Marc Marschark Family Involvement as Part of Success for Learning to Speak in Hard of Hearing Child
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Abstruse
Deaf learners are a highly heterogeneous group who demonstrate varied levels of bookish achievement and attainment. Well-nigh prior research involving this population has focused on factors facilitating academic success in young deaf children, with less attending paid to older learners. Contempo studies, still, have suggested that while factors such equally early cochlear implantation and early sign language fluency are positively associated with academic accomplishment in younger deaf children, they no longer predict achievement once children attain high school age. This study, involving information from 980 college-bound high school students with hearing loss, examined relations betwixt bookish achievement, advice variables (audiological, linguistic communication), and use of assistive technologies (e.g., cochlear implants [CIs], FM systems) and other support services (eastward.grand., interpreting, real-time text) in the classroom. Spoken language skills were positively related to achievement in some domains, while better sign language skills were related to poorer achievement in others. Amongst these college-bound students, use of CIs and academic support services in high school accounted for little variability in their higher entrance examination scores.
Understanding Deafened Learners' Outcomes
For well over xxx years, investigators have recognized our inability to business relationship for near of the variability in the academic outcomes of deafened learners, every bit indicated by either standardized accomplishment testing or level of degree attainment (Carlberg & Kavale, 1980; Dammeyer & Marschark, 2016; Kluwin & Moores, 1985; Leigh & Crowe, 2015; Leigh & Marschark, 2016; Rydberg, Gellerstedt, & Danermark, 2009; Stinson & Kluwin, 2011). It now has been shown that factors like hearing thresholds, language modality, schoolhouse placement, and other child and family characteristics can be of import contributors to deaf children'southward educational progress, but no i of them solitary is sufficient to predict the academic outcomes of individual deaf learners or groups of deaf learners. This does non brand those factors whatsoever less interesting or worthy of investigation. Instead, it suggests that rather than evaluating the extent to which whatsoever single variable (e.1000., cochlear implant [CI] use or preferred language modality) is significantly related to bookish performance, a broader agreement of deaf learners' bookish outcomes might be gained through multifactorial investigations of variables that co-occur amid deaf learners in educational settings (eastward.yard., CI use and preferred language modality).
Given the acknowledged diversity in the deaf population with regard to hearing thresholds, language fluencies, modality preferences, socio-cultural backgrounds, and and so on, our agreement of contributors to those outcomes is well-served by investigations that involve relatively large, and relatively diverse samples of deaf individuals. Small, homogeneous samples, consisting of, for example, native signers in a single community, students in a bilingual classroom, or successful CI users from a unmarried implant center, tin be informative in guiding further enquiry, just they are not very enlightening with regard to the larger issue of predicting or understanding academic outcomes of deaf learners at large. In an effort to movement toward a broader understanding of bookish outcomes for deaf learners, the nowadays written report was designed as a large sample, multi-factor study following from findings with regard to two factors by and large causeless to be potent predictors of bookish outcomes among deafened learners: language modality and the use of engineering, including CIs and hearing aids, in education settings.
Benefits to Deaf Learners' Academic Outcomes: Now You See 'em At present You Don't
Variability in the benefits to spoken language for immature deafened children who receive CIs is "notoriously loftier" (Niparko et al., 2010, p. 1498). Nevertheless, a variety of studies has documented benefits of pediatric cochlear implantation for early on reading achievement (Damen, van den Oever-Goltstein, Langereis, Chute, & Mylanus, 2006; Geers, 2003; Vermeulen, Van Bon, Schreuder, Knoors, & Snik, 2007; Nittrouer, & Caldwell-Tarr, 2016). "Early on" is an important qualifier here, because such benefits are primarily evident during the elementary school years (historic period half dozen–11 years), and several big-sample studies have indicated that these early benefits are profoundly attenuated or absent past the high school (historic period 15–18 years) and higher/university years (historic period eighteen and over) (Convertino, Marschark, Sapere, Sarchet, & Zupan, 2009; Geers, Tobey, Moog, & Brenner, 2008; Marschark, Shaver, Nagle, & Newman, 2015).
Gaps in reading achievement between deaf children who employ implants and their hearing peers typically get larger with age, just as they do among deaf children who do and do not use CIs (Geers et al., 2008; Harris & Terlektsi, 2011; Thoutenhoofd, 2006). Thoutenhoofd (2006) aptly suggested that as more deaf children receive CIs at younger ages, that pattern might change. Comparison of contempo findings to his snapshot of CI users and nonusers in the years 2000–2004, however, indicates that the change has non however occurred. All the same, while such findings have been obtained in the majority of studies and for the majority of deaf children, some deaf learners do reach reading levels like to those of their hearing peers, or at to the lowest degree are not every bit far behind, as do deafened peers who exercise not employ CIs (Easterbrooks & Aggravate-Alvarez, 2012; Fitzpatrick et al., 2012; Nittrouer & Caldwell-Tarr, 2016). Among high school and college students as well equally adults, CI employ is generally found to be unrelated to level of caste attainment (Dammeyer & Marschark, 2016), classroom learning (Convertino et al., 2009), vocabulary and earth knowledge (Convertino, Borgna, Marschark, & Durkin, 2014), and bookish achievement across the curriculum (Marschark et al., 2015).
A like pattern of early benefits to academic achievement being attenuated or absent among older deaf learners appears to exist nowadays in the literature concerning sign language abilities. Studies by Strong and Prinz (1997), Padden and Ramsey (2000), and others have shown significant advantages in reading among young, native-signing deaf children of deaf parents compared to deaf children of hearing parents. Notwithstanding, children in those studies have been predominantly of simple schoolhouse age. A study by Nover, Andrews, Baker, Everhart, and Bradford (2002) of 179 8- to 18-year-olds, approximately i-third of whom had deaf parents, found an advantage in reading for deaf children in a bilingual (American Sign Linguistic communication and English) deaf education plan compared to deaf children at big, according to U.South. norms. Although statistically significant, the advantage was small (about ane%) and held merely for 8- to 12-yr-olds. Similarly, Lange, Lane-Outlaw, Lange, and Sherwood (2013) studied a sample of deaf children in which 95% were of elementary school age, and they reported no advantage for deaf children of deaf parents over deaf children of hearing parents in math or reading skills or in bookish growth. Other studies examining reading (Convertino et al., 2009; Marschark et al., 2015; Miller et al., 2012; Miller, Kargin, & Guldenoglu, 2015) besides as achievement in mathematics and science (Convertino et al., 2009; Marschark et al., 2015) take failed to notice significant advantages associated with sign language abilities or parental hearing status amongst deaf children of deaf parents once those students reach high school and higher age. Others take plant negative associations of sign language and reading (DeLana, Gentry, & Andrews, 2007; Sarchet et al., 2014). Meanwhile, in that location besides has been little testify for long-term benefits to bookish outcomes of bilingual deaf education, equally indicated by achievement test scores (ordinarily in reading) or level of degree attainment (Bagga-Gupta, 2004; Dammeyer & Marschark, 2016; Rydberg et al., 2009) across the elementary school years. Bilingual deafened instruction models therefore are at present being phased out in a number of European countries that were among the beginning to implement them (Swanwick et al., 2014).
Several explanations take been offered for the above findings indicating that early on linguistic communication benefits for children who have effective admission to language through CIs (spoken linguistic communication) or deaf parents (sign language) back up academic functioning in the early grades but do not do so besides in the later grades (meet Marschark & Knoors, in press, for a review). Virtually apparently, deafened children who demonstrate better language and academic skills in elementary school might be less likely to concenter teacher and school interventions and support services every bit they get older. The language, materials, and instructional goals in school likewise become more complex in subsequently grades, requiring higher level linguistic communication abilities (Archbold, 2015; Chung, 2016; Domínguez, Carrillo, González, & Alegria, 2016) and cerebral abilities (Ansell & Pagliaro, 2006; Blatto-Vallee, Kelly, Gaustad, Porter, & Fonzi, 2007; Knoors & Marschark, 2014). All of these factors contribute to the irresolute academic demands and outcomes as children get older, affecting dissimilar learners in dissimilar ways. Meanwhile, differences in teacher methods and expectations, peer interactions, and educational technologies likewise change every bit children become older, and deaf learners' language and cognitive abilities probable touch the speed and extent to which they adapt to those differences.
Diverse Predictors of Accomplishment in a Diverse Population
The apparent disconnect between factors that predict deafened learners' bookish performance in early on school years and the later school years clearly is neither abrupt nor ubiquitous. If all, or even some, of the above factors are involved in the changing of academic "inputs" and "outputs," variability in them will affect the outcomes of relevant investigations. Hence the importance of the before noted emphasis on including diverse segments of the deaf population in educational research, specially those in the subsequently stages of formal education. Rydberg et al. (2009), for example, evaluated the bear on of bilingual didactics in Sweden on bookish attainment, comparing data from 2,144 individuals born between 1941 and 1980 who had attended schools for the deafened before and during the bilingual deafened pedagogy era there. They establish that while academic attainment in the deaf population had increased during the bilingual era, so had that of the full general Swedish population, pregnant that the deafened-hearing accomplishment gap persisted. Similar findings recently have been obtained in Kingdom of denmark (Dammeyer & Marschark, 2016).
Marschark et al. (2015) examined data from approximately 500 deaf high school students randomly selected from around the United States to participate in the National Longitudinal Transition Written report two (NLTS2). Their results indicated that neither the employ of CIs nor sign language was significantly associated with achievement at that level, when other factors were controlled. Having attended merely mainstream schools was one of the all-time predictors of achievement scores in reading, mathematics, social studies, and science. However, the NLTS2 was a report of loftier school students with disabilities, and the Marschark et al. sample of deaf students included a number who had additional challenges, a cistron that was significantly related to achievement. Dammeyer and Marschark (2016) found both CI use and having attended a schoolhouse for the deaf negatively related to academic attainment. However, their sample of 839 Danish xvi- to 64-year-olds varied widely in their utilize of CIs and their educational backgrounds (including schooling earlier and after the bilingualism era). Both of these studies thus warrant replication with other, big samples.
The present study had a more restricted focus than the big, omnibus studies described in a higher place, insofar as information technology specifically was aimed at predictors of achievement amidst deaf high schoolhouse students who were higher-bound. The written report had 2 specific goals. One goal was to replicate previous studies examining associations betwixt primary language modality and/or CI use on academic outcomes. Marschark et al. (2015) establish that while neither using sign language nor a CI significantly predicted high school accomplishment, the power to use spoken language was a significant predictor of achievement scores beyond all four achievement domains. Dammeyer and Marschark (2016) institute that among those deaf adults with good to very good spoken linguistic communication abilities, sign language power was not a significant predictor of educational attainment when other variables were controlled. Amidst those with skillful to very good sign language abilities, speech communication was a predictor of educational attainment. In a written report that analyzed census information for sign language users in Australia, Willoughby (2011) establish that sign language users between 25 and 44 years of historic period had achieved higher levels of bookish attainment than those between 45 and 64 years of historic period. Willoughby attributed the younger deafened individuals' completing more schooling to external factors, such as pressure during the 1960s–1980s for deaf people to leave school to accept upwards a merchandise, contrasting with the later emphasis on school retention in the (Australian) Disability Discrimination Deed of 1992. Factors such as language skills and the possible contributions of CIs in spoken language were not considered in the Willoughby study, despite the fact that CI employ in Australia has long outpaced the rest of the world.
A second goal of the nowadays study was to examine the impact of relevant technologies on academic achievement. Marschark et al. (2015) failed to discover an event of either hearing aid or CI use on academic outcomes, merely other educational technologies were not considered. Dammeyer, Lehane & Marschark (in press) conducted a study of academic support services that included various classroom technologies and interpreting among deafened xvi- to 65-year-olds in Denmark. They found that neither employ of hearing aids nor CIs was associated with academic attainment (i.due east., whether or not a college degree had been obtained). However, they did find that individuals who had accomplished college degrees were more probable to have used FM systems, mobile video interpreting, and texting devices. The investigators suggested that that association might be explained by college graduates having gained greater noesis, feel, and better access to support services and technologies through their college educations. The opposite also may be true, of form: Greater use of technology may have improved access and learning, thus enabling greater academic attainment.
Studies examining the impact of applied science use on bookish outcomes apparently have not been conducted in the United states of america, although Stinson (in press) reviewed studies that have found communication technologies to increase deaf students' participation and the frequency of content-related interactions between deaf and hearing peers in the classroom. Several studies also have examined the impact of real-time text in the classroom. Stinson, Elliot, Kelly, and Liu (2009), for example, compared the benefits to deaf loftier school and college students' learning of real-time text equally compared to sign language interpreting. High school students retained more than data from classroom lectures supported by real-time text rather than by sign language interpreting, merely a pregnant deviation was not observed amid the college students. Marschark et al. (2006) compared the benefits to learning by 12- to 16-yr-olds of existent-fourth dimension text, sign language, and having both available simultaneously. No differences were institute among the 3 types of information delivery either immediately later on the lesson or on a delayed test 1 week later. A similar experiment involving college students, in contrast, institute that real-time text alone led to significantly amend test performance than either of the other two atmospheric condition. Although that finding might appear counterintuitive to those familiar with deafened education, follow-up studies revealed that deaf college students, every bit a group, consistently learn equally much or more from text every bit they do from sign linguistic communication, regardless of whether instructors are signing for themselves or using sign language interpreters (Borgna, Convertino, Marschark, Morrison, & Rizzolo, 2011; Marschark, Sapere, Convertino, Mayer, Wauters, & Sarchet, 2009).
In summary, studies examining the benefits of sign linguistic communication and access technology in deafened education take yielded three general findings of involvement hither. Get-go, although CIs and speech are associated with better bookish performance (or at least reading) in younger grades, large-scale studies have establish that implant use generally is not significantly related to either academic achievement or academic attainment among deafened individuals from high schoolhouse onward. Second, studies involving centre schoolhouse (eleven–14 years of age) through higher-anile deafened students take found classroom learning to benefit as much or more from real-time text equally sign language in the classroom, even when such text is as evanescent as signing. This finding may be related to results indicating that at least past high school age, spoken language merely non sign linguistic communication abilities are associated with reading achievement (Perfetti & Sandak, 2000). 3rd, although there is limited research on the benefits of classroom technologies other than CIs on long-term academic outcomes, a contempo large-scale study found the use of such educational technologies in the past to be associated with college academic attainment in terms of degree completion (Dammeyer et al., in press).
The present written report sought to bridge these three areas of enquiry by examining, in a big sample of college-leap deaf learners, possible associations among use of educational and assistive listening technologies, language abilities, and bookish accomplishment. Importantly, the report provided opportunities to determine whether classroom support services (i.e., technologies, interpreting, notetaking) and technology apply are associated with academic accomplishment equally well as academic attainment (as previously found by Dammeyer et al., in printing) and to replicate findings indicating that spoken language merely not CIs or sign language are associated with academic achievement amongst deaf high school students (Marschark et al., 2015). Based on recent research findings, spoken language skills were expected to exist a significant predictor of achievement among the high schoolhouse students in the present study. Looking alee, however, all of the high school students in the present sample were going to be attending a university with a specific focus on educating deaf students in a mainstream environment, a setting may be particularly attractive to better-qualified deaf students. Both signed and spoken language abilities thus might be predictors of academic achievement for that population (Marschark et al., 2015).
Method
Data
Anonymous data for this study were drawn from institutional records of 980 deafened high school students. 1 Data originally were collected from online questionnaires completed by students applying to college during their last 2 years of high schoolhouse. These students went on to enroll as undergraduates at a university in which approximately ix% of the educatee body has hearing losses sufficient to qualify them for educational support services. Students were from 46 U.S. states; 56% were males, and 37% were CI users. The variables examined from this questionnaire are listed in Table 1 with the number of consummate profiles, ways, standard deviations, and response ranges.
Table i.
Means and standard deviations (SD) for variables of interest
| N | Mean | SD | Range | |
|---|---|---|---|---|
| Academic variables | ||||
| Act Reading score | 827 | 19.77 | 6.22 | 9–36 |
| ACT Mathematics score | 827 | 19.75 | 5.00 | 11–36 |
| Human activity English score | 826 | 16.85 | 5.90 | half dozen–35 |
| ACT Science score | 827 | twenty.77 | 5.x | 7–36 |
| SAT Reading score | 292 | 473.60 | 121.78 | 200–800 |
| Saturday Mathematics score | 292 | 509.86 | 114.99 | 210–800 |
| ACT (ACT/Sabbatum) composite | 980 | nineteen.57 | v.07 | 11–35 |
| Communication variables | ||||
| PTA (dB) | 973 | 94.93 | 23.27 | 31–120 |
| Overall sign language skill | 980 | iii.65 | 1.37 | 1.0–5.0 |
| Overall spoken linguistic communication skill | 978 | 3.32 | 1.16 | 0.v–5.0 |
| Age of cochlear implantation | 366 | 6.28 | 4.66 | one.0–28.0 |
| Full language score | 978 | 6.97 | 1.24 | 2.5–x.0 |
| N | Hateful | SD | Range | |
|---|---|---|---|---|
| Academic variables | ||||
| ACT Reading score | 827 | 19.77 | 6.22 | 9–36 |
| ACT Mathematics score | 827 | nineteen.75 | five.00 | 11–36 |
| Act English language score | 826 | sixteen.85 | 5.90 | half dozen–35 |
| ACT Science score | 827 | 20.77 | 5.10 | 7–36 |
| Sat Reading score | 292 | 473.threescore | 121.78 | 200–800 |
| Sabbatum Mathematics score | 292 | 509.86 | 114.99 | 210–800 |
| ACT (ACT/SAT) composite | 980 | xix.57 | v.07 | xi–35 |
| Communication variables | ||||
| PTA (dB) | 973 | 94.93 | 23.27 | 31–120 |
| Overall sign language skill | 980 | three.65 | 1.37 | ane.0–five.0 |
| Overall spoken communication skill | 978 | 3.32 | 1.sixteen | 0.5–5.0 |
| Historic period of cochlear implantation | 366 | six.28 | four.66 | 1.0–28.0 |
| Total language score | 978 | 6.97 | one.24 | 2.5–x.0 |
Annotation. Human activity = American College Test; PTA = Pure Tone Average hearing loss averaged over both ears; SAT = Scholastic Assessment Test.
Table 1.
Means and standard deviations (SD) for variables of involvement
| N | Mean | SD | Range | |
|---|---|---|---|---|
| Academic variables | ||||
| Human activity Reading score | 827 | 19.77 | half-dozen.22 | 9–36 |
| ACT Mathematics score | 827 | xix.75 | 5.00 | xi–36 |
| Human activity English score | 826 | 16.85 | 5.90 | 6–35 |
| ACT Scientific discipline score | 827 | 20.77 | 5.10 | 7–36 |
| Sabbatum Reading score | 292 | 473.60 | 121.78 | 200–800 |
| Sabbatum Mathematics score | 292 | 509.86 | 114.99 | 210–800 |
| Human action (ACT/Sat) composite | 980 | 19.57 | 5.07 | 11–35 |
| Communication variables | ||||
| PTA (dB) | 973 | 94.93 | 23.27 | 31–120 |
| Overall sign language skill | 980 | 3.65 | 1.37 | ane.0–5.0 |
| Overall voice communication skill | 978 | three.32 | 1.16 | 0.v–v.0 |
| Age of cochlear implantation | 366 | 6.28 | 4.66 | one.0–28.0 |
| Total language score | 978 | 6.97 | 1.24 | two.5–10.0 |
| N | Mean | SD | Range | |
|---|---|---|---|---|
| Academic variables | ||||
| ACT Reading score | 827 | 19.77 | vi.22 | ix–36 |
| ACT Mathematics score | 827 | 19.75 | 5.00 | 11–36 |
| Human action English score | 826 | sixteen.85 | five.90 | half-dozen–35 |
| ACT Science score | 827 | 20.77 | 5.x | vii–36 |
| Sabbatum Reading score | 292 | 473.lx | 121.78 | 200–800 |
| Sabbatum Mathematics score | 292 | 509.86 | 114.99 | 210–800 |
| Human activity (Act/SAT) composite | 980 | nineteen.57 | 5.07 | 11–35 |
| Advice variables | ||||
| PTA (dB) | 973 | 94.93 | 23.27 | 31–120 |
| Overall sign language skill | 980 | 3.65 | 1.37 | 1.0–5.0 |
| Overall spoken language skill | 978 | three.32 | 1.16 | 0.5–5.0 |
| Age of cochlear implantation | 366 | half-dozen.28 | 4.66 | ane.0–28.0 |
| Total language score | 978 | vi.97 | 1.24 | 2.five–10.0 |
Annotation. Human action = American College Test; PTA = Pure Tone Boilerplate hearing loss averaged over both ears; Saturday = Scholastic Cess Test.
Academic data
In the Us, the American College Examination (ACT) and SAT (formerly the Scholastic Assessment Test) are 2 written, standardized tests of academic qualification used by colleges/universities in admission decisions. ACT English, math, reading comprehension, and science reasoning subtest scores were available for 826 or 827 individuals (Table ane). Scores on the ACT subtests range from i–36, and the total or composite Human action score is the average of the iv subtest scores as well ranging from 1–36. SAT reading and math subtest scores were available for only 292 individuals (both ACT and Sat scores were available for 138 individuals). 2 The sum of SAT subtests was converted to an equivalent Act composite score using concordance tables bachelor from the College Lath (2009). For individuals who took both the SAT and Human action, the college of the two scores was used. This provided Act composite scores for 980 individuals who comprised the dataset for subsequent analyses.
Communication information
As part of the college application process, students requesting support services associated with their hearing loss were required to submit audiograms. 4-frequency, pure tone boilerplate hearing thresholds (PTAs) averaged across both ears were available for 98% of individuals in the sample (Tabular array i). Students also completed the Language and Communication Background Questionnaire (LCBQ) online, which gathers information about communication skills, history, and preferences, and is used to determine service provision. Metz, Caccamise, and Gustafson (1997) found stiff positive correlations between self-rated sign linguistic communication and cocky-rated voice communication intelligibility on the LCBQ and formal, independent assessments of sign linguistic communication proficiency and speech intelligibility for young adults with hearing loss.
On the LCBQ, individuals rated their electric current communication skills on v-point Likert scales (Table i). Sign language skills ("Please rate your sign linguistic communication skills") were rated every bit fantabulous, skillful, fair, I understand a little, or I don't know sign language. Expressive spoken advice skills ("How well do yous think most hearing people sympathize your speech?") were rated every bit they understand everything I say, almost everything I say, about one-half of what I say, only a few words that I say, zero, and I don't use speech communication. Receptive spoken communication skills ("How well practise you understand speech when you both speechread and/or utilize your hearing?") were rated every bit everything people say, almost everything I say, about half, simply a few words, and nil. LCBQ data describing expressive and receptive skills in spoken linguistic communication were averaged to yield a single overall spoken linguistic communication score comparable to the overall sign language score. Individuals who indicated that they used sign language were asked the age they began learning sign language, given a option of 0–5 years old (n = 542, 55.3%), 6–xv years old (n = 196, twenty.0%), 16 years or older (due north = 106, 10.viii%), or I don't know sign language (n = 135, 13.8%). Information were missing for one individual (0.1%).
Devices, aids, and service use
Individuals were asked whether they had received a CI (yes/no) and the historic period of their (first or only) CI surgery. The mean historic period of implant surgery was 6.28 years, and the manner 3.00 years (Quartiles 25 = three.00, 50 = 5.00, 75 = 9.00). This is relatively late past current standards but accurately reflects the current accomplice of college-aged students. Information on whatever subsequent implants was not bachelor. The bulk of students reported not using a hearing aid (n = 436, 44.5%), with less reporting that they used a hearing aid all of the time (due north = 344, 35.1%), most of the fourth dimension (n = 82, 8.4%), about one-half of the fourth dimension (n = 47, iv.8%), and not oft (n = 71, 7.2%). Individuals who reported having a CI by and large had higher PTAs averaged across both ears (hateful = 111 dB, SD = x.half dozen, range 53–120 dB), that is, greater levels of hearing loss, than those who did not report having a CI (mean = 86.3 dB, SD = 21.9; range 31–120 dB). Because not all students with greater hearing losses used CIs or hearing aids, those devices and PTAs were considered separately in analyses described beneath.
Equally part of the college application procedure, individuals in the sample indicated in binary choices (yes/no) what kinds of classroom access services were provided to them in their well-nigh recent education placement: real-time text, FM systems, sign language interpreting, and/or notetaking (categories similar to Dammeyer et al., in press) (Table ii).
Table 2.
Aid and service use
| N | Yes | No | |
|---|---|---|---|
| Did you receive these services in your last schoolhouse: | |||
| Sign linguistic communication interpreting | 976 | 588 (sixty.2%) | 388 (39.8%) |
| Existent-time captioning | 976 | 162 (sixteen.5%) | 814 (83.1%) |
| FM system | 976 | 291 (29.7%) | 685 (69.9%) |
| Notetaking | 976 | 411 (41.9%) | 565 (57.7%) |
| N | Yeah | No | |
|---|---|---|---|
| Did y'all receive these services in your last school: | |||
| Sign language interpreting | 976 | 588 (sixty.two%) | 388 (39.8%) |
| Real-time captioning | 976 | 162 (xvi.five%) | 814 (83.ane%) |
| FM organisation | 976 | 291 (29.vii%) | 685 (69.9%) |
| Notetaking | 976 | 411 (41.9%) | 565 (57.7%) |
Tabular array ii.
Aid and service utilize
| N | Yes | No | |
|---|---|---|---|
| Did you receive these services in your terminal school: | |||
| Sign language interpreting | 976 | 588 (lx.2%) | 388 (39.8%) |
| Real-time captioning | 976 | 162 (16.5%) | 814 (83.1%) |
| FM organization | 976 | 291 (29.7%) | 685 (69.9%) |
| Notetaking | 976 | 411 (41.9%) | 565 (57.7%) |
| N | Yes | No | |
|---|---|---|---|
| Did yous receive these services in your last schoolhouse: | |||
| Sign language interpreting | 976 | 588 (60.ii%) | 388 (39.eight%) |
| Real-fourth dimension captioning | 976 | 162 (16.v%) | 814 (83.1%) |
| FM system | 976 | 291 (29.7%) | 685 (69.9%) |
| Notetaking | 976 | 411 (41.9%) | 565 (57.seven%) |
Results
Test of the extent to which the communication variables of interest predicted academic achievement first was analyzed in a stepwise multiple regression in which ACT composite scores were the benchmark variable; predictor variables were whether or not individuals had received a CI, whether they used hearing aids, PTA, cocky-reported spoken linguistic communication and sign linguistic communication skills, and the use of classroom support services (real-fourth dimension text, sign language interpreting, FM systems, notetaking). All and but those variables accounting for significant portions of the variance are described here. As tin be seen in Table 3, better spoken language skill was the best predictor of Human activity composite scores, accounting for approximately 10% of the variance, with smaller amounts of additional variance accounted for past the age at which individuals learned sign language (3%; subsequently acquisition associated with college achievement), use of sign linguistic communication interpreting in high schoolhouse (<1%), whether they had received a CI (<1%), and not using FM systems in loftier school (<1%). Like analyses were conducted using the same predictors and ACT reading scores (Table 3) and Act English language scores (Table 4), in turn, as criterion variables. When Human action reading scores served as the criterion variable, a regression yielded the aforementioned results as the previous analysis, with spoken language skill every bit the main predictor of the scores (10%) and minor amounts of additional variance accounted for by (later) historic period of sign linguistic communication acquisition (2%), the use of sign language interpreting (<1%), and nonuse of FM services (<ane%) in loftier school. With ACT English scores equally the criterion variable, spoken linguistic communication skill was the best predictor, bookkeeping for approximately xi% of the variance, followed by self-rated sign language skills (ii%), CI use (i%), and nonuse of FM systems in high schoolhouse (<ane%). Importantly, spoken language skills were a positive predictor of English language scores, while sign linguistic communication skills were a negative predictor.
Tabular array iii.
Regression (final) model results, R ii change and beta weights, predicting college entrance test (Act) scores
| Due north | R 2 | β | F change significance | |
|---|---|---|---|---|
| Composite ACT | 956 | |||
| Spoken linguistic communication skill | .10 | .23 | p = .000 | |
| Age learned to sign | .03 | .13 | p = .000 | |
| Interpreting in schoolhouse | .01 | .08 | p = .004 | |
| CI | <.01 | .08 | p = .013 | |
| FM system in school | <.01 | −.07 | p = .043 | |
| Reading | 810 | |||
| Spoken language skill | .10 | .25 | p = .000 | |
| Age learned to sign | .02 | .14 | p = .000 | |
| Interpreting in school | <.01 | .08 | p = .016 | |
| FM organisation in school | <.01 | −.09 | p = .017 | |
| English | 809 | |||
| Spoken language skill | .eleven | .23 | p = .000 | |
| Sign language skill | .02 | −.16 | p = .000 | |
| CI | .01 | .10 | p = .005 | |
| FM system in school | <.01 | −.08 | p = .021 | |
| Math | 810 | |||
| Sign linguistic communication skill | .06 | −.09 | p = .000 | |
| Speech skill | .01 | .15 | p = .000 | |
| Age learned to sign | <.01 | .ten | p = .036 | |
| Science | 810 | |||
| Sign linguistic communication skill | .06 | −.16 | p = .000 | |
| Spoken linguistic communication skill | .02 | .xv | p = .000 |
| N | R two | β | F alter significance | |
|---|---|---|---|---|
| Composite Human activity | 956 | |||
| Spoken language skill | .10 | .23 | p = .000 | |
| Age learned to sign | .03 | .13 | p = .000 | |
| Interpreting in school | .01 | .08 | p = .004 | |
| CI | <.01 | .08 | p = .013 | |
| FM system in school | <.01 | −.07 | p = .043 | |
| Reading | 810 | |||
| Spoken language skill | .ten | .25 | p = .000 | |
| Age learned to sign | .02 | .14 | p = .000 | |
| Interpreting in school | <.01 | .08 | p = .016 | |
| FM system in school | <.01 | −.09 | p = .017 | |
| English | 809 | |||
| Spoken language skill | .xi | .23 | p = .000 | |
| Sign language skill | .02 | −.16 | p = .000 | |
| CI | .01 | .10 | p = .005 | |
| FM system in schoolhouse | <.01 | −.08 | p = .021 | |
| Math | 810 | |||
| Sign linguistic communication skill | .06 | −.09 | p = .000 | |
| Speech communication skill | .01 | .15 | p = .000 | |
| Age learned to sign | <.01 | .10 | p = .036 | |
| Science | 810 | |||
| Sign language skill | .06 | −.16 | p = .000 | |
| Speech communication skill | .02 | .fifteen | p = .000 |
Tabular array iii.
Regression (concluding) model results, R 2 change and beta weights, predicting college entrance test (Deed) scores
| N | R two | β | F modify significance | |
|---|---|---|---|---|
| Composite ACT | 956 | |||
| Spoken language skill | .10 | .23 | p = .000 | |
| Age learned to sign | .03 | .13 | p = .000 | |
| Interpreting in school | .01 | .08 | p = .004 | |
| CI | <.01 | .08 | p = .013 | |
| FM system in school | <.01 | −.07 | p = .043 | |
| Reading | 810 | |||
| Spoken linguistic communication skill | .ten | .25 | p = .000 | |
| Historic period learned to sign | .02 | .14 | p = .000 | |
| Interpreting in school | <.01 | .08 | p = .016 | |
| FM organization in school | <.01 | −.09 | p = .017 | |
| English | 809 | |||
| Spoken language skill | .11 | .23 | p = .000 | |
| Sign linguistic communication skill | .02 | −.16 | p = .000 | |
| CI | .01 | .10 | p = .005 | |
| FM system in school | <.01 | −.08 | p = .021 | |
| Math | 810 | |||
| Sign language skill | .06 | −.09 | p = .000 | |
| Spoken language skill | .01 | .xv | p = .000 | |
| Age learned to sign | <.01 | .10 | p = .036 | |
| Scientific discipline | 810 | |||
| Sign language skill | .06 | −.16 | p = .000 | |
| Spoken communication skill | .02 | .15 | p = .000 |
| N | R 2 | β | F change significance | |
|---|---|---|---|---|
| Composite Deed | 956 | |||
| Speech skill | .10 | .23 | p = .000 | |
| Age learned to sign | .03 | .13 | p = .000 | |
| Interpreting in school | .01 | .08 | p = .004 | |
| CI | <.01 | .08 | p = .013 | |
| FM system in schoolhouse | <.01 | −.07 | p = .043 | |
| Reading | 810 | |||
| Spoken language skill | .10 | .25 | p = .000 | |
| Historic period learned to sign | .02 | .xiv | p = .000 | |
| Interpreting in school | <.01 | .08 | p = .016 | |
| FM organization in school | <.01 | −.09 | p = .017 | |
| English | 809 | |||
| Spoken language skill | .11 | .23 | p = .000 | |
| Sign language skill | .02 | −.xvi | p = .000 | |
| CI | .01 | .ten | p = .005 | |
| FM system in school | <.01 | −.08 | p = .021 | |
| Math | 810 | |||
| Sign language skill | .06 | −.09 | p = .000 | |
| Spoken linguistic communication skill | .01 | .15 | p = .000 | |
| Age learned to sign | <.01 | .10 | p = .036 | |
| Science | 810 | |||
| Sign language skill | .06 | −.sixteen | p = .000 | |
| Spoken language skill | .02 | .15 | p = .000 |
Students' mathematics and science ACT scores were examined every bit above. With ACT mathematics scores as the criterion variable, overall sign language skill (half dozen% of the variance) was the primary predictor, followed by overall spoken language skill (1%) and the age at which individuals learned sign language (<1%; see Table 3). Once again, whereas spoken language skill was a positive predictor of ACT mathematics scores, sign language skill was a negative predictor, and it was after rather than before acquisition of sign language that predicted a small amount of variance. When Human action science scores served every bit the benchmark variable, overall sign language skill (vi% of the variance) was the primary predictor, followed past overall spoken language skill (two%; see Table 3). Voice communication skill once again was a positive predictor of Human action mathematics scores, and sign language skill was a negative predictor.
While the positive prediction of achievement scores by deaf high schoolhouse students' spoken language skills is consistent with previous results, the negative prediction of English, mathematics, and science scores past their sign language skills was a surprising new finding. Those results left open, notwithstanding, the possibility that deafened students' bookish achievement might be related more to their general language skills (i.eastward., some combination of sign linguistic communication and spoken language skills) rather than their skills in any unmarried modality (Convertino et al., 2009; Rinaldi, Caselli, Onofrio, & Volterra, 2014). A full language score therefore was computed for each private by summing their spoken language and sign language scores. The median total communication score (x maximum) was 7.0. Using a median split up, independent sample t-tests were used to compare scores on the individual Human action subtest and ACT blended scores. None of the t-tests yielded significant results, 0.32 < t < 1.78, and that variable will not be considered further.
Discussion
The present study examined associations between academic accomplishment, language abilities, listening technologies, and back up services in a large accomplice of college-leap loftier school students in the U.s.a.. Consistent with previous studies involving high schoolhouse students, bookish achievement was positively related to students' spoken language skills but, if anything, negatively related to their sign language skills (DeLana et al., 2007; Marschark et al., 2015; Sarchet et al., 2014). Whether or non individuals used CIs or hearing aids contributed piffling to predicting accomplishment at the loftier school level, a finding consistent with U.S. national information from NLTS2 (Marschark et al., 2015). Reported utilize of back up services in loftier school (merely non the extent of such use) too deemed for little variance in accomplishment scores, with simply sign linguistic communication interpreting and FM contributing whatsoever at all (and the latter, negatively). The finding that technology apply in academic settings was not associated with high school students' achievement as measured by college entrance tests contrasts with the finding of (Dammeyer et al., in press) who found previous use of such technologies (at no specific time) related to level of degree attainment among adults. This departure might be explained past Dammeyer and Marschark's (2016) suggestion that different factors might contribute to academic accomplishment (due east.thou., parent education level, literacy and mathematic skills) and academic attainment (due east.g., effective communication strategies and self-advocacy in obtaining bookish back up services). Alternatively, Dammeyer et al.'s (in press) results may reflect apply of such technologies at academy rather than during high school or a difference between their availability and apply in Denmark as compared to the United States.
Hearing thresholds might be expected to be related to bookish accomplishment (Karchmer, Milone, & Wolk, 1979), even though they usually are confounded with communication modality (Allen & Anderson, 2010; Wagner, Marder, Blackorby, & Cardoso, 2002). PTAs did non account for significant amounts of variance in achievement in the present report. This finding is in line with previous big-scale studies that found PTAs either unrelated or but weakly related to academic measures from preschool (Dammeyer, 2014; Tymms, Brien, Merrell, Collins, & Jones, 2003) through high school and college historic period (Convertino et al., 2009; Marschark et al., 2015; Powers, 2003). Amid high schoolhouse students, Marschark et al. (2015) reported mild hearing loss was a meaning negative predictor of mathematics accomplishment, but moderate hearing loss was non a pregnant predictor of accomplishment in any of the domains tested.
A related merely also possibly counterintuitive finding from this study was the lack of a stronger relation betwixt CI utilise and achievement, as that variable accounted for only about 1% of the variance in ACT composite scores and English scores, and, most notably, no meaning variance in reading scores. As indicated earlier, yet, that finding is consistent with previous enquiry involving high school and college students, even if implant utilise is associated with improve reading achievement among immature children (Geers et al., 2008; Harris & Terlektsi, 2011; Marschark et al., 2015; Thoutenhoofd, 2006). That finding besides is complemented by the finding that students' sign language skills were not positively related to achievement. That result is consistent with previous, large-scale studies involving both high school students (Marschark et al., 2015) and higher students (Convertino et al., 2009). Those two studies failed to find any meaning relation between academic outcomes (achievement test scores and either college archway scores or classroom learning, respectively) and sign language skills or having deaf parents, even though they have been found associated with reading abilities among younger deaf children (Dammeyer, 2014; DeLana et al., 2007; Miller et al., 2012, 2015; Sarchet et al., 2014). The sign language skills obtained through bilingual instruction programming also have been found largely restricted to the elementary school years, even when big proportions of deafened students in those programs have deaf parents (Dammeyer & Marschark, 2016; Lange et al., 2013; Nover et al., 2002).
As described before, all 3 of these findings point to differences in the language, cognition, materials, and goals involved in academic operation during versus beyond the uncomplicated school years. They besides emphasize that historic period-appropriate linguistic communication skills amongst immature deafened children should not be taken as indicators that they no longer need support services as they move into subsequently grades. Rather, nosotros need to recognize that deafened learners volition continue to face less than optimal admission to advice and language throughout the school years, and perhaps beyond. At the point at which hearing children shift from learning to read to reading to learn (effectually 4th grade), for example, deaf children might continue to need reading pedagogy (Wauters, Van Bon, Tellings, & Van Leeuwe, 2006). More generally, the fact that voice communication continues to be a predictor of achievement in loftier school and beyond while sign linguistic communication and CI use exercise not suggest the demand for further research into the language abilities of older deafened learners and the means in which they interact with instructional methods and materials.
The relationship between sign language variables and academic achievement is worthy of note, if merely to emphasize the need for further research to clarify underlying relationships and implications. Later, not earlier sign language acquisition was associated with higher achievement scores, and in that location were negative relations between sign linguistic communication skill and science and math achievement scores among these college-bound high school students. Marschark et al. (2015) likewise institute use of sign language to exist a negative predictor of science and mathematics achievement scores when other factors were controlled (i.e., in multiple regression analyses). Information technology has been suggested that sign language might be more than beneficial than speech for explaining concepts in science and mathematics (Bauman & Murray, 2010). The extent to which that might exist true in whatsoever specific content areas remains to exist demonstrated, just such descriptions (eastward.yard., the length and width of a garden or Bauman & Murray's description of cell mitosis in a biology course) generally involve gesture rather than sign language per se.
Limitations and Future Research
The use of technology and school back up services were not found to impact academic accomplishment to the caste expected in the nowadays report. This lack of association may exist related to nuances that require farther investigation with more sensitive measures, for example, the corporeality of fourth dimension spent using engineering science (i.eastward., was real-time captioning available for all classes?) or at which ages/grades different technologies and support services were used. Information relevant to the use of engineering science and back up options at this level of detail was non available in the current study, and it difficult to meet how information technology could be obtained in any reliable manner across various school settings. In addition to examining such issues over the course of individuals' academic careers, studies involving various subpopulations of deaf learners also would be useful. The present study involved merely college-bound deaf students, who are presumably the highest academically-achieving students of all deaf students, on average, and used their higher entrance scores as indicators of achievement. Similar research might compare students who are and are non college-spring, using either secondary schoolhouse cumulative grade point averages or course rigor every bit indicators of achievement and workplace readiness.
Although the present findings are consistent with those from the more comprehensive, NLTS2 written report (Marschark et al., 2015), hereafter studies also would benefit from the comparison of the bear on of the variables examined in this report (e.chiliad., CI apply, historic period of sign language acquisition, linguistic communication skills) and the inclusion of more student (and family unit) demographic information than was available for this study. Understanding the effects of such factors at unlike points in fourth dimension (and for dissimilar subpopulations of deafened learners) as well as interactions amid them is an important goal for further research aimed at a better understanding of ways to support academic outcomes of deafened learners.
Determination
This study investigated the relationships between college-jump deafened students' academic achievement, communication characteristics, and apply of classroom applied science/back up. Meliorate cocky-reported spoken language skills was positively associated to achievement in some domains while amend self-reported sign language skills were related to poorer achievement in others. Consistent with other recent findings, employ of CIs accounted for very little variance (≤one%) in achievement scores at the high school level. Several other listening technologies and classroom access services surveyed did not contribute significantly at all to the prediction of achievement scores. Farther research is needed to explore what kinds of support work for various deaf learners in various educational settings.
Footnotes
1 Approximately 5% of the individuals included in the dataset appear to have taken i or more "gap years" between high school and college. Those individuals were left in the sample, but because it was unclear whether their admission tests were taken during or after high school, age was included in statistical analyses, as appropriate.
two Missing data were not replaced, hence degrees of freedom in analyses presented later will vary.
Funding
This research was supported in part by grant R01DC012317 from the National Institute on Deafness and Other Communication Disorders and a Fulbright scholarship from the Australian-American Fulbright Commission. Its contents are solely the responsibility of the authors and practice not necessarily represent the official views of NIDCD or NTID.
Conflict of Interest
No conflicts of interest were reported.
Acknowledgments
The authors wish to give thanks Richard Dirmyer and Denise Wellin for their assistance.
References
Allen
,
T. E.
, & Anderson Thou. Fifty.
2010
).
Deaf students and their classroom communication: An evaluation of higher order categorical interactions among school and background characteristics
.
Journal of Deafened Studies and Deaf Education
,
15
,
334
–
347
.
.
Ansell
,
E.
, & Pagliaro C. One thousand.
2006
).
The relative difficulty of signed arithmetic story bug for primary level deaf and hard-of-hearing students
.
Journal of Deaf Studies and Deafened Education
,
11
,
153
–
170
.
.
Archbold
,
S.
(
2015
). Existence a deaf student: Changes in characteristics and needs. In H. Knoors M. Marschark
Educating deafened learners: Creating a global testify base
(pp.
23
–
46
).
New York, NY
:
Oxford University Press
.
Dammeyer
,
J.
, Lehane C. Marschark M.
Bagga-Gupta
,
S.
(
2004
).
Literacies and deafened educational activity: A theoretical analysis of the international and Swedish literature
.
Stockholm, Sweden
:
The Swedish National Agency for School Comeback
.
Bauman
,
H.-D. L.
, & Murray J. J.
2010
). Deaf studies in the 21st century: "Deafened-proceeds" and the future of homo diversity. In Chiliad. Marschark P. E. Spencer
The Oxford handbook of deafened studies, linguistic communication, and education
(
Vol. 2
, pp.
210
–
225
).
New York, NY
:
Oxford University Printing
.
Blatto-Vallee
,
One thousand.
, Kelly R. R. Gaustad Thou. G. Porter J. Fonzi J.
2007
).
Spatial-relational representation in mathematical problem-solving by deaf and hearing students
.
Journal of Deafened Studies and Deaf Education
,
12
,
432
–
448
.
.
Borgna
,
G.
, Convertino C. Marschark Grand. Morrison C. Rizzolo K.
2011
).
Enhancing deaf students' learning from sign language and text: Metacognition, modality, and the effectiveness of content scaffolding
.
Periodical of Deaf Studies and Deaf Education
,
sixteen
,
79
–
100
.
.
Carlberg
,
C.
, & Kavale K.
1980
).
The efficacy of special versus regular grade placement for exceptional children
.
Journal of Special Education
,
xiv
,
295
–
309
.
Chung
,
I.
(
2016
, June). Characteristics of the language learning careers of deaf college students. Keynote address at the ACIC 2016 Conference, Tokyo Medical University, Tokyo, Nihon.
Convertino
,
C. Grand.
, Borgna G. Marschark M. Durkin A.
2014
).
Give-and-take and world knowledge among deaf students with and without cochlear implants
.
Journal of Deaf Studies and Deaf Instruction
,
19
,
471
–
483
.
.
Convertino
,
C. Thousand.
, Marschark M. Sapere P. Sarchet T. Zupan M.
2009
).
Predicting academic success amid deaf college students
.
Journal of Deaf Studies and Deaf Educational activity
,
fourteen
,
324
–
343
.
.
Damen
,
Grand. W.
, van den Oever-Goltstein M. H. Langereis Thou. C. Chute P. M. Mylanus Eastward. A.
2006
).
Classroom performance of children with cochlear implants in mainstream education
.
The Annals of Otology, Rhinology, and Laryngology
,
115
,
542
–
552
.
.
Dammeyer
,
J.
(
2014
).
Literacy skills amidst deaf and hard of hearing students and students with cochlear implants in bilingual/bicultural instruction
.
Deafness and Education International
,
16
,
108
–
119
.
.
Dammeyer
,
J.
, & Marschark Thousand.
2016
).
Level of educational attainment amidst deaf adults who attended bilingual-bicultural programs
.
Journal of Deaf Studies and Deaf Education
,
21
,
394
–
402
.
.
DeLana
,
M.
, Gentry Thousand. Andrews J.
2007
).
The efficacy of ASL/English bilingual education: Considering public schools
.
American Annals of the Deaf
,
152
,
73
–
87
.
.
Domínguez
,
A. B.
, Carrillo Chiliad. Southward. González V. Alegria J.
2016
).
How do deaf children with and without cochlear implants manage to read sentences: The key word strategy
.
Journal of Deaf Studies and Deaf Education
,
21
,
280
–
292
.
.
Easterbrooks
,
South. R.
, & Beal-Alvarez J. Due south.
2012
).
States' reading outcomes of students who are d/Deafened and hard of hearing
.
American Annals of the Deafened
,
157
,
27
–
forty
.
.
Fitzpatrick
,
Due east. M.
, Olds J. Gaboury I. McCrae R. Schramm D. Durieux-Smith A.
2012
).
Comparing of outcomes in children with hearing aids and cochlear implants
.
Cochlear Implants International
,
13
,
5
–
15
.
.
Geers
,
A. E.
(
2003
).
Predictors of reading skill development in children with early cochlear implantation
.
Ear and Hearing
,
24
,
59S
–
68S
.
.
Geers
,
A.
, Tobey E. Moog J. Brenner C.
2008
).
Long-term outcomes of cochlear implantation in the preschool years: From elementary grades to high school
.
International Periodical of Audiology
,
47 (Suppl 2)
,
S21
–
S30
.
.
Harris
,
M.
, & Terletski E.
2011
).
Reading and spelling abilities of deaf adolescents with cochlear implants and hearing aids
.
Periodical of Deaf Studies and Deaf Educational activity
,
16
,
24
–
34
.
.
Karchmer
,
M. A.
, Milone M. North. Wolk Due south.
1979
).
Educational significance of hearing loss at three levels of severity
.
American Annals of the Deaf
,
124
,
97
–
109
.
Kluwin
,
T.
, & Moores D. F.
1985
).
The result of integration on the achievement of hearing-impaired adolescents
.
Exceptional Children
,
52
,
153
–
160
.
Knoors
,
H.
, & Marschark Grand.
2014
).
Teaching deaf learners: Psychological and developmental foundations
.
New York, NY
:
Oxford University Press
.
Lange
,
C. M.
, Lane-Outlaw S. Lange Westward. E. Sherwood D. L.
2013
).
American Sign Language/English bilingual model: A longitudinal written report of bookish growth
.
Journal of Deaf Studies and Deaf Education
,
18
,
532
–
544
.
.
Leigh
,
G.
, & Crowe K.
2015
). Responding to cultural and linguistic diversity amid deafened and hard-of-hearing learners. In M. Marschark H. Knoors
Educating deaf learners: Global perspectives
(pp.
69
–
92
).
New York, NY
:
Oxford University Press
.
Leigh
,
Thou.
, & Marschark G.
2016
). Recognizing diversity in deaf instruction: From Paris to Athens with a diversion to Milan. In M. Marschark 5. Lampropoulou E. Skordilis
Diversity in deaf education
(pp.
1
–
20
).
New York, NY
:
Oxford University Press
.
Marschark
,
M.
, & Knoors H. H. Knoors Grand. Marschark
Evidence-based practice in deaf instruction
.
New York, NY
:
Oxford University Press
.
Marschark
,
M.
, Leigh Thou. Sapere P. Burnham D. Convertino C. Stinson G. Noble Due west.
2006
).
Benefits of sign language interpreting and text alternatives to classroom learning past deafened students
.
Journal of Deaf Studies and Deafened Educational activity
,
11
,
421
–
437
.
.
Marschark
,
Chiliad.
, Sapere P. Convertino C. Mayer C. Wauters L. Sarchet T.
2009
).
Are deaf students' reading challenges really about reading
.
American Annals of the Deaf
,
154
,
357
–
370
.
.
Marschark
,
M.
, Shaver D. M. Nagle K. Newman L.
2015
).
Predicting the academic accomplishment of deaf and difficult-of-hearing students from individual, household, communication, and educational factors
.
Infrequent Children
,
8
,
350
–
369
.
.
Marschark
,
M.
, Spencer Fifty. Durkin A. Borgna 1000. Convertino C. Machmer E. Trani A.
2015
).
Understanding linguistic communication, hearing condition, and visual-spatial skills
.
Journal of Deaf Studies and Deaf Teaching
,
20
,
310
–
330
.
.
Metz
,
D.
, Caccamise F. Gustafson M.
1997
).
Criterion validity of the langauge background questionnaire: A cocky-assesment musical instrument
.
Periodical of Communication Disorders
,
30
,
23
–
32
.
.
Miller
,
P.
, Kargin T. Guldenoglu B.
2015
).
Deaf native signers are amend readers than nonnative signers: Myth or truth
.
Journal of Deaf Studies and Deafened Education
,
xx
,
147
–
162
.
.
Miller
,
P.
, Kargin T. Guldenoglu B. Rathmann C. Kubus O. Hauser P. Spurgeon Due east.
2012
).
Factors distinguishing skilled and less skilled deafened readers: Evidence from 4 orthographies
.
Journal of Deaf Studies and Deaf Education
,
17
,
439
–
462
.
.
Niparko
,
J. K.
, Tobey Due east. A. Thal D. J. Eisenberg 50. Due south. Wang Due north.-Y. Quittner A. L. Fink Northward. E.
2010
).
Spoken language evolution in children following cochlear implantation
.
Journal of the American Medical Association
,
303
,
1498
–
1506
.
.
Nittrouer
,
Due south.
, & Caldwell-Tarr A.
2016
). Linguistic communication and literacy skills in children with cochlear implants: Past and present findings. In N. Young Yard. Kirk
Pediatric cochlear implantation: Learning and the brain
(pp.
177
–
197
).
New York, NY
:
Springer
.
Nover
,
S.
, Andrews J. Baker S. Everhart V. Bradford 1000.
2002
). ASL/English Bilingual didactics for deaf students: Evaluation and bear on study. Final report 1997–2002. Retrieved 2 April 2013 from: http://world wide web.gallaudet.edu/Documents/year5.pdf.
Padden
,
C. A.
, & Ramsey C.
2000
). American Sign Language and reading power in deaf children. In C. Chamberlain J. P. Morford R. I. Mayberry
Language conquering by center
(pp.
165
–
190
).
Mahwah, NJ
:
Lawrence Erlbaum Assembly
.
Perfetti
,
C. A.
, & Sandak R.
2000
).
Reading optimally builds on spoken language: Implications for deafened readers
.
Journal of Deaf Studies and Deaf Instruction
,
v
,
32
–
50
.
.
Powers
,
S.
(
2003
).
Influences of student and family factors on academic outcomes of mainstream secondary school students
.
Journal of Deaf Studies and Deafened Education
,
eight
,
57
–
78
.
.
Rinaldi
,
P.
, Caselli C. Onofrio D. Volterra V.
2014
). Linguistic communication acquisition by bilingual deaf preschoolers: Theoretical, methodological issues and empirical information. In M. Marschark 1000. Tang H. Knoors
Bilingualism and bilingual deaf education
(pp.
54
–
73
).
New York, NY
:
Oxford University Press
.
Rydberg
,
Due east.
, Gellerstedt 50. C. Danermark B.
2009
).
Toward an equal level of educational attainment betwixt deaf and hearing people in Sweden
.
Journal of Deaf Studies and Deaf Instruction
,
14
,
312
–
323
.
.
Sarchet
,
T.
, Marschark M. Borgna G. Convertino C. Sapere P. Dirmyer R.
2014
).
Vocabulary knowledge and meta-knowledge in deafened and hearing students
.
Journal of Postsecondary Education and Disabilities
,
17
,
161
–
178
.
Stinson
,
M. S.
(in press). Importance of engineering science for education of deaf students. In H. Knoors M. Marschark
Evidence-based exercise in deaf educational activity
.
New York, NY
:
Oxford University Printing
.
Stinson
,
M. S.
, Elliot L. B. Kelly R. R. Liu Y.
2009
).
Deaf and hard-of-hearing students' memory of lectures with speech-to-text and interpreting/note taking services
.
Periodical of Special Education
,
43
,
52
–
64
.
.
Stinson
,
Chiliad. Due south.
, & Kluwin T. N.
2011
). Educational consequences of alternative school placements. In G. Marschark P. Spencer
The Oxford handbook of deaf studies, linguistic communication, and didactics
(2nd ed.,
Vol. 1
, pp.
47
–
62
).
New York, NY
:
Oxford University Press
.
Stiff
,
G.
, & Prinz P.
1997
).
A study of the relationship between American Sign Language and English literacy
.
Periodical of Deaf Studies and Deafened Didactics
,
2
,
37
–
46
.
Swanwick
,
R.
, Hendar O. Dammeyer J. Kristoffersen A. Salter J. Simonsen Eastward.
2014
). Shifting contexts and practices in sign bilingual education in northern Europe: Implications for professional evolution and training. In Yard. Marschark Yard. Tang H. Knoors
Bilingualism and bilingual deaf education
(pp.
292
–
310
).
New York, NY
:
Oxford University Press
.
Thoutenhoofd
,
E.
(
2006
).
Cochlear implanted pupils in Scottish schools: 4-year school attainment data (2000–2004)
.
Periodical of Deaf Studies and Deaf Teaching
,
xi
,
171
–
188
.
.
Tymms
,
P.
, Brien D. Merrell C. Collins J. Jones P.
2003
).
Young deafened children and the prediction of reading and mathematics
.
Journal of Early Childhood Inquiry
,
1
,
197
–
212
.
.
Vermeulen
,
A. M.
, van Bon W. Schreuder R. Knoors H. Snik A.
2007
).
Reading comprehension of deaf children with cochlear implants
.
Journal of Deaf Studies and Deaf Education
,
12
,
283
–
302
.
.
Wagner
,
Yard.
, Marder C. Blackorby J. Cardoso D.
2002
).
The children we serve: The demographic characteristics of elementary and middle school students and their households
.
Menlo Park, CA
:
SRI International
.
Wauters
,
L. N.
, Van Bon Westward. H. J. Tellings A. E. J. M. Van Leeuwe J.
2006
).
In search of factors in deaf and hearing children's reading comprehension
.
American Annals of the Deaf
,
151
,
371
–
380
.
.
Willoughby
,
50.
(
2011
).
Sign language users' teaching and employment levels: Keeping stride with changes in the general Australian population
.
Journal of Deafened Studies and Deaf Education
,
16
,
401
–
413
.
.
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