith typical hearing. In addition, students with a hearing loss oftencomplete written work that is difficult to read due to various factors,

including numerous errors in spelling (Alamargot et al., 2007; Mayer, 2010).In order to instruct children who are DHH on appropriate strategies toincrease their spelling accuracy, it would be useful to identify individualstrengths and weaknesses in their linguistic knowledge.

Children who are DHH comprise a heterogeneous population with uniquecharacteristics that present obstacles to teachers who want their students toachieve effective and accurate written expression (Wolbers, Dostal, & Bowers,

2012). Although the literature on spelling skills of children who are DHH islimited, research with typically developing children without hearing lossdemonstrates that there are a number of linguistic processes critical to spelling

development. These include phonological awareness (PA), orthographicpattern awareness (OPA), morphological awareness (MA), and semanticawareness (SA). The ability to visualize words that do not follow typical

phonological or orthographic patterns is also a necessary skill, categorized asthe ability to use mental graphemic representations (MGRs) (Apel, 2009, 2011;Apel & Masterson, 2001). Spelling error categories, with definitions andexamples, are included in Table 1.

In general, the importance of phonological and orthographic knowledge hasdominated spelling theory and spelling research (Catts & Kamhi, 1999;Cunningham, Perry, & Stanovich, 2001; Ehri, 2000). However, recent studies

have demonstrated the contribution of morphological and semantic under-standing as well as the importance of stored mental images of words to accuratespelling (Apel & Masterson, 2001; Berninger, Cartwright, Yates, Swanson, &

Abbott, 1994; Denckla & Cutting, 1999; Wasowicz, 2007). These relationshipshave usually been explored by analyzing the spelling errors made by childrenwho are developing typically. In contrast, the spelling patterns of DHHchildren are not well understood. What is known is that students who are DHH

have less access to phonological information and the structure of the Englishlanguage (Alamargot et al., 2007; Antia, Reed, & Kreimeyer, 2005; Kluwin &Kelly, 1992). However, there is still much to learn about the relationship

between linguistic processes known to support the development of spellingskills for students who are DHH.

30 Bowers, McCarthy, Schwarz, Dostal, & Wolbers

Spelling Errors of Children Who Are Deaf and Hard of Hearing

Additional research is needed in order to identify the types of errors that aremost frequently represented in the spelling of children who are DHH. Thisstudy was designed to explore their spelling errors and determine if they signalunique problems with specific linguistic processes or stored mental represen-tations of words. Each of the linguistic processes described below wereidentified through previous research as important to spelling.

Table 1. Spelling error linguistic categories, definitions, defining characteristics,and examples

Spelling ErrorLinguistic Category Definitions, Defining Characteristics, and Examples

Phonological errors(PA)

� Errors of SOUND� omission or addition of phonemes not in the word� maximally different incorrect representations of vowels

(‘‘o’’ for ‘‘a’’; ‘‘u’’ for ‘‘e’’)� all letter reversals

Orthographic PatternAwareness Errors(OPA)

� Errors of regular PATTERNS� incorrect consonant substitutions (d/t; n/m; s/tch)� rules for combining letters (‘‘kry’’ for ‘‘cry’’; ‘‘jrum’’ for

‘‘drum’’)� patterns that govern spelling (‘‘ran’’ for ‘‘rain’’; ‘‘lader’’

for ‘‘ladder’’)� positional constraints on spelling patterns (‘‘ckow’’ for

‘‘cow’’)Mental Graphemic

RepresentationErrors (MGR)

� Errors of IRREGULARITY (you just have to memorizethe word)� correct ‘‘phonetic’’ spelling of non-phonetic words

(‘‘cidy’’ for ‘‘city’’)� incorrect spelling of unstressed syllables (‘‘buckit’’ for

‘‘bucket’’)� incorrect vowels preceding –ng, r, l (‘‘reng’’ for ‘‘rang’’;

‘‘whil’’ for ‘‘wheel’’)� incorrect spelling for repeated attempts (stopd, stopt,

stoppd)Morphological

Awareness Errors(MA)

� Errors of MODIFICATION (i.e., prefix, suffix, tensechange)� incorrect use of morphemes� wrong tense is represented (‘‘walk’’ for ‘‘walked’’)

Semantic AwarenessErrors (SA)

� Errors of MEANING� suffix modification errors represent another word (‘‘fry’’

for ‘‘fried’’; ‘‘drive’’ for ‘‘drivers’’)� wrong word used (‘‘dog’’ for ‘‘car’’)


Phonological Awareness (PA)

Spelling has been referred to as a ‘‘window to the knowledge childrenpossess about phonology’’ (Strattman & Hodson, 2005, p. 166). PA includesone’s ability to think about, talk about, and manipulate speech sounds. It isdemonstrated through skills in attending to sound units (e.g., soundidentification and rhyming), and manipulating the sounds in words (e.g.,elision, segmentation, and blending). Research has documented that childrenwith typical hearing employ phonological skills to spell, such as phonemeidentification and sound blending (Adams, 1990; Kamhi, Catts, Mauer, Apel, &Gentry, 1988; Larkin & Snowling, 2006), make connections between speechsounds and spelling, and use their understanding of sound-letter relationshipsin early spelling attempts (Cataldo & Ellis, 1988; Muter, Hulme, Snowling, &Taylor, 1997; Treiman & Bourassa, 2000). Students who are DHH often exhibitphonological awareness errors in spelling and regardless of whether they usecochlear implants or hearing aids they generally exhibit more phonologicalerrors than students with typical hearing, including errors that are phoneticallyimplausible (e.g., ‘‘timfe’’ for ‘‘time’’ or ‘‘exctiend’’ for ‘‘excited’’) (Geers &Hayes, 2011). It is hypothesized that this may be related to their limited access tothe acoustic signal (Leybaert & Alegria, 1995; Sutcliffe et al., 1999).

Leybaert and Alegria (1995) examined PA and spelling outcomes withFrench-speaking students who were deaf. The students were enrolled in threeschools in Brussels, both elementary and secondary. A control group ofstudents with typical hearing was included in the study. Mode of communi-cation for the students who were deaf was not described; they were between theages of 8 years, 7 months and 13 years, 4 months (mean age: 10.9 years) with amean hearing loss of 95 dB (range 72–120 dB). When asked to spell words with ahigh sound-letter correspondence, students who were deaf made twice asmany errors as the students with typical hearing. A related study by Sutcliffe etal. (1999) compared the spelling errors of children who had profound hearingloss (average hearing loss of at least 96 dB in their better ear) that attended aschool using a Total Communication philosophy (i.e., instruction occurred inBritish Sign Language and Sign Supported Speech) with children who hadtypical hearing and spoke English as a second language. The spelling testsincluded regular words, defined as having a common spelling with anunambiguous spelling-sound relationship (e.g., gun). Results revealed thatboth groups performed better with words that were used with greaterfrequency in English. However, there was a significant difference between thespelling accuracy of the two groups, with the students learning English as asecond language demonstrating better spelling than the students who weredeaf. Interestingly, only the students who were deaf produced errors on initialsounds, including omissions of the first sound. When the types of errors werecompared, results showed that the children who were deaf produced asignificantly higher number of non-phonetically acceptable spelling errors


(e.g., ‘‘cmal’’ for ‘‘camel’’, ‘‘aicax’’ for ‘‘axe’’) than the English language learnerswith typical hearing.

In 2004, Harris and Moreno matched younger (age 8) and older (age 14)students who were deaf (unaided hearing loss of at least 85 dB in their betterear) with control groups matched for age or reading level. It was reported thatsome of the children, especially in the older group, used oral communication;however, primarily Total Communication (a combination of English andSigned English used at the same time) was used by the children with only asmall percentage of participants demonstrating fluent British Sign Languageskills. A spelling test was administered to all participants. Results revealed thatfewer than 20% of the errors produced by younger and older students whowere deaf were considered ‘‘phonetic errors’’ (defined as when a child attemptsto represent all the sounds in a word but still spells the word incorrectly)(Harris & Moreno, 2004, p.256) while 60% of the errors produced by theyounger students and 80% of the errors produced by the older students withtypical hearing included acceptable phonetic errors. In addition, the spellingtests from the students who were deaf contained significantly more spellingrefusals (i.e., no attempt to spell the word). The authors suggest that studentswho use phonological strategies will attempt to spell unfamiliar words andstudents who are deaf do not use phonological awareness in spelling to thesame extent as students with typical hearing.

Orthographic Pattern Awareness (OPA)

OPA may be described as the ability to translate spoken language to writtenform, specifically focusing on spelling patterns and conventions. Orthographicknowledge includes the understanding of predictable sound-letter combina-tions, sound-syllable relationships, and the patterns that govern a writtenlanguage system (Apel, 2011; Treiman & Bourassa, 2000). School-age childrenwith typical hearing receive systematic instruction in order to learnorthographic relationships, starting with direct sound to letter correspondence(i.e., alphabetic principle), moving to digraphs (i.e., two letters representingone sound), continuing with explicit spelling patterns (e.g., ‘‘i before e exceptafter c’’), and finally learning to spell words that do not conform to specificpatterns but must be memorized (e.g., turquoise, linear).

In a study by Padden (1993), children between the ages of 4 years, 0 monthsand 9 years, 11 months who had severe to profound hearing loss (hearing loss ofgreater than 85 dB in the better ear) and proficient in American Sign Language(ASL) and trained to read written English at school were asked to providewriting samples for analysis of single-word spelling. Results showed that as thechildren got older, their spelling attempts demonstrated a growing knowledgeof English orthographic patterns. In fact, by the time children were 8 years ofage, their orthography was generally consistent with the rules of Englishspelling, and errors reflected transpositions or substitutions of letters in the


medial and final positions, often with substituted letters of similar height orshape. In general, their orthographic errors did not differ to any great extentfrom the types of orthographic pattern errors that might be present in thespelling of children with typical hearing at a younger age.

To assess the OPA of students who are deaf, Olson and Caramazza (2004)analyzed spelling errors made by 23 adults who were deaf (hearing loss of least85 dB hearing loss in their better ear) attending a precollege preparatory courseat a satellite campus of Gallaudet University. Results were compared to thespelling tests from 100 high school students with typical hearing (grades 10, 11,and 12). Incorrectly spelled words were considered to have ‘‘legal’’ orthogra-phy if syllable- and word-position constraints followed allowable Englishpatterns. Results revealed that the students who were deaf made errors thatfollowed orthographic rules, with only 9.4% of all errors categorized asorthographically ‘‘illegal.’’ In addition, the students who were deaf demon-strated no differences in illegal orthographic spellings when words with moreregular sound-letter sequences were compared to less regular sequences (p .

0.05). Results of this study indicate that adults who are deaf attending a collegepreparatory class tend to use legal orthographic patterns when attempting tospell words.

Mental Graphemic Representations (MGRs)

MGRs are the stored mental images of written words or portions of writtenwords (Apel, 2011; Apel & Masterson, 2001) and include spelling words withatypical sound-letter match-ups (e.g., the ‘‘sc’’ in ‘‘scene’’ and ‘‘conscience’’) andinflections of a word that a person has to commit to memory. The ability to usestored MGRs facilitates spelling, particularly with words that do not fit knownpatterns, have atypical orthographic configurations, or atypical sound-lettermatch-ups (e.g., draught, opaque). MGRs are also essential for words that donot follow conventional spelling rules or are used when the word does notcontain a phoneme to orthographic correspondence (e.g., meringue, chame-leon). MGR errors are noted when spelling reflects an incorrect stored mentalimage of a written word.

A growing body of research indicates that students acquire MGRs at thesame time they begin to acquire phonological awareness and orthographicskills, suggesting an interdependent acquisition of phonological, orthographic,and MGR processes (Apel, Wolter, & Masterson, 2006; Treiman & Bourassa,2000). Leybaert and Alegria (1995) showed that students who were deaf hadmore difficulty spelling opaque words (i.e., words in which the correct spellingcannot be derived entirely from use of phonological information) than regularwords or words with morphological components. Similarly, Sutcliffe et al.(1999) demonstrated that students who were deaf had difficulty spelling‘‘strange’’ words—a category defined as having an ambiguous soundcomponent with an unusual letter sequence (e.g., the kn in ‘‘knee’’). Although


their results showed that both students with hearing loss and typical hearingproduced more errors when asked to spell ‘‘strange’’ or opaque words whencompared to regular words, the students who were deaf produced significantlymore errors than the students with typical hearing (Leybaert & Alegria, 1995) orthan the students learning English as a second language (Sutcliffe et al., 1999).

Morphological Awareness (MA)

MA includes one’s ability to consider morphemes (i.e., the smallestmeaningful units of language), their spelling, and the meaningful connectionsthat are made between a root word and its corresponding inflectional andderivational forms (Apel, 2011; Carlisle, 1995). Inflectional morphemes do notchange a word’s intended meaning, pronunciation, or grammatical role (e.g.,jump þ ed ¼ jumped; jump þ ing¼ jumping; book þ s¼ books; Molly þ ’s¼Molly’s), whereas derivational morphemes create novel words with morecomplex meanings than their root form (e.g., ‘‘submit’’ to ‘‘submission’’) (Bahr,Silliman, Berninger, & Dow, 2012). Leybaert and Alegria (1995) showed thatstudents who were deaf made twice as many morphological errors than didstudents with typical hearing. They attributed these findings to poor linguisticcompetence, or a lack of understanding of word meaning and deficiencies inmorphological understanding. Olson and Caramazza (2004) also reportedinteresting findings in regard to morphological representations in theirresearch. During a spelling task, the intended word was read aloud, signedin isolation, included in a sentence that was read and signed, and finally theword was read and signed once again in isolation. Even when repetitions of theintended word were provided as well as a sentence to provide contextualinformation, morphological errors were noted for 12% of the total test battery.The authors suggest that these results may have been due to ambiguities inASL-to-English translations where the morphology of an item was not alwaysprecisely specified by the ASL sign.

Semantic Awareness (SA)

SA is defined as the ability to understand word meanings and the effect ofspelling on a word’s meaning. For example, the meaning of a sentence wouldbe interpreted incorrectly when the wrong word is used to represent anotherword (e.g., ‘‘fry’’ for ‘‘fried’’ or ‘‘drive’’ for ‘‘drivers’’). In addition, errors ofmeaning occur when the wrong word is used and, in context, the meaning is notrepresented correctly (e.g., ‘‘dog’’ for ‘‘car’’). Thus, while a word may be spelledcorrectly, if it has been used incorrectly in context, an error in semantics hasoccurred (e.g., ‘‘foot’’ and ‘‘ball’’ for ‘‘football’’; ‘‘mice’’ for ‘‘mouse’’; ‘‘usually’’for ‘‘used’’). In the literature, spelling has been referred to in the literature as alanguage-based function (Bahr, Silliman, & Berninger, 2009; Perfetti, 1997).While there is relatively little research documenting the explicit relationship


between semantic awareness and spelling skills, Templeton (2004) suggeststhat spelling knowledge provides a place for students to gain an awareness andunderstanding of morphology, which may lead to further enhancement of astudent’s depth and breadth of semantic awareness. Research is required toexamine this potentially reciprocal relationship between vocabulary knowl-edge and spelling skills with children who are DHH.

Gaining insight into the underlying linguistic strengths and weaknessesshown in the spelling errors made by children who are DHH should providevaluable information regarding individual or group language or processingskills. Overall, the literature indicates that students who are DHH demonstratemore errors than do children with typical hearing on spelling tests and inwritten expression (Burman, Nunes, & Evans, 2007; Colombo, Arfe, & Bronte,2011; Olson & Caramazza, 2004; Sutcliffe et al., 1999). However, the researchthat has been done is limited. Additional studies are needed to determine ifthere are effective ways for educators to assess the underlying linguisticprocesses and MGRs related to the spelling errors of students who are DHH inorder to improve our understanding of their unique spelling needs. If specificareas of weakness can be identified, educators can focus their instructional timeto target the deficit(s) and improve written expression.

The purpose of the current study is to examine the effectiveness of twodifferent methods of analyzing spelling errors in an effort to gain insight intothe type of linguistic knowledge that DHH children demonstrate in theirspelling performance, and how that information might be used in spellinginstruction. To date, there have not been any studies to indicate the optimalmethod for analyzing the spelling errors of children who are DHH. The twodifferent coding methods that were selected for the analysis included onestandardized measure and one detailed descriptive measure. It is hypothesizedthat both coding methods will supply information about the linguisticprocesses and mental images of words used by children who are DHH. Theresults will determine which coding method provides information educatorsneed to understand how linguistic knowledge is represented in the spellingerrors of DHH students. This information should ultimately assist educators inthe development of better spelling interventions.

Methods

Participants

Twenty middle school students—12 sixth grade and 8 seventh gradestudents—attending a Southeastern residential school for the deaf participatedin the study. All students in the sixth and seventh grades with completedconsent forms were included in the study. Hearing status of the students usingthe most recent available data was calculated. Students averaged a meanhearing loss (HL) of 97dB in their better ear (range 43–113þ). One student was


considered hard of hearing (43 dB HL in the left ear, 48 dB in the right ear).Exposure to ASL varied among the children. Some students were fluent in ASL,while other students used sign supported speech as their primary mode ofcommunication. The school’s communication philosophy is to practiceSimultaneous Communication (i.e., spoken English and Manually CodedEnglish).

Procedures

Spelling Words

Nineteen words, a subset of the 40 words used in conjunction with theSpelling Sensitivity Score procedure (SSS) (Masterson & Apel, 2000, 2010), wereselected as stimuli for the experimental spelling test. The 19 words used for theexperimental test were selected because they represent different spellingpatterns and place demands on a child’s phonological, orthographic,morphological, and semantic knowledge, and understanding of mentalgraphemic representations. The full list was not used because their teacherthought the 19-word list was about the right length for gathering spellinginformation without frustrating the participants. A list of the words used in thestudy is included in Appendix A.

Test Administration

The spelling test was administered by the students’ classroom teacher in agroup setting. All test administrations were provided by one teacher of the deafin order to maintain consistency throughout the administration of theassessment. The teacher is one of the authors of this paper and holds a degreein interpreting as well as a doctorate in education with a concentration inliteracy studies. All students completed the spelling test at their desk onstandard notebook paper. For each item, the classroom teacher selected andprojected a picture of the word to provide context while reading it aloud inEnglish; and when a signed equivalent was available, the word was alsosigned. The teacher then fluently fingerspelled each word in order to accountfor any loss in meaning when the word was presented via picture or sign. Thestudents were instructed to spell the presented word after each word waspresented in a picture, said orally, signed (if there was a direct ASL signavailable for that word), and fluently fingerspelled.

The use of fluent fingerspelling has been used in previous spelling research(e.g., Olson & Carramaza, 2004), with the rationale that providing only the signfor each word would require the student to know what the sign means (i.e., linkthe sign to meaning). Students who are deaf have access to orthographicinformation via fingerspelling that is similar to the phonological information ofa word presented orally to students with typical hearing. As a result, the use of


fingerspelling with children who are DHH is comparable to the oralpresentation of words for students with typical hearing in a spelling test(Reitsma, 2009; Stewart & Clark, 2003).

Scoring

Total Correct Versus Incorrect

The completed spelling tests were first examined for total words correctcompared to words attempted. This was done because a quick review of theindividual spelling tests indicated that there were many words that were eitherpartially attempted or not attempted at all across the participants. Words werecoded as (a) correct, (b) attempted with only one element, (c) attempted withmore than one element, or (d) unattempted. An element was defined as one ormore letters/sounds that correctly corresponded with the target word. Forexample, if the target word was pool and a participant only wrote a ‘‘p,’’ theword would be considered attempted with only one element. If a participantwrote ‘‘hear’’ for heard, the word would be coded for attempted with more thanone element. Words were scored as unattempted when the student did notmake any attempt to spell a word, drew a straight line after the item number, orwrote ‘‘IDK’’ (i.e., I don’t know) in the blank.

Coding Methods

Two different coding methods were used to analyze the results of the spellingtests. Both coding methods used the same 19 words for the analyses. Allspelling tests were first coded using the SSS procedure and then the multi-linguistic coding (MLC) system by one of the authors familiar with both codingmeasures. Twenty percent of the words from the total number of spelling tests(i.e., five words from each test), as well as 20% of the spelling tests (i.e., fivecomplete assessments) were scored by one of the authors, also familiar withboth coding systems. For the SSS scoring metric, 97% reliability across itemsand students was obtained. For the MLC system, 96% reliability across itemsand 94% reliability across students was obtained. All discrepancies for bothmeasures were reviewed and a consensus was reached for all items in question.

SSS Coding. The first coding method was taken directly from the SSS manual(Masterson & Apel, 2000). The SSS is a published measure designed to provideinformation about the linguistic knowledge required for accurate spelling atboth the word and the element (i.e., the letter) level. When used with typicallydeveloping children, the SSS has been shown to be an effective spelling tool thatis sensitive to developmental and instructional change.

Following the SSS manual instructions, each word attempted by the studentis broken down into three key word components for scoring: base word (i.e., root


word), juncture (i.e., any elements that occur before a suffix), and inflections(i.e., prefixes and suffixes). Using the SSS interactive spreadsheet, words aredivided into their individual components. For example, the word puttingincludes all three word components. The base word in this case would beconsidered ‘‘put.’’ The juncture, which occurs after the base word but beforeany inflections, would be the second ‘‘t’’ in putting. Inflections are consideredtheir own word component, in this example, the ‘‘ing’’ in putting. It should benoted that not all words will include all three possible word components (e.g.,the words ‘‘jog,’’ ‘‘chair,’’ and ‘‘ship’’ do not include junctures or inflections).

In addition to word level components, spelling words are also analyzed at theelement level. First, the base word component is broken down into elements,with each sound in the base word representing an element. For example, forput, the base word would be broken into ‘‘p-u-t.’’ Next, junctures and inflectionsare also analyzed at the element level. For example, the spelling attempt ‘‘cry’’for ‘‘cries’’ would be analyzed as follows: the student would receive credit at theword level for including the base (i.e., ‘‘cr’’) and the juncture (i.e., ‘‘y’’), but notthe affix (i.e., ‘‘s’’). So, two of the three word components were accounted for. Atthe element level, three of the four elements were present (i.e., ‘‘c,r,y’’ but not‘‘s’’). Therefore, errors occurred at the word level (no inflection), the elementlevel (no ‘‘s’’ at the end), and the orthographic level, representing ‘‘i’’ with a ‘‘y.’’All of these would be taken into account by the scoring metric.

It is important to note that several types of words are excluded from the SSSanalysis. These include: (a) any words that students do not attempt to spell; (b)transpositions (i.e., errors when two adjacent letters or sounds are reversed); (c)errors with two or more adjacent element omissions or additions that cross thebase-juncture or juncture-suffix boundaries; and (d) random strings, includingincorrect initial letter, strings of more elements or letters than the target word,or a mix of letters and non-letters. Therefore, if a student failed to attempt fivewords and included random strings of letters in two words, only 12 out of 19words were included in the final SSS analysis. After all the words included inthe analysis have been analyzed at the word component and element levels,two scores can be obtained.

Based on the SSS analysis, each word is scored at an SSS-Element (SSS-E) andan SSS-Word (SSS-W) level. The final SSS-E represents the sum of all individualword SSS-E totals divided by the total number of elements in the words used forthe spelling test. For the word putting, there are a total of five possibleindividual elements (i.e., three base word elements; one juncture element; onesuffix or inflection element); however, it has only three possible word elements(i.e., base word, juncture, and inflection). The total SSS-Wrepresents the sum ofall word scores divided by the total number of analyzed words in the sample fora single participant. Both the SSS-E and the SSS-W are interpreted based on ascore range of 0–3. Scores between 0.0–1.0 imply a weakness in phonologicalawareness (PA), scores between 1.0–2.0 suggest a strength in PA knowledgeand a lack of orthographic pattern knowledge (OPA), and scores between 2.0–


3.0 are interpreted as strengths in PA and OPA knowledge, with a need toimprove use of mental grapheme representations (MGR). Thus, a student mayreceive different scores for their word level performance and their elementlevel performance.

MLC. The second coding method used a multi-linguistic coding system(Apel & Masterson, 2001; Masterson & Apel, 2010; McCarthy, Hogan, & Catts,2012). The MLC system was developed to provide a detailed qualitativeanalysis of spelling errors. It differs from the SSS in that it does not providescores to describe the results (e.g., SSS-Word or SSS-Element scores). Rather, theMLC system provides a detailed accounting of linguistic errors beyond thoseexamined in the SSS analysis. Specifically, this coding system allows theexaminer to analyze the phonological, orthographic, mental graphemicrepresentation, morphologic, or semantic errors that can be identified withineach word without the constraints posed by the scoring rules of the SSS (refer toTable 1). As a result, this system offers a more flexible and in-depth analysis ofthe linguistic errors that appear within an individual’s single-word spelling.All spelling words were placed in an Excel spreadsheet and then coded for typeof error. Each word was first examined to see if all sounds for the word wererepresented. If a sound was missing in the word or two letters were reversed, aPA error was coded. Next, the word was examined for any orthographic errors.If any incorrect representations of regular spelling patterns (e.g., consonantsubstitutions, letter combinations, positional constraints), were noted, an OPAerror was coded. If any errors that would be considered irregular patterns ofEnglish spelling rules (e.g., correct phonetic spelling of non-phoneticallyspelled words, incorrect spelling of unstressed words), an error of MGR wascoded. Any errors of modification (e.g., morphemes, wrong tense) were codedas an MA error. Finally, errors of meaning (e.g., wrong word represented butspelled correctly) were coded as an error of SA. Spelling errors could be codedfor one or more linguistic categories. For example, ear for ‘‘heard’’ was coded asboth a PA and an SA error. The word ‘‘heard’’ has 3 possible sounds; however,the participant’s spelling of ear only represents 2 sounds, thus it was coded PA.Additionally, the word ear was coded SA, as it is a true spelling of a word.

Results

Overall Spelling Accuracy

Out of a possible 380 words, attempts were made for 308 of the words. Ofthese, 149 were spelled correctly. For the 159 words that were attempted but notspelled correctly, 45 word attempts included only one element while more thanone element was attempted for the remaining 114 words. Participants did notattempt (i.e., no response was written) 72 words (i.e., 19% of words were notattempted) (Figure 1). Across all tests, the participants attempted to spell 80%


of the target words and spelled 149 words correctly out of a possible 380; thus,on average, each participant spelled 7.4 words correctly (range: 0–16).

SSS Coding

Average scores for both the SSS-E and SSS-W analysis were calculated foreach participant (Figure 2). For the SSS-E, on average, participants scored a 1.66(range of 0.30–2.91), with a standard error of 0.18. For the SSS-W, participantson average scored 1.56 (range of 0.00–2.74), with a standard error of 0.19. Theaverage scores for the SSS-E and SSS-W fell within the 1–2 range, indicating thatparticipants have adequate PA skills and weaknesses in understandingorthographic patterns; however, there was high variability among the resultsof individual participants.

Following the SSS analysis, individual participant test results were furtherexamined and scoring problems using the SSS were identified (see Appendix Bfor the SSS-E and SSS-W individual test results). An average of 14.1 words(range of 8–19) from the target 19 words could be analyzed using the SSS. Thus,out of 380 words, only 282 were included in the SSS analysis, or 74% of the totalnumber of words. The 98 remaining target words were deemed unanalyzable

Figure 1. Number of words unattempted, only one element attempted, more than oneelement attempted, and correctly spelled words.


because the word was not attempted, contained transpositions, or had errorswith two or more adjacent element omissions or additions that crossed thebase-juncture or juncture-suffix boundaries.

MLC

Scores from the MLC (Apel & Masterson, 2001; Masterson & Apel, 2010;McCarthy et al., 2012) were analyzed using a one-way analysis of variance(ANOVA) with one repeated measure, Error Type (PA vs. OPA vs. MGR vs. SAvs. MA). Results indicated that there was a significant main effect for ErrorType, F(1, 19)¼ 81.52, p , 0.001, with a large effect size (gp2¼ 0.81). Effect sizeis provided using the partial eta-squared (gp2), considered small when lessthan 0.06, medium when greater than or equal to 0.06 and less than 0.14, andlarge when greater than or equal to 0.14 (Kinnear & Gray, 2008).

A closer examination of the means for each spelling error type (Figure 3)revealed that the participants made more phonological awareness (PA) errors(M¼ 5.85, SD¼ 3.87, range 0–13) than any other type of error. Additionally,participants made semantic awareness (SA) errors (M¼ 2.20, SD¼ 2.11, range0–8) more often than morphological awareness (MA) (M ¼ 1.65, SD ¼ 1.18,

Figure 2. Mean and standard error (SE) of SSS-Element (SSS-E) and SSS-Word (SSS-W)scores.


range 0–4), orthographic awareness (OPA) (M¼ 1.10, SD¼ 1.21, range 0–3), ormental graphemic representation (MGR) errors (M¼ 0.10, SD¼ 0.31, range 0–1) on the spelling assessment.

Discussion

To gain further understanding of the linguistic skills that children who areDHH employ during a spelling task, this study examined the spelling errors ofmiddle school students who are DHH using two types of analyses. Twodifferent coding systems—the SSS and MLC measures—were used in an effortto determine how the two coding systems provide insight into the underlyinglinguistic knowledge of the students in order to target appropriate interven-tions for this specific population. Consistent with previous research, the resultsfrom both measures indicate that this group of DHH children revealedsignificant difficulty with spelling. Results of the two measures differed in theiranalysis of the specific areas of weakness that children who are DHHdemonstrate in their spelling. The SSS and MLC measures each provide uniqueinformation regarding spelling skills. It is notable that the SSS looks at fewerlinguistic processes than the MLC, so the linguistic categories differ. The SSS isstructured so that words may be considered unanalyzable, even if a spellingattempt was made. The MLC evaluates all spelling attempts and even codeswords that were not attempted, which has the potential to provide insight intospelling problems.

SSS

Scores from the SSS indicated that the students demonstrated adequatephonological awareness skills, as 15 of the 20 students had scores above a 1.00

Figure 3. Mean and standard error (SE) of the Multi-Linguistic Coding.


for the SSS-W score. As interpreted by their final SSS-W scores, nine of thestudents showed the greatest deficits in understanding orthographic patterns,and six students demonstrated an SSS-W score in the 2–3 range, indicatingadequate PA and OPA skills for the spelling task. However, scoring proceduresdo not allow the SSS results to account for words made up of random letterstrings or words that were not attempted. Thus, for some children, the SSSresults suggest that they have adequate phonological awareness skills when infact they may have made phonologically implausible word strings (Geers &Hayes, 2011), have attempted to write random letter strings, or just did notattempt the word. For example, Subject 12 spelled seven of 19 words correctlybut did not attempt 11 words (see Figure 4). Therefore, only eight of thestudent’s 19 words were used in the SSS-E and SSS-Wanalysis. Interpretation ofthis student’s SSS-E, a 1.156, suggests that this student has effective PA skillsbut did not employ orthographic awareness skills for the spelling task at theelement level. The same sample resulted in an SSS-Wof 2.625, which would beinterpreted as sufficient PA and OPA skills with a need for further developmentof MGRs. Since these results do not represent all of the words, they cannot fullyevaluate the student’s spelling abilities which might result in the student notreceiving much needed work to improve in non-identified deficit areas.

Another example is Subject 19, who did not attempt to spell the words chain,unite, or chief, and his attempt for the words pie and leaf contained too manyelements to analyze (pard and levar, respectively). Since three words were notattempted and two words contained more elements than the target word, thesespelling words were not included in the SSS scoring procedure. At the present

Figure 4. Portion of a spelling assessment that included 11 omissions.


time, there is no way within the SSS to note how many words are discarded ordeemed unanalyzable, thus potentially inflating the gross SSS-E and SSS-W forsome students. For this student, the SSS could only be used to analyze 14 of the19 words, earning the student an SSS-E of 1.766 and an SSS-W of 1.688. Thisoverall SSS total indicates the student has more difficulty with orthography atthe element level and word level; however, closer examination of the errorsreveals that this student continues to struggle with phonological knowledge(e.g., pute for putting) and semantic information (e.g., produced right for correct)when spelling. Research has demonstrated that children who are DHHproduce spelling errors that are phonetically implausible (Leybaert & Alegria,1995; Sutcliffe et al., 1999), yet the SSS does not consider many of thephonetically implausible spelling attempts in their analysis.

Results of the analyses indicate that the SSS does not account for thenumerous unanticipated morphological errors typically produced by studentswho are DHH. For example, when presented with the target word cries, sixstudents wrote cry and six other students wrote crying. Even though the wordhad been spoken, pictured, signed in ASL, and fluently fingerspelled, thestudents were unable to access the morphological information being targeted.Only one student was able to accurately spell cries. The inability to capturethese morphological errors using the SSS system indicates a weakness in theSSS for use with children who are DHH, as morphological errors are common.This is an important finding, as research has shown a significant relationshipbetween spelling and morphological awareness (Apel, 2011; Carlisle, 1995) andresearch has demonstrated students who are DHH struggle in this area ofspelling (Leybaert & Alegria, 1995; Olson & Caramazza, 2004). Using ananalysis method that captures these types of errors could provide beneficialinformation for teachers and other professionals working to improve thespelling skills of children who are DHH.

In addition to the errors in morphology that were not described using theSSS, several students made semantic errors that could not be coded becausethere is no category for these types of errors; thus, the words were deemedunanalyzable and not included within the final SSS total. For example, Figure 5shows a portion of the spelling test for Subject 18, which includes five clearsemantic errors: walking for jog, boat for ship, water park or lake for pool, sweep-leaffor rake, and boil-ball for coal. It is hypothesized that the semantic errorsoccurred because the oral presentation, sign, and fluent fingerspelling weremissed or ignored, and the student simply guessed at the picture. Due to thefact that the SSS does not analyze semantic errors with more elements than thetarget word, three correctly spelled words by this student were not included inthe final analysis for either the element or word level, and two correctly spelledwords were included even though the attempt did not match the target. Thisstudent received an SSS-E score of 1.438 and an SSS-W score of 1.688, indicatingdeficits in orthographic awareness at the element level and word level.However, it is clear that these are semantic rather than orthographic errors


since the accurate orthographic information was included in the student’sspelling attempts.

MLC

In contrast to the SSS results, the MLC scores show that participants mademainly phonological errors rather than orthographic errors. The results alsoindicate that children who are DHH were more likely to make semantic errorswhen spelling single words rather than morphological, orthographic, or MGRerrors. In comparison to the SSS, the MLC provides a more in-depth andpotentially more complete picture of each participant’s spelling abilities. Forexample, it would be suggested that Subject 6, who received an SSS-E of 1.719and an SSS-W of 1.867, has phonological and orthographic awareness skillswith a weakness in MGR knowledge. However, further examination of thisstudent’s errors shows that four words were not attempted. In addition, thestudent produced caol for coal (phonological error) and chapel for chain(semantic error) that were not included in the analysis, as well as heared for heard(orthographic pattern and morphological errors). Thus, this is not a student

Figure 5. Portion of spelling assessment with five semantic errors.


who needs to learn words that one ‘‘just needs to know’’ how they are spelled;this student requires understanding of suffixes (-ed) as well as irregular pasttense, semantic knowledge of the word chain, and orthographic informationabout combining the vowels a and e in English words. In addition, furtherexploration as to why the student did not attempt four words—hang, unite,chief, and correct—should be conducted, possibly via interview with thestudent. This information would only have been captured using an in-depthanalysis such as the coding system.

A limitation of the MLC analysis is that it does not provide a score forprogress monitoring but rather a qualitative analysis. In addition, the analysisof the spelling tests takes longer than scoring for correct versus incorrect trials(i.e., percentage of correct spelling attempts). It required approximately 15minutes to code each child’s single-word spelling test and a total of 5 hours ofanalyses for 20 children. For these reasons, the MLC system may prove to beimpractical for routine classroom assessment and best used for children whosespelling is clearly different from the norm.

Limitations and Future Directions

This study was the first known attempt at examining the spelling skills ofchildren who are DHH by analyzing their errors using two different codingsystems—SSS and MLC—to assess underlying linguistic deficits. One of thelimitations of this study includes the small sample size of middle schoolchildren. In addition, spelling samples from a control group of peers withtypical hearing were not obtained so comparisons are not available. Futureresearchers may consider testing a larger sample of participants with a widerrange of hearing loss. Further, the participants in this study attended a schoolfor the deaf and communicated primarily through sign language. Futurestudies may want to include children who use cochlear implants and uselistening and spoken language as their primary mode of communication.

Another potential limitation of the study is the sample size of the words usedto assess spelling. It may be that a larger sample would provide additional ordifferent information about spelling errors. Future researchers may considerincreasing the sample of spelling words and using all of the 40 words from theSSS list that were designed to target different phonological, orthographic, andmorphological structures. It would be interesting to know if the differences inthe results between the shorter (19-word) and longer (40-word) lists werestatistically significant. If they were different, then the longer list may be moresensitive to calculating error categories. However, administration of the 40-word list and subsequent spelling analyses with this population may have to beconducted on an individual basis since the 19-word list was chosen because theteacher felt it was as long a test as the children would tolerate. In contrast, if thesmaller sample size did not differ in any significant way from the longer list,


additional lists with words of similar structures and content could be used toestablish multiple forms for progress monitoring. This would be a usefuladdition to assessment protocols in schools that administer curriculum-basedmeasures to evaluate response to intervention.

For future studies, test administration effects should be controlled for byvarying the presentation of pictures, simultaneous sign and speech, andfingerspelling of the target word. It is possible that some students—particularlythose that made a significant amount of semantic errors (refer to Figure 5)—may have looked only at the picture representation and did not attend to thefingerspelled presentation or ASL sign. Different test administration ap-proaches, such as providing the ASL sign, fingerspelled presentation, andspoken word prior to showing a picture of the intended item should beconsidered in the future. There is also the possibility that there could be changesor improvements in the types of words used to assess spelling since MLC can beused with any words. These changes might include the use of words includedin the curriculum because that would provide additional information about astudents’ familiarity with important content area vocabulary.

To test the practicality of using more in-depth analyses of spelling errors,future research may also want to examine spelling errors using words obtainedfrom assigned writing activities. By using words that the child has chosen tospell as part of their own writing, educators may be able to provide moreindividualized spelling assistance and facilitate immediate improvements inwriting.

Conclusion

Spelling is a complex and critical skill. Beyond the obvious need to spell wellenough for others to read what has been written, the ability to spell is importantfor school-age children because better spellers are able to focus their cognitiveresources on other important aspects of composition, including tone, audienceneeds, and topic maintenance (Aaron et al., 1998; Moats, Foorman, & Taylor,2006; Wolbers, 2007). The participants in this study were noted to be poorspellers, and the analyses of their spelling tests revealed that they showed thegreatest deficits in phonological, morphological, and semantic knowledge withrelatively good skills in orthographic knowledge.

With additional research, an MLC system may prove the optimal means ofcapturing the linguistic foundations of spelling errors evidenced by studentswho are DHH. In addition to the need for studies that examine the size of thespelling sample, future investigations might also look at spelling patterns usingdifferent types of writing, including personal narratives and expository texts.The use of different types of writing samples may provide further insight intothe linguistic strategies students who are DHH use for spelling when theyselect the words. Gathering this type of information is important because it has


the potential to help educators design interventions that target the greatestareas of weakness in spelling. Additional research in these areas may alsoprovide teachers with a way to accurately monitor improvements in spelling asa result of instruction.

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Appendix A

Target Word List Used for Analysis

Target Words

1. jog2. ship3. nine4. white5. pie6. pool7. bowl8. hang9. leaf

10. rake11. cries12. coal13. heard14. chain15. unite16. chief17. putting18. knocked19. correct


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Examination of the spelling skills of middle school students who are deaf