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. 2023 Apr 24:1–22. Online ahead of print. doi: 10.1007/s10882-023-09910-y

Revisiting College Entry Testing to Increase Trained Deaf Teachers in the Classrooms

Millicent Musyoka 1,✉, Raymond Doe 1
PMCID: PMC10123014  PMID: 37361458

Abstract

Graduate Records Examinations (GRE) remain an important criterion for admission to the graduate program. This study explored the predictive role of the GRE for college success among deaf students because most deaf and hard-of-hearing students experience lifelong difficulties in English language and literacy because of their different language acquisition processes. Additionally, the study examined the students' undergraduate grade point average (UGPA), first-semester grade point average (FSGPA), and graduating graduate grade point average (GGPA) to understand D/HH students' performance in a graduate program. Additionally, the study examined the use of the Wechsler Adult Intelligence Scale (WAIS) as a substitute for the GRE criterion for graduate admission. The findings' discussions offer suggestions for using GRE scores in admitting D/HH students to graduate academic programs across the United States.

Keywords: GRE, GPA, WAIS, Deaf and Hard of Hearing, Teacher Preparation

Most graduate programs use the Graduate Records Examinations (GRE) scores to identify and admit candidates considered academically ready for graduate-level learning and less likely to struggle academically (Education Testing Service (ETS), 2019). The argument for using GRE as a program entry is that it provides an objective measure that applies to all candidates as opposed to other entry requirements, which may be subjective. ETS does not support a cut-off score based on only GRE scores as a sole criterion for denial of admission (ETS, 2019). According to ETS (2019), the three critical skills assessed in GRE needed in graduate programs include Analytical Writing, Verbal Reasoning, and Quantitative Reasoning. Verbal Reasoning focuses on how well an individual understands and can analyze, evaluate, and synthesize written information. Quantitative Reasoning examines one's mathematical skills, including arithmetic, algebra, geometry, and data analysis. Finally, Analytical Writing assesses an individual critical thinking and analytical writing skills. To demonstrate the three skills in GRE requires one to have a good command of English which is the language used in the assessment.

Opponents of the use of GRE as an entry requirement argue that GRE can undermine and underestimate the academic performance of minority groups, thus limiting their access and admission to graduate Education (Abedi, 2002; Ansell et al., 2018; Milner et al., 1984; Stricker, 2004; Stricker & Rock, 1995). According to Abedi (2002), most minority students, particularly English Language Learners (ELLs), have limited resources to learn the test material. Hence, ELLs tend to score lower when compared to English proficient peers (Abedi, 2009, 2014). Research noted that ELLs faced challenges with the large-scale standardized test (Abedi et al., 2002; Benet et al., 1985; Noble et al., 2014; Ragosta & Kaplan, 1986; Stricker, 2004). In particular, Stricker (2004) observed a challenge of using and interpreting English assessments to compare and admit both native English users and English language learners (ELL). Also, previous research show gender gap in the GRE performance which would impact the admission of female students in some graduate programs (Tock & Ericsson, 2019). The limitation presented regarding minority indicates a need for alternative documentation platforms that allow candidates to show attributes such as perseverance, creativity, and conscientiousness during interviews, exhibitions, or portfolios of their work. Alternative documentation includes letters of recommendation, personal statements, and GPA from previous course work from an accredited university.

D/HH students' group is one of the minority groups that GRE can undermine and underestimate their academic performance, thus limiting their access and admission to graduate education. Most D/HH students are not native English speakers and are ELLs. In addition, most D/HH students struggle with reading and writing English because of language delay or language deprivation they experience because most of them have non-signing hearing parents (Hall et al., 2017; Hile, 2009; Meek, 2020). As a result, most D/HH students arrive at school with limited language for learning and literacy development (Erting, 2001; Erting & Pfau, 1997). Due to language challenges, research shows that their reading by the time most D/HH students graduate high school reading below the fourth-grade level, and only 7–10% of D/HH high school graduates read at the seventh-grade level or above (Allen, 1986, 1994; Cawthon, 2004; Holt, 1994; Marschark et al., 2002; Strong & Prinz, 1997; Traxler, 2000; Wilbur, 2000). Also, research shows that D/HH students' math performance is lower than expected from grade-level hearing peers (Kritzer, 2009; Marschark et al., 2015; Mitchell, 2008; Traxler, 2000). Although research is lacking that focus on D/HH students' performance on GRE, there is little research on individuals with disabilities who have taken ETS standardized exams.

ETS Standardized Exams and Individual with Disabilities

According to ETS, individuals with disabilities receive testing accommodations, including extended time, extra breaks, screen magnification, and screen readers. The accommodation varies depending on the individual test taker's needs. There is limited research on GRE and individuals with disabilities (Ling et al., 2020). Ling et al. (2020) examined the validity of using the GRE General Test to assist with graduate school admissions for individuals with disabilities. They found no significant impact on the First-semester Graduate Grade Point Average (FGGPA), although it varied across various disabilities. Previous research that has focused on students with disabilities in standardized testing focuses on Scholastic Assessment Test (SAT) and reports challenges that vary across disabilities and the age of the onset of the disability (Benet et al., 1984; Braun et al., 1986; Ragosta & Kaplan, 1986; Ragosta & Nemceff, 1982). For instance, the correlation between Undergraduate Grade Point Average (UGPA) and SAT scores was lower for test-takers with a learning disability (Laitusis et al., 2002).

Previous studies have demonstrated that across all disabilities, D/HH students' performance was the lowest score in standardized testing (Benet et al., 1985; Jones & Ragosta, 1982; Ragosta & Nemceff, 1982). In most cases, the language of assessment was English, and most D/HH have low English literacy skills of D/HH students, which impacts their performance in the assessments (Luetke-Stahlman & Nielsen, 2003; Qi & Mitchell, 2012). Ragosta and Nemceff (1982) examined D/HH students' performance on SAT and reported that their scores were lower than those of students without disabilities (between 0.5 and 1.2 standard deviations). These findings concur with Benet et al. (1985), who reported that D/HH students scored lower than other groups with disabilities and students without disabilities by at least 0.5 standard deviations. D/HH students performed below the general test takers population on the verbal portion of the SAT (Benet et al., 1984, 1985; Jones & Ragosta, 1982; Ragosta & Kaplan, 1986). Mitchell and Cawthon (2014) questioned the 'fairness' and 'bias' of assessment tools and argued that "the performance differences that establish bias, by themselves, do not mean that a test is unfair. Bias only becomes unfairness when the reason for the differences is unrelated to the content of the test" (p. 2).

Research with D/HH students who are ELL reported difficulties related to vocabulary use, reading comprehension, and the quantity of the reading materials ((Luetke-Stahlman & Nielsen, 2003; Ragosta & Kaplan, 1986). D/HH students' performance on assessments varies with the diversity of demographic, age of hearing loss, the type of assessment, and educational placement (Braun et al., 1986; Cawthon, 2015a, b). Jones and Ragosta (1982) noted no differences in verbal scores of D/HH students based on their degree of hearing loss, but discrepancies occurred in the age of onset of hearing loss. Benet et al. (1985) found that D/HH students performed better on mathematical tests than verbal tests compared to non-disabled students. The correlational study by Jones and Ragosta (1982) reported a relationship between freshman GPA scores and SAT scores for 60 D/HH students. Also, they noted that combined high school GPA and SAT predicted freshman performance of D/HH students. Also, within the D/HH student population, Jones and Ragosta (1982) reported that pre-lingual D/HH students performed lower in SAT than post-lingual D/HH. Pre-lingual D/HH is an individual who becomes D/HH before language acquisition and development. On the other hand, post-lingual D/HH is an individual who becomes D/HH after acquiring and developing language.

Predictability of GRE in Graduate Education

In some graduate programs, GRE and UGPA are valid predictors of most graduate performance indicators (Kuncel et al., 2001). Despite this, studies have inconsistent findings and conflicting opinions on the GRE's ability to predict graduate performance (Kuncel et al., 2001). The ETS, which funds a considerable amount of research on the validity of the GRE, asserts that GRE General Test scores tend to show moderate correlations with first-year GPA averages (ETS, 2019). Several programs have argued for considering both UGPA and GRE scores. For example, McKee et al. (2001) reported that both UGPA and GRE scores predicted Graduating-semester Grade Point Average (GGPA) for master students in criminal justice. UGPA alone accounted for about 24% of the variance in GGPA, while (Graduate Records Examinations- Verbal) GRE-V explained the most variance (9.9%), Graduate Records Examinations-Analytical writing (GRE-A) (8.9%), and Graduate Records Examinations- Quantitative (GRE-Q) (6.9%). A total of 40% of the variance in GGPA was accounted for by the combination of UGPA and GRE scores.

Studies across various disciplines have indicated that GRE can be a predictor of 1st year GPA of graduate students (Holt et al., 2006; Powers, 2004; Sternberg & Williams, 1997). Powers (2004) reported that GRE scores and (UGPA) predicted 1st year GPAs of veterinary medical graduate students. Sternberg and Williams (1997) examined the predictive validity of the GRE for students in a graduate psychology program. They reported that GRE scores predicted students' GPA for the 1st year but not the 2nd year. Holt et al. (2006) indicated that GRE scores predicted students' first year and cumulative GPAs of master students in an engineering program. Their findings showed that both GRE-V and GRE-Q scores explained a significantly large portion of the variance than undergraduate GPA.

Previous studies have examined the predictive ability of GRE scores to graduate exit exams. For example, Schmidt et al. (2009) study on counseling graduate students found that UGPA, GRE-V, and GRE-Q scores predicted students' performance on the comprehensive exit examination. Of the three scores, GRE-V was the best predictor. Similarly, Stack and Kelley (2002) also studied the validity of GRE scores for master students in criminal justice. They reported that GRE-V was the better predictor of GGPA and accounted for 21% of the variance in GGPA. Another study reported both GRE scores and UGPA as strong predictors of academic performance, such as final GGPA, students' low grades, and incompletes (Reisig & DeJong, 2005).

On the other hand, various studies have shown that GRE does not predict students' GGPA and graduate education success (Feeley et al., 2005; Moneta-Koehler et al., 2017; Sternberg & Williams, 1997). Sternberg and Williams (1997) found that GRE was limited in predicting students' success in graduate school for psychology. According to Sternberg and Williams (1997), only the analytical subtest predicted any aspect of graduate success beyond the first-year GPA based on gender. She noted that the verbal subtest predicted only the first-year GPA. Feeley et al. (2005) examined the validity of GRE scores in predicting GGPA for students majoring in communication. They found that the UGPA was a better predictor of GGPA than the GRE for both masters and doctoral students. More recently, Moneta-Koehler et al. (2017) demonstrated that scores on the GRE are not predictive of success in biomedical graduate school. They reported a correlation between GRE and FSGPA. Hence, the literature review indicates inconsistencies in the ability of the GRE to predict graduate school students' performance. The literature review shows that GRE scores and UGPA have been used as one of the criterion admissions tests to predict graduate performance. The review does not mention D/HH students, hence the assumption that previous studies geared toward hearing candidates or students. Thus, more research was needed to address the gaps in previous graduate studies' entry requirements for D/HH students. The present study, therefore, tested the difference in the predictive validity of GRE scores between D/HH students and hearing students enrolled in a graduate program. In addition, the study considered the hearing loss and language issues prevalent among D/HH candidates in examining the predictive validity of GRE scores of hearing and D/HH students pursuing a masters in Deaf Education.

Methodology

Study Design and Data Collection

The current study focused on quantitative data drawn from the university's registrar databases that hold the applicants' Admission GRE scores, WAIS level, UGPA scores, FSGPA scores, and GGPA scores. The current study focused on graduate students who applied and pursued a deaf education graduate program. The minimum required UGPA for the program is 3.0. Although applicants are required to take GRE, there is no required standard score. For GRE, the students submitted three scores: Quantitative, Verbal, and Total.

Until recently, D/HH applicants were allowed to substitute GRE with the Wechsler Adult Intelligence Scale level (WAIS) for graduate admission. Hence, some D/HH applicants took WAIS while others opted for the GRE test. WAIS assessed the cognitive ability of adults by examining the relationship between intellectual functioning and memory for purposes of educational planning and placement (Climie & Rostad, 2011; Hershberger, 1997). The faculty argued that WAIS was an alternative fair test for D/HH students to overcome biases and challenges of language and literacy expectations of the GRE that D/HH students experienced. However, there were no scores for students who took the WAIS assessment. The psychologist interpreted the performance and assigned the candidates a qualification that used the words superior, high average, average, and low average; hence it was impossible to perform a quantitative analysis of the WAIS data. Applicants admitted to the graduate program had the labels superior and high averages.

Hence, data analyzed in the current study included GRE scores, WAIS level, First Semester GPA (FSGPA), and Graduating GPA(GGPA) for students who enrolled in the graduate program in Deaf Education from 2007 to 2018 to predict graduate student success. The grade point average measured graduate student success (GPA) scored after the first semester and at the end of the program. The university's student application records and transcripts provided the data. Data analysis included descriptive statistics means and standard deviations. Inferential statistics employed a t-test to compare D/HH students' and hearing peers' performance in the GRE. Also, the Pearson correlation determined the relationship between GRE scores, undergraduate GPAs, and graduating GPAs. Finally, the multiple regression determined the best predictor for both D/HH students and hearing students' achievement (GGPAs) in the master's program.

Participants

A total of 111 students' data was analyzed. Table 1 presents the descriptive results. The participants are graduate students from a program that implements an ASL/English bilingual philosophy intending to increase the population of teachers who are D/HH and from culturally and linguistically diverse backgrounds. Of the total number of students in the program, 67.6% were D/HH. Hence, the program's recruitment and retention strategy intentionally target D/HH students, resulting in a rare high number of D/HH students graduating from the program. The term D/HH represents students' self-identity as Deaf or Hard of hearing. All D/HH in the program identified themselves as ASL/English bilinguals. Also, Table 1 shows that most students were White (73.9%) and female (70.3%).

Table 1.

Descriptive results of D/HH students and hearing students in the study (N = 111)

Variable Description N (%)
Gender

Male

Female

33 (29.7)

78 (70.3)
D/HH or Hearing

D/HH

Hearing

75 (67.6)

36 (32.4)
Race

Caucasian

Black

Hispanic

American Indian

Asian

82 (73.9)

12 (10.8)

12 (10.8)

3 (2.7)

2 (1.8)
GRE or WAIS

GRE

WAIS

66 (59.5)

45 (40.5)
UGPA Undergraduate GPA 111 (100)
First Sem GPA

Completers of First Sem

In-completers of First Sem

85 (76.6)

26 (23.4)
Graduating GPA

Graduated the program

In-completers of the program

70 (63.1)

41 (36.9)
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Of the total 111 students, some did not have data on all the variables considered in the study. All students had UGPA. Some students with GRE or WAIS level and UGPA had missing FSGPA and GGPA scores. Students who missed FSGPA scores (26 students) were admitted into the program, enrolled, and withdrew before completing the first semester due to financial or other personal challenges. Also, other students did not have the graduating GGPA because they dropped out of the program before graduating. Table 1 shows that 41 of the 111 students did not have GGPA. The absence of the GGPA was because graduate students had to pass the teacher licensing exams to do internships and graduate. Some students could not pass the teacher licensing exam, and despite being offered an option to complete a master thesis instead of the teaching certification, they could not complete the thesis; hence they did not get the final GGPA. Most of the students who dropped out (in-completers of the program) were D/HH (37 D/HH and four hearing students). Also, of these 37 D/HH students, nine were Hispanic, three black, and 25 were White.

Hence, the results of each research question drew on different groups of students who had complete data for the question. For example, on the question on GRE predictability on the graduating GGPA, the analysis was conducted using data for only the students with GRE, UGPA, FSGPA, and GGPA scores.

Purpose of the Study

The study aimed to examine and compare the predictive ability of the GRE scores on the D/HH students and hearing students' outcomes in the master's in Deaf Education. During COVID-19, most graduate programs decided to offer a complete waiver or a temporal waiver of the GRE due to concerns and barriers associated with taking the online GRE at Home (Millar, 2020). Even before the pandemic, more graduate applicants are looking for schools that do not require GRE, and an increasing number of universities are joining the "GRExit" movement (Jaschik, 2016). The "GRExit" movement does not require GRE as part of the graduate application. Additionally, in the recent past, all D/HH students are required to take GRE and not WAIS. Currently, no research explains the WAIS and GRE use as part of entry requirements and the student's success.

Moreover, several D/HH applicants question the termination of WAIS and the requirement for GRE for both hearing and D/HH applicants. Consequently, the researchers sought to examine if GRE was a predictor of graduate student success and use the findings to make recommendations. Additionally, the researchers wanted to compare students' performance and academic success concerning WAIS and GRE to recommend whether the WAIS assessment was essential as a prerequisite for joining a graduate program for D/HH students.

Research Questions

The present study, therefore, focused on two major questions:

  1. What is the difference in the predictive validity of GRE scores between D/HH students and hearing students enrolled in a graduate program?

  2. How does hearing loss and language issues prevalent among D/HH candidates affect the predictive validity of GRE scores when pursuing a masters in Deaf Education in comparison to their hearing peers?

The research questions were organized in three parts to examine the students' application and admission, performance at the program's start (first semester), and performance at the end of the program (graduating semester). This article responded to the following research questions:

Students' Application and Admission

  1. Is there a significant difference between D/HH and hearing students' GRE scores?

  2. Is there a significant difference between D/HH and hearing students' UGPA scores?

  3. Is there a correlation between GRE scores and UGPAs across all students and separately for D/HH students?

Start of the Programs

  1. Is there a significant difference in the mean of first-semester graduate GPA(FGPA) for D/HH and hearing students?

  2. Is there a significant difference in the mean of first-semester graduate GPA(FGPA) for D/HH who took the GRE and those who took WAIS?

  3. Is there a correlation between first-semester graduate GPA and GRE score – across all students and separately for D/HH and hearing students?

  4. Is there a correlation between First Semester Graduate GPA and UGPA – across all students and separately for deaf and hearing students' GPA?

End of the Program

  1. Is there a significant difference in the mean of graduating GPA (GGPA) for D/HH and hearing students?

  2. Is there a significant difference in the mean of graduating GPA (GGPA) for D/HH who took the GRE and those who took WAIS?

  3. Is there a correlation between graduating GPA and GRE scores?

  4. Is there a correlation between graduating GPA and undergraduate GPA?

  5. Is there a correlation between graduating GPA and first-semester graduate GPA?

  6. What is the best predictor for students' achievement in the master's program in Deaf education?

Results

The normality of the data was checked and determined as normally distributed or approaching normality using the Shapiro-Wilks test and the Normal Q-Q plots. Data analysis answered the research questions (RQs) of interest. The analysis followed a timeline matching the students' progression through the program to provide more clarity to the reader. The three-time levels included the application process, the program's start, and the program's end.

Program Application and Admission

The research questions that guided the first part of the application process included:

RQ1: Is There a Significant Difference Between D/HH and Hearing Students' GRE Scores?

All the applicants submitted only the Quantitative and Verbal portions of the GRE test. We converted some students' old GRE scores into new GRE scores. Here is the table from ETS for converting Old to new scores.

https://www.qsleap.com/gre/resources/old-gre-to-new-gre-score-conversion

In answering this question, an independent samples t-test examined significant differences in GRE Quantitative, GRE Verbal, and GRE Total scores. The results showed a significant difference between D/HH students and hearing students in all GRE scores. Hearing students performed significantly better than Deaf students on all the GREs required to enter the program. The total GRE for hearing students (M = 291.5, SD = 9.96) was better than D/HH students (M = 281.93, SD = 11.89), t (64) = 3.56, p = .001 (See Table 2).

Table 2.

Results of t-tests for GRE Quant, GRE Verbal, and GRE Total by Hearing and D/HH Students

Outcome Group 95% CI for Mean Difference
D/HH
(n = 30)		 Hearing
(n = 36)
M SD M SD t df p d
GRE Q 140.07 4.77 143.56 5.09 -5.93, -1.05 -2.85 64 .006 .71
GRE V 141.87 9.45 147.97 6.41 -10.18, -2.03 -3.11 64 .004 .76
GRE T 281.93 11.89 291.50 9.96 -14.94, -4.19 -3.56 64 .001 .87
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RQ2: Is There a Significant Difference Between D/HH and Hearing Students' UGPA Scores?

An independent-samples t-test compared UGPA for D/HH students and hearing students. The results showed there was a significant difference in UGPA scores for D/HH (M = 3.11, SD = 0.42) and hearing (M = 3.39, SD = 0.34); t (109) = 3.62, p < .001. The hearing students had significantly higher UGPA than D/HH students (see Table 3).

Table 3.

Results of t-tests for UGPA by Hearing and D/HH Students

Group Max Min M SD t df p
Deaf (n = 75) 4.0 2.5 3.11 0.42 3.62 109  < .001
Hearing (n = 36) 4.0 2.58 3.39 0.34
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RQ3. Is There a Correlation Between GRE Scores and UGPAs Across All Students and Separately for D/HH Students?

  1. A Pearson Correlation assessed the relationship between GRE scores and undergraduate GPAs – across all students. The results, as shown in Table 4, indicate that:
    1. There was a significant relationship between GRE Total scores and total UGPA scores (r = .282, p = .024).
    2. There was a significant relationship between GRE Total scores and GRE Quantitative scores (r = .775, p < .001).
    3. There was a significant relationship between GRE Total scores and GRE Verbal scores (r = .921, p < .001).
    4. There was a significant relationship between GRE Quantitative scores and GRE Verbal scores (r = .468, p < .001).
    5. There was no significant relationship between UGPA and GRE Verbal scores (r = .243, p = .053).
    6. There was a significant relationship between UGPA and GRE Quantitative scores (r = .249 p = .047).

  2. A Pearson Correlation was computed to assess the relationship between GRE scores and undergraduate GPAs for hearing students. For hearing the students, the results showed a significant relationship between all GRE scores and UGPA except UGPA and GRE Quantitative scores (see Table 5).

  3. A Pearson Correlation was also computed to assess the relationship between GRE scores and undergraduate GPAs for D/HH students. For D/HH students, the results showed that the UGPA did not correlate with GRE Total, GRE Quantitative, and GRE Verbal scores (see Table 6).

Table 4.

Summary of Correlations Between GRE Quantitative, GRE Verbal, GRE Total, and UGPA - Across All Students

n M SD 1 2 3 4
1. GRE Total 66 287.1515 11.81426 -
2. GRE Quant. 66 141.9697 5.21232 .775** -
3. GRE Verbal 66 145.1970 8.44752 .921** .468** -
4. UGPA 109 3.19848 .420165 .282* .249* .243 -
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*p < .05; **p < .01; ***p < .001

Table 5.

Summary of Correlations Between GRE Quantitative, GRE Verbal, GRE Total, and UGPA - Hearing Students

n M SD 1 2 3 4
1. GRE Total 36 291.5000 9.96135 -
2. GRE Quant. 36 143.5556 5.09030 .828** -
3. GRE Verbal 36 147.9722 6.41198 .896** .494** -
4. UGPA 35 3.38114 .365423 .341* .203 .371* -
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*p < .05; **p < .01; ***p < .001

Table 6.

Summary of correlations between GRE Quantitative, GRE Verbal, GRE Total, and UGPA - D/HH Students

n M SD 1 2 3 4
1.GRE Total 30 281.9333 11.89301 -
2.GRE Quant. 30 140.0667 4.77012 .660** -
3.GRE Verbal 30 141.8667 9.44944 .925** .326 -
4.UGPA 74 3.11208 .418834 .168 .236 .093 -
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*p < .05; **p < .01; ***p < .001

Start of the Programs

RQ4. Is There a Significant Difference in the Mean of First-Semester Graduate GPA (FGPA) for D/HH and Hearing Students?

An independent-sample t-test compared FGPA for all D/HH students and hearing students. The results did not show any significant differences in students' first-semester GPA scores. That is, D/HH students (M = 3.64, SD = .55) performed about the same as hearing students (M = 3.71, SD = .49), t (83) = .532, p = .596.

RQ5. Is There a Significant Difference in the Mean of First-Semester Graduate GPA (FGPA) for D/HH Who Took the GRE and Those Who Took WAIS?

The D/HH students' sample included both students who took GRE and the WAIS test. An independent-sample t-test compared FGPA for D/HH students who took GRE and D/HH students who took the WAIS test. The results did not show significant differences in the students' first GPA scores. That is, for D/HH students who took GRE (M = 3.78, SD = .32) performed about the same as D/HH who took WAIS (M = 3.58, SD = .61), t (57) = .1.26, p = .213.

RQ6. Is There a Correlation Between First-Semester Graduate GPA and GRE Score – Across All Students, and Separately for D/HH and Hearing Students?

  1. Correlation across all students

    A Pearson Correlation assessed the relationship between GRE scores and Semester 1 GPAs for all students. There was a low negative correlation between Sem 1 GPA scores and GRE Quantitative scores for all students. The findings suggest that students' Semester 1 GPA scores were high even for those with low GRE Quant GRE Quantitative scores (see Table 7).

  2. Correlation between D/HH students

    Similarly, a Pearson Correlation assessed the relationship between GRE scores and Semester 1 GPAs for D/HH students. There was no significant correlation between Semester 1 GPA and GRE scores (GRE Total, GRE Verbal & GRE Quantitative) for D/HH students. The findings showed that D/HH students had high Semester 1 GPA scores even when admitted with low GRE scores (see Table 8).

  3. Correlations between hearing students

    A Pearson Correlation assessed the relationship between GRE scores and Semester 1 GPAs for hearing students to compare the results. The results showed a negative correlation between Semester 1 GPA and GRE Quantitative scores for hearing students. The findings indicated that hearing students' Semester 1 GPA can be high even for students with low GRE Quant. Hearing students' performance in Semester one had an impact compared to their entry GRE Quantitative scores. The finding indicated that student performance in the first semester in graduate school contributed to them graduating early and with higher GPAs even when their total GRE scores were low. D/HH students' data did not demonstrate this finding (Table 9).

Table 7.

Summary of correlations between GRE Quantitative, GRE Verbal, GRE Total, and First Semester FGPA - Across all students

n M SD 1 2 3 4
1. GRE Total 66 287.1515 11.81426 -
2. GRE Quant. 66 141.9697 5.21232 .775** -
3. GRE Verbal 66 145.1970 8.44752 .921** .468** -
4. Sem 1 GPA 85 3.6619 .52872 .109 -.084 .201 -
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*p < .05; **p < .01; ***p < .001

Table 8.

Summary of correlations between GRE Quantitative, GRE Verbal, GRE Total, and First Semester FGPA - D/HH students

n M SD 1 2 3 4
1. GRE Total 30 281.9333 11.89301 -
2. GRE Quant. 30 140.0667 4.77012 .660** -
3. GRE Verbal 30 141.8667 9.44944 .925** .326 -
4. Sem 1 GPA 59 3.6415 .54876 .157 .144 .141 -
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*p < .05; **p < .01; ***p < .001

Table 9.

Summary of correlations between GRE Quantitative, GRE Verbal, GRE Total, and First Semester FGPA - Hearing students

n M SD 1 2 3 4
1. GRE Total 36 291.5000 9.96135 -
2. GRE Quant. 36 143.5556 5.09030 .828** -
3. GRE Verbal 36 147.9722 6.41198 .896** .494** -
4. Sem 1 GPA 26 3.7081 .48729 .150 -.128 .335 -
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*p < .05; **p < .01; ***p < .001

RQ7. Is There a Correlation Between First Semester Graduate GPA and UGPA – Across All Students and Separately for Deaf and Hearing Students' GPA?

  1. A Pearson Correlation was computed to assess the relationship between First Semester Graduate GPA and UGPA for all students. There was no significant relationship between first-semester graduate GPA and UGPA – across all students, r = .199, p = .068.

  2. A Pearson Correlation was computed to assess the relationship between First Semester Graduate GPA and UGPA for deaf students. There was no significant relationship between first semester graduate GPA and UGPA for D/HH students, r = .173, p = .190.

  3. A Pearson Correlation was computed to assess the relationship between First Semester Graduate GPA and UGPA for hearing students. There was no significant relationship between first-semester graduate GPA and UGPA for hearing students, r = .246, p = .227.

End of the Program

RQ8. Is There a Significant Difference in the Mean of Graduating GPA (GGPA) for D/HH and Hearing Students?

An independent-sample t-test compared Graduating GPA (GGPA) for D/HH students and hearing students. The results showed there was no significant difference in the mean of graduating GPA (GGPA) for D/HH (M = 3.72, SD = 0.27) and hearing (M = 3.81, SD = 0.29); t (68) = 1.175, p = .244.

RQ9. Is There a Significant Difference in the Mean of Graduating GPA (GGPA) for D/HH Who Took the GRE and those Who Took WAIS?

An independent-sample t-test compared Graduating GPA (GGPA) for D/HH who took GRE and those who took WAIS. The results showed there was no significant difference in the mean of graduating GPA (GGPA) for D/HH who took GRE (M = 3.80, SD = 0.23) and D/HH who took WAIS (M = 3.69, SD = 0.28); t (47) = 1.416, p = .163.

RQ10. Is There a Correlation Between Graduating GPA and GRE Scores?

A Pearson Correlation assessed the relationship between GRE scores and Graduating GPAs across all students. There was no significant correlation between Graduating GPA and GRE scores (GRE Total, GRE Verbal & GRE Quantitative). Students in the Graduate Deaf education program can have high Graduating GPA scores even when they were admitted with low GRE scores (see Table 10).

Table 10.

Summary of correlations between GRE Quantitative, GRE Verbal, GRE Total, and Graduating GPA (GGPA) - Across all students

n M SD 1 2 3 4
1. GRE Total 66 287.1515 11.81426 -
2. GRE Quant. 66 141.9697 5.21232 .775** -
3. GRE Verbal 66 145.1970 8.44752 .921** .468** -
4. Grad GGPA 70 3.7466 .27866 .132 .121 .118 -
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*p < .05; **p < .01; ***p < .001

RQ11. Is There a Correlation Between Graduating GPA and Undergraduate GPA?

A Pearson Correlation assessed the relationship between graduating GPA and undergraduate GPA across all students. There was no significant relationship between first-semester graduate GPA and UGPA for hearing students, r = .158, p = .191.

RQ12. Is There a Correlation Between Graduating GPA and First-Semester Graduate GPA?

A Pearson Correlation assessed the relationship between graduating GPA and first semester GPA across all students. There was a significant positive relationship between first graduating GPA and first semester GPA, r = .725, p < .001.

RQ13. What is the Best Predictor for Students' Achievement in the Master's Program in Deaf Education?

Multiple regression determined the best predictor for D/HH and hearing students' achievement in the master's program. The hierarchical regression model showed that the best predictor explaining 52.6% of the variance in graduating GGPA is students' first semester's GGPA (see Table 11).

Table 11.

Summary of Hierarchical Regression Analysis for Variables predicting student achievement (GGPAs)

b SE b β t
Step 1
Constant 3.411 .256
UGPA .105 .079 .158 1.320
Step 2
Constant 2.322 .222
UGPA .010 .057 .015 .171
Sem 1 GGPA .380 .045 .722 8.409***
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R2 = .025 for Step 1: ΔR2 = .501 for Step 2

***p < .001

Discussion

The current study occurred in a university graduate program that adopts an ASL/English approach and ensures communication and language access to both hearing and D/HH students. All students and faculty are required to be proficient and use ASL as the language of instruction. Comprehensible language access allowed D/HH students communication and social interaction opportunities in and out of the class sessions. Most applicants who demonstrate the required proficiency skills in ASL tend to be individuals who are D/HH who are ASL users. Hence, the descriptive statistics indicated a high percentage of D/HH students compared to hearing students. In this section, the discussion will highlight the key findings based on the research questions.

Most deaf applicants' GRE scores in this study were significantly low, indicating that GRE may not be an accurate assessment for the decision to enroll Deaf applicants to graduate school or even to assess their success in graduate studies. ETS (Educational Testing Services, 2008) reported that minority students typically received significantly lower GRE scores which may explain the Deaf applicants' scores as a minority group. Specifically focusing on Deaf as a student with disabilities, there is limited research on GRE and students with disabilities, and most of the studies that focused on testing college entry exams such as GRE and SAT taken by applicants with disabilities occurred almost 40 years ago (Benet et al., 1984; Benet et al., 1985; Braun et al., 1986; Ragosta & Kaplan, 1986; Ragosta & Nemceff, 1982). A more recent survey examined the predictive ability of GRE scores for graduate students with disabilities compared to those without disabilities (Ling et al., 2020).

The current study concurred with the previous research findings that there was a significant difference between students with disabilities and those without disabilities. Ling et al., (2020) showed that the significant difference between students with and without disabilities was on GRE Quantitative but not for GRE Verbal and GRE Analytical Writing. Ragosta and Nemceff (1982) reported on the differences in the performance of D/HH and non-disabled students on SAT. D/HH students had lower scores compared to their non-disabled peers. Ling et al. (2020) and Ragosta and Nemceff's (1982) studies did not provide information on Deaf participants' hearing level and the mode of communication, whether spoken or sign language.

Separating scores in GRE-V and GRE-Q in the analysis between different subgroups in this study enabled the researchers to understand the unique characteristics of D/HH students and hearing students' performance on the test. The difference was apparent in GRE-V, which requires a high level of English proficiency (Educational Testing Services, 2013). The low performance on GRE-V is similar to the findings reported on SAT, in which D/HH students reported difficulties related to vocabulary use, reading comprehension, and the quantity of the reading materials (Ragosta & Kapla, 1986).

Previous research on standardized testing indicates that D/HH students experience challenges that can impact their performance because most testing lack accommodation for language delay and competence (Cawthon, 2011, 2015a, b; Cawthon & Leppo, 2013; Luft, 2020; Qi & Mitchell, 2012). According to Qi and Mitchell, testing D/HH in a spoken language such as English impedes their ability to articulate their content knowledge. Cawthon (2011) argued that when it comes to assessment and DHH students, the main issues include access to the test content, maintaining the test score validity, and D/HH students' linguistic and communication needs. In most cases, standardized testing, including GRE, and accommodation of extended time, does not explicitly address the limited background in the test and the D/HH students' language and communication needs (Cawthon, 2011). Similar to other standardized tests, deaf students' performance in GRE compared to their hearing peers may be explained by their language challenges and access to the content.

The current study showed no significant correlation between D/HH students' GRE quantitative scores and GRE verbal scores. This finding is inconsistent with previous research, which indicated that D/HH students performed low in the verbal section and had higher scores in the mathematical section (Benet et al., 1985; Ragosta & Kaplan, 1986). Also, Ling et al. (2020), reported that D/HH performed better in GRE Verbal than in GRE Quantitative. Previous studies on D/HH students' performance in SAT scores explain that this inconsistency can be due to students' educational placement (Braun et al., 1986). Most participants in the current study attended an educational program for D/HH students in K-12 and at the college level, which provided them with direct access. Cummins's (1991) language interdependence hypothesis posits that language and literacy skills learned in the first language could be transferred to the second language. Based on Cummins (1991), we can assume that D/HH students in this study transferred their ASL language skills into understanding English skills used for the GRE assessment.

Although Deaf and hearing students' data showed a significant difference in their GRE performance and UGPA the data showed no significant difference between D/HH students and hearing students in their first-semester Graduate GPA and graduating GPA. Previous studies on undergraduates did not cite academic performance, but D/HH students identified communication and social issues as the main block in their education completion (Foster et al., 1999; Saur et al., 1987; Stinson et al., 1996). Communication and social issues can result in a 25% graduation rate reported for D/HH undergraduates in the United States (Lang, 2002; Stinson & Walter, 1992, 1997). The graduate students who participated in the current study did not express communication and social issues because they had access to both ASL and English for social and academic use. In addition, most of the students in the program were D/HH students.

The Pearson correlation coefficients indicated no significant relationships between GRE scores and GGPA but showed a negative correlation to the First semester GPA. First, the findings were consistent with previous findings on the predictive ability of GRE that also found that GRE was not a strong predictor of graduate performance (Feeley et al., 2005; Kuncel et al., 2001; Moneta-Koehler et al., 2017; Sternberg & Williams, 1997). Also, the current findings concur with Braun et al. (1986). They reported that SAT scores for high school Deaf students had little to no correlation to their college education although the SAT scores over-reported correlation to all other students with disabilities on their performance in college. On the other hand, the current study found that students First semester GPA accounted for more than 50% of the variance in GGPA. Previous studies have reported the predictability of UGPA to GGPA (Feeley et al., 2005; Ling et al., 2020). Other studies indicated that the combination of GRE scores and UGPA strongly predicts graduate GGPA (Burton & Wang, 2005).

In conclusion, although GRE is a standardized test designed to determine the academic potential of graduate students and is widely used in graduate admission decisions by many universities and institutions in the United States, it was not a predictor of D/HH students' graduate academic performance. Also, with the mixed findings on the predictability of GRE, there is a demand for higher education institutions to be more conscious when making graduate admission applications for students with disabilities, particularly Deaf.

Limitations of this Study

There are three main limitations of this study. The first limitation is that this study targeted candidates in a unique Deaf Education program that embraced an ASL/English bilingual approach. Due to the nature of the program, most students are D/HH and previously attended a special school for the D/HH in K-20, where they had access to a comprehensible language. Participants with diverse backgrounds may provide representative results in the performance of the GRE by D/HH students and an explanation of the validity of the GRE for D/HH students seeking admission to a graduate program. Hence, the generalization of the findings of this study to other disciplines should be made cautiously, with careful consideration given to D/HH students' language access and use.

The second limitation concerns the sample size and available data used in the analysis. Some participants did not have data on all the variables considered in the study. For example, all the participants had GRE or WAIS levels and UGPA scores. However, some participants did not have FGGPA and GGPA. Hence, the results of each research question align with the different data sets drawn from groups of students who had complete data for a particular question.

The third limitation is the absence of a complete GRE data set; The GRE includes three parts GRE Quantitative, GRE Verbal, and GRE Analytical Writing. In the current study, the applicants did not submit scores on GRE Analytical writing. The graduate program performed its writing assessment for the applicants and destroyed the writing assessment scripts upon admission. Also, the qualitative interview committee writing assessment rubric labeled applicants' writing as average, above average, excellent or unacceptable.

Implications and Recommendations for Future Research

This study has some implications to policy on graduate admission decisions for Deaf Education programs and graduate programs admitting D/HH students. First, the study provided means for GRE scores for D/HH and hearing students, which can guide decisions on possible cut-off scores for admission into the Deaf Education program. Also, there is a need of a policy that guide institutions of higher education to be aware of D/HH applicants' low performance on GRE compared to their hearing peers when making decisions on cut-off points so as not to blindly compare them with their hearing peers.

Additionally, since GRE was not a good predictor for graduating GGPA; hence, there is a need for caution when using it to decide on graduate admission to a Deaf Education program. For example in Fall 2020, in the midst of the COVID-19 pandemic, Graduate students were admitted without GRE. Alternative entry requirements such writing sample and interviews used supplemented the absence of the GRE scores. These students progressed well and are now graduating to work in schools as teachers of D/HH students. Hence, the findings from this study call for higher education institutions to consider alternative requirements for D/HH students' admissions into graduate school in addition to the GRE scores if used. With all the findings reported on the relationships between GRE, UGPA, FSGPA, and GGPA, there is a need for a tool that focuses on assessing D/HH applicants' academic ability to pursue graduate school, particularly in teacher education.

Deaf Education graduate programs should re-evaluate requiring GRE scores as part of their admission criteria or use it as the only criterion to admit or not admit. Instead, they should design other forms of admission assessment to supplement the GRE scores. For example, the current study missed scores on GRE Analytical writing not previously collected as part of the criteria. Writing is a challenge for many D/HH students (Antia et al., 2005; Mayer & Trezek, 2019); hence it is important to know the writing ability of Deaf college applicants. More practical entry assessments suggested may include an interview with the admission committee, a written personal statement, an applicant e-portfolio, a sample publication, ASLPI testing, and a detailed resume exhibiting students' previous work and achievement in the field of Deaf Education.

The current data is quantitative; hence, conducting a qualitative will help the field of Deaf education to understand D/HH individuals' experience taking GRE. Also, future studies should examine how variables such as D/HH applicants' previous education placement, high school SAT scores, and language and communication choice may impact their GRE and GGPA. Additionally, future studies ought to examine the challenges graduate D/HH students experience as they pursue their graduate studies.

Compliance with Ethical Standards

Ethical Approval

The University IRB judged the study as not involving human subjects research and did not require IRB approval. In addition, the study used collected data in the university system. Hence the study was granted an exemption from requiring ethics approval.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Millicent Musyoka, Email: mmusyoka@lamar.edu.

Raymond Doe, Email: rdoe@lamar.edu.

References

  1. Abedi J. Standardized achievement tests and English language learners: Psychometric issues. Educational Assessment. 2002;8(3):231–257. doi: 10.1207/S15326977EA0803_02. [DOI] [Google Scholar]
  2. Abedi, J. (2009). English language learners with disabilities: classification, assessment and accommodation issues. Journal of Applied Testing Technology, 10(2), 1–30.
  3. Abedi J. The use of computer technology in designing appropriate test accommodations for English language learners. Applied Measurement in Education. 2014;27(4):261–272. doi: 10.1080/08957347.2014.944310. [DOI] [Google Scholar]
  4. Allen, T. E. (1994). Who are the Deaf and hard-of-hearing students leaving high school and entering postsecondary education? Unpublished manuscript. Washington, DC: Gallaudet University Center for Assessment and Demographic Studies. http://research.gallaudet.edu/AnnualSurvey/whodeaf.php
  5. Allen, T. (1986). Patterns of academic achievement among hearing impaired students: 1974 and 1983. In A. N. Schildroth, & M. A. Karchmer (Eds.), Deaf children in America (pp. 161–206). San Diego: College-Hill Press.
  6. Ansell, E., Cassidy, B., Gardner, K., Marra, K., & Tokowicz., N. (2018). Graduate Record Examination Use Survey. The University of Pittsburgh’s Senate Equity, Inclusion, and Anti-Discrimination Advocacy Committee’s Education Working Group. https://www.univsenate.pitt.edu/sites/default/files/EIADAC_Survey_Summary_FAll_2018%20Final.pdf
  7. Antia, S. D., Reed, S., & Kreimeyer, K. H. (2005). Written language of deaf and hard-of-hearing students in public schools. Journal of Deaf Studies and Deaf Education,10(3), 244–255. 10.1093/deafed/eni026 [DOI] [PubMed]
  8. Benet RE, Ragosta M, Stricker L. The test performance of handicapped people. Educational Testing Service; 1984. [Google Scholar]
  9. Benet RE, Rock D, Kaplan B. The internal psychometric characteristics of the SAT for the nine handicapped groups. Educational Testing Service; 1985. [Google Scholar]
  10. Braun H, Ragosta M, Kaplan B. The predictive validity of the scholastic aptitude test for disabled students. Educational Testing Service; 1986. [Google Scholar]
  11. Burton N, Wang M. Predicting long term success in graduate school: A collaborative validity study. ETS Research Report Series. 2005;1:i–61. doi: 10.1002/j.2333-8504.2005.tb01980.x. [DOI] [Google Scholar]
  12. Cawthon S. Schools for the Deaf and the No Child Left Behind Act. American Annals of the Deaf. 2004;149:314–323. doi: 10.1353/aad.2005.0002. [DOI] [PubMed] [Google Scholar]
  13. Cawthon SW. Making Decisions About Assessment Practices for Students Who Are Deaf or Hard of Hearing. Remedial and Special Education. 2011;32(1):4–21. doi: 10.1177/0741932509355950. [DOI] [Google Scholar]
  14. Cawthon S. From the Margins to the Spotlight: Diverse Deaf and Hard of Hearing Student Populations and Standardized Assessment Accessibility. American Annals of the Deaf. 2015;160(4):385–394. doi: 10.1353/aad.2015.0036. [DOI] [PubMed] [Google Scholar]
  15. Cawthon S. Issues of access and validity in standardized academic assessments for students who are Deaf or hard of hearing. In: Knoors H, Marschark M, editors. Educating Deaf learners: Global evidence. Oxford University Press; 2015. pp. 213–230. [Google Scholar]
  16. Cawthon S, Leppo LR. Assessment Accommodations on Tests of Academic Achievement for Students Who Are Deaf or Hard of Hearing: A Qualitative Meta-analysis of the Research Literature. American Annals of the Deaf. 2013;158(3):363–376. doi: 10.1353/aad.2013.0023. [DOI] [PubMed] [Google Scholar]
  17. Climie EA, Rostad K. Test Review: Wechsler Adult Intelligence Scale. Journal of Psychoeducational Assessment. 2011;29(6):581–586. doi: 10.1177/0734282911408707. [DOI] [Google Scholar]
  18. Cummins J. Interdependence of first- and second-language proficiency in bilingual children. In: Bialystok E, editor. Language processing in bilingual children. Cambridge University Press; 1991. pp. 70–89. [Google Scholar]
  19. Educational Testing Service. (2008). Factors that can influence performance on the GRE General Test 2006-07. ETS Princeton, NJ. https://docplayer.net/20204034-Graduate-record-examinations-gre-factors-that-can-influence-performance-on-thegre-general-test.html. Accessed 3 April 2023.
  20. Educational Testing Service. (2013). GRE guide to the use of scores. Princeton, NJ: Author.
  21. Educational Testing Service. (2019). Guide to use of the Graduate Record Examination Program. Princeton, NJ. Retrieved April 3, 2023, from https://www.csusb.edu/sites/default/files/GRE%20Guide%20to%20the%20use%20of%20scores%20%282016-17%29..pdf
  22. Erting, L. (2001). Language and literacy development in a preschool for D/HH children: A qualitative study (unpublished doctoral dissertation). University of Maryland.
  23. Erting, L., & Pfau, J. (1997). Becoming bilingual: Facilitating English literacy development using ASL in preschool. Sharing ideas. https://clerccenter.gallaudet.edu/national-resources/documents/clerc/SI-BecomingBilingual.pdf
  24. Feeley TH, Williams VM, Wise TJ. Testing the predictive validity of the GRE Exam on communication graduate student success: A case study at university at Buffalo. Communication Quarterly. 2005;53(2):229–245. doi: 10.1080/01463370500090209. [DOI] [Google Scholar]
  25. Foster S, Long G, Snell K. Inclusive instruction and learning for Deaf students in post-secondary education. Journal of Deaf Studies and Deaf Education. 1999;4:225–235. doi: 10.1093/D/HHed/4.3.225. [DOI] [PubMed] [Google Scholar]
  26. Hall WC, Levin LL, Anderson ML. Language deprivation syndrome: A possible neurodevelopmental disorder with sociocultural origins. Social Psychiatry and Psychiatric Epidemiology. 2017;52(6):761–776. doi: 10.1007/s00127-017-1351-7.ISSN0933-7954.PMC5469702.PMID28204923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hershberger, K. A. (1997). The relationship between conceptually similar subtests of the Wechsler adult intelligence scale-revised and the career ability placement survey with a vocational rehabilitation sample. University of Cincinnati.
  28. Hile, A. (2009). Deaf children’s acquisition of novel fingerspelled words. (Unpublished doctoral dissertation). University of Colorado, Boulder.
  29. Holt JA. Classroom attributes and achievement test scores for Deaf and hard of hearing students. American Annals of the Deaf. 1994;139:430–437. doi: 10.1353/aad.2012.0274. [DOI] [PubMed] [Google Scholar]
  30. Holt DT, Bleckmann CA, Zitzmann CC. The Graduate Record Examination and success in an engineering management program: A case study. Engineering Management Journal. 2006;18(1):10–16. doi: 10.1080/10429247.2006.11431679. [DOI] [Google Scholar]
  31. Jaschik, S. (2016). An Unlikely Campaign to Move Beyond GRE Scores. Inside Higher Ed. https://www.insidehighered.com/news/2016/06/06/ets-plans-encourage-graduatedepartments-de-emphasize-gre
  32. Jones D, Ragosta M. Predictive validity of the SAT on two handicapped groups: The Deaf and learning disabled. Educational Testing Service; 1982. [Google Scholar]
  33. Kritzer KL. Barely started and already left behind: A descriptive analysis of the mathematics ability demonstrated by young Deaf children. Journal of Deaf Studies and Deaf Education. 2009;14:409–421. doi: 10.1093/D/HHed/enp015. [DOI] [PubMed] [Google Scholar]
  34. Kuncel NR, Hezlett SA, Ones DS. A Comprehensive meta-analysis of the predictive validity of the Graduate Record Examinations: Implications for graduate student selection and performance. Psychological Bulletin. 2001;127(1):162–181. doi: 10.1037/0033-2909.127.1.162. [DOI] [PubMed] [Google Scholar]
  35. Laitusis C, Mandinach BE, Camara JW. Predictive validity of SAT I: Reasoning Test for test takers with learning disabilities and extended time accommodations. ETS Research Report Series. 2002;1:i–13. doi: 10.1002/j.2333-8504.2002.tb01878.x. [DOI] [Google Scholar]
  36. Lang HG. Higher education for D/HH students: Research priorities in the new millennium. Journal of Deaf Studies and Deaf Education. 2002;7(4):267–280. doi: 10.1093/D/HHed/7.4.267. [DOI] [PubMed] [Google Scholar]
  37. Ling G, Buzick H, Belur V. The GRE and Students with Disabilities: A Validity Study at 10 Universities. Exceptional Children. 2020;86(2):193–208. doi: 10.1177/0014402919872688. [DOI] [Google Scholar]
  38. Luetke-Stahlman B, Nielsen DC. The Contribution of Phonological Awareness and Receptive and Expressive English to the Reading Ability of Deaf Students with Varying Degrees of Exposure to Accurate English. Journal of Deaf Studies and Deaf Education. 2003;8(4):464–484. doi: 10.1093/D/HHed/eng028. [DOI] [PubMed] [Google Scholar]
  39. Luft P. Strengths-based reading assessment for deaf and hard-of-hearing students. Psychology in the Schools. 2020;57(3):375–393. doi: 10.1002/pits.22277. [DOI] [Google Scholar]
  40. Marschark M, Lang H, Albertini J. Educating Deaf students: From research to practice. Oxford University Press; 2002. [Google Scholar]
  41. Marschark, M., Shaver, D. M., Nagle, K. M., & Newman, L. A. (2015). Predicting the academic achievement of Deaf and hard-of- hearing students from individual, household, communication, and educational factors. Exceptional Children, 81, 350–369. 10.1177/2F0014402914563700 [DOI] [PMC free article] [PubMed]
  42. Mayer C, Trezek B. Writing and Deafness: State of the Evidence and Implications for Research and Practice. Education Sciences. 2019;9(3):185. doi: 10.3390/educsci9030185. [DOI] [Google Scholar]
  43. McKee, A. J., Mallory, S. L., & Campbell, J. (2001). The Graduate Record Examination and undergraduate grade point average: Predicting graduate grade point averages in a criminal justice program. Journal of Criminal Justice Education, 12, 311–317.
  44. Meek D. Dinner Table Syndrome: A Phenomenological Study of Deaf Individuals' Experiences with Inaccessible Communication. Qualitative Report. 2020;25(6):1676–1694. [Google Scholar]
  45. Millar J. A. (2020). The GRE in Public Health Admissions: Barriers, Waivers, and Moving Forward. Frontiers in Public Health, 8, 609599. 10.3389/fpubh.2020.609599 [DOI] [PMC free article] [PubMed]
  46. Milner M, McNeil JS, King SW. The GRE: A question of validity in predicting performance in professional schools of social work. Educational and Psychological Measurement. 1984;44(4):945–950. doi: 10.1177/0013164484444015. [DOI] [Google Scholar]
  47. Mitchell RE. Academic achievement of D/HH students. In: Johnson RC, Mitchell RE, editors. Testing Deaf students in an age of accountability. Gallaudet University Press; 2008. pp. 38–50. [Google Scholar]
  48. Mitchell, R. E., & Cawthon, S. W. (2014). Academic achievement: Test bias and fairness. In G. Gertz & P. Boudreault (Eds.), Deaf studies encyclopedia. Thousand Oaks, CA: Sage.
  49. Moneta-Koehler, L., Brown, A.M., Petrie, K. A., Evans, B. J., & Chalkley, R. (2017). The Limitations of the GRE in predicting success in biomedical graduate school. PLoS ONE, 12(1), e0166742. 10.1371/journal.pone.0166742 [DOI] [PMC free article] [PubMed]
  50. Noble, T., Rosebery, A., Suarez, C., Warren, B., & O’Connor, M. C. (2014). Science assessments and English language learners: Validity evidence based on response processes. Applied Measurement in Education, 27(4), 248–260.
  51. Powers DE. Validity of Graduate Record Examinations (GRE) general test scores for admissions to colleges of veterinary medicine. Journal of Applied Psychology. 2004;89(2):208–219. doi: 10.1037/0021-9010.89.2.208. [DOI] [PubMed] [Google Scholar]
  52. Qi S, Mitchell RE. Large-scale academic achievement testing of Deaf and hard-of-hearing students: Past, present, and future. Journal of Deaf Studies and Deaf Education. 2012;17(1):1–18. doi: 10.1093/deafed/enr028. [DOI] [PubMed] [Google Scholar]
  53. Ragosta, M., & Kaplan, B. (1986). A survey of handicapped students taking special test administration of the SAT and GRE. Report No. 5. Studies on admissions testing and handicapped people. Princeton, NJ. Educational Testing Service
  54. Ragosta M, Nemceff WPA. Research and development program testing handicapped people. Educational Testing Service; 1982. [Google Scholar]
  55. Reisig MD, DeJong C. Using GRE scores and prior GPA to predict academic performance among criminal justice graduate students. Journal of Criminal Justice Education. 2005;16(1):37–59. doi: 10.1080/1051125042000333451. [DOI] [Google Scholar]
  56. Saur RE, Popp-Stone MJ, Hurley-Lawrence E. The classroom participation of mainstreams hearing impaired college students. Volta Review. 1987;89:277–286. [Google Scholar]
  57. Schmidt EA, Homeyer LE, Walker JL. Predictors of success on the preparation comprehensive examination. Counselor Education & Supervision. 2009;48:226–238. doi: 10.1002/j.1556-6978.2009.tb00077.x. [DOI] [Google Scholar]
  58. Stack, S. & Kelly, T. (2002). The graduate record examination as predicting of graduate student performance: The case of criminal justice. Journal of Criminal Justice Education, 13(2), 335–349. 10.1080/10511250200085511
  59. Sternberg RJ, Williams WM. Does the Graduate Record Examination predict meaningful success in the graduate training of psychology? A Case Study. American Psychologist. 1997;52(6):630–641. doi: 10.1037/0003-066X.52.6.630. [DOI] [PubMed] [Google Scholar]
  60. Stinson M, Liu Y, Saur R, Long G. Deaf college students’ perception of communication in mainstream classes. Journal of Deaf Studies and Deaf Education. 1996;1:40–51. doi: 10.1093/oxfordjournals.D/HHed.a014280. [DOI] [PubMed] [Google Scholar]
  61. Stinson MS, Walker GG. Persistence in college. In: Foster SB, Walter GG, editors. Deaf students in post-secondary education. Routledge; 1992. pp. 43–64. [Google Scholar]
  62. Stinson MS, Walker GG. Improving retention for Deaf and hard of hearing students: What research tells us. Journal of American D/HH Ness and Rehabilitation Association. 1997;30:14–23. [Google Scholar]
  63. Stricker LJ. The performance of native speakers of English and ESL speakers on the computer-based TOEFL and GRE General Test. Language Testing. 2004;21(2):146–173. doi: 10.1191/0265532204lt279oa. [DOI] [Google Scholar]
  64. Stricker LJ, Rock DA. Examinee background characteristics and GRE general test performance. Intelligence. 1995;21:49–67. doi: 10.1016/0160-2896(95)90038-1. [DOI] [Google Scholar]
  65. Strong M, Prinz P. A Study of the Relationship between American Sign Language and English Literacy. Journal of Deaf Studies and Deaf Education. 1997;2(1):37–46. doi: 10.1093/oxfordjournals.D/HHed.a014308. [DOI] [PubMed] [Google Scholar]
  66. Tock, J. L., & Ericsson, K. A. (2019). Effects of curricular emphasis in college on the GRE and its impact on the gender gap in performance. Contemporary Educational Psychology, 56, 40–54. https://www.sciencedirect.com/science/article/pii/S0361476X18302248
  67. Traxler C. The Stanford achievement test, 9th edition: National norming and performance standards for Deaf and hard of hearing students. Journal of Deaf Studies and Deaf Education. 2000;5:337–348. doi: 10.1093/deafed/5.4.337. [DOI] [PubMed] [Google Scholar]
  68. Wilbur RB. The use of ASL to support the development of English and literacy. Journal of Deaf Studies and Deaf Education. 2000;5(1):81–104. doi: 10.1093/D/HHed/5.1.81. [DOI] [PubMed] [Google Scholar]

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