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Examining Racial Disparities in Teacher Perceptions of Student Disabilities


by North Cooc - 2017

Background/Context: The overrepresentation of some minority groups in special education in the United States raises concerns about racial inequality and stratification within schools. While many actors and mechanisms within the school system may contribute to racial disparities in special education, the role of teachers is particularly important given that teachers are often the first ones to refer students for services. Previous studies examining biases in teacher perception of student disability have used simulations and vignettes that lack information on how teachers may perceive their own students.

Purpose of the Study: This study examined whether teachers disproportionately perceive minority students as having a disability based on survey information from teachers about their students. The study provides additional insight into teacher perception of student disability by accounting for student background, teacher traits, and school characteristics.

Research Design: The study used data on a nationally representative sample of high school sophomores from the Education Longitudinal Study of 2002 (ELS:2002). The dataset included surveys that asked teachers about their students, including whether they perceived them to have a disability. Logistic regression models were used to model the relationship between teacher perception of student disability and student race, controlling for background factors relevant to identification for a disability.

Results: The findings show that while teachers were more likely to perceive Black, Hispanic, and Native American students as having a disability compared to White students, controlling for individual background characteristics and school contextual factors often resulted in underidentification. The exception is Asian Americans, who were consistently less likely to be perceived to have a disability.

Conclusions/Recommendations: Since teachers were less likely to perceive certain racial minority students as having a disability when accounting for student background characteristics, the finding provides a different perspective on how teachers may contribute to disproportionality in special education. The results also raise concerns about whether racial minority students are appropriately identified for services, especially Asian Americans who were consistently less likely to be perceived to have a disability, even when their achievement and behavior were similar to those of other students. Policies and practices should focus on using culturally and linguistically appropriate methods to identify students who may have disabilities.



EXAMINING RACIAL DISPARITIES IN TEACHER PERCEPTION OF STUDENT DISABILITIES


Racial disparities in special education enrollment have been a well-documented trend in the United States for the last four decades and a focal point of federal legislation and policies (Artiles, Kozleski, Trent, Osher, & Ortiz, 2010; Donovan & Cross, 2002; Government Accountability Office, 2013). Annual reports to Congress indicate that overall about 12–14% of Black and American Indian students receive special education services, compared to 8% of White and Hispanic students and 5% of Asian American students, who are the one minority group that tends to be underrepresented (U.S. Department of Education, 2012). These disparities are larger for specific disabilities like emotional behavior disorder for which Black students are twice as likely to be identified as their peers (U.S. Department of Education, 2012). Evidence of racial disproportionality—the over- or underrepresentation of students of a particular race based on a higher-than-expected percentage of that population in special education—is also observed at local levels (Ahram, Fergus, & Noguera, 2011; Deninger, 2008; Sullivan & Bal, 2013).


These racial disparities in special education would be less alarming if all students were receiving appropriate services for a disability. However, one concern is that racial minority students are incorrectly identified for services and denied access to the general curriculum (Losen & Orfield, 2002). Studies show that special education participation itself may result in lower academic expectations among teachers (Woodcock & Vialle, 2011), fewer learning opportunities (Harry & Klingner, 2014), and lower academic outcomes for students (Morgan, Frisco, Farkas, & Hibel, 2010; Sullivan & Field, 2013). For students and families, particularly those from diverse cultural backgrounds, special education services and disability labels can be stigmatizing (Green, 2003). The high cost of educating students with special needs also means these disparities have implications for local school budgets (Chambers, Parrish, & Harr, 2004).


Many students do have legitimate disabilities and can benefit from appropriate special education services (Hehir & Katzman, 2012). Given the high stakes involved in classification, researchers have focused on the sources of racial disproportionality. Waitoller, Artiles, and Cheney’s (2010) review of the last 40 years identified three main research domains. The first focuses on the sociodemographic traits of students and the home and school contexts. The hypothesis is that disproportionality reflects larger socioeconomic disparities and disadvantaged conditions that minority students are more likely to experience (Coutinho, Oswald, & Best, 2002; Hosp & Reschly, 2003), which in turn exposes them to early childhood health problems that affect school readiness and special education referral (Delgado & Scott, 2006; Hibel, Farkas, & Morgan, 2010). The second research area analyzes systemic racial bias within professional practices. Studies in this area suggest that assessments may lack cultural appropriateness (Coffey & Obringer, 2000), bureaucratic procedures may disadvantage minority families (Klingner & Harry, 2006; Rogers, 2002), or classroom teachers may identify certain students disproportionately as having disabilities (Hosterman, DuPaul, & Jitendra, 2008; Skiba et al., 2006). The third research area examines the sociohistorical context of special education and structural inequalities within schools. Critics argue that school decisions reflect historical race relations and cultural assumptions that privilege White, middle-class values and put racial minority students at a disadvantage regarding disability decisions (Artiles et al., 2010; Eitle, 2002; Ong-Dean, 2006).


Although the role of sociodemographic and sociohistorical contexts is important in understanding the ecology of disproportionality in special education, bias in professional practices—if properly identified—is potentially more amenable to policy change in the short term. Research on disproportionality has focused extensively on systemic biases in professional practices within schools (Waitoller et al., 2010). Among the many actors and mechanisms within the school system that may contribute to racial disparities, teachers in particular play an integral role in decisions regarding services since they are often the first ones to refer students (Hosp & Reschly, 2003). Indeed, it is a teacher’s perception of whether a student has a disability that initiates the special education process. Consequently, in this article, I focus on teachers and contribute to the literature by using national data to examine whether there are racial disparities in how teachers perceive students in terms of disability.


Examining teacher perception of student disability can provide insight into racial disproportionality. Research shows that teacher perception of whether a student has a disability predicts their decision to later refer the student for special education (Abidin & Robinson, 2002; Podell & Soodak, 1993; Schwartz, Wolfe, & Cassar, 1997).1 Thus, if teachers disproportionately perceive minority students compared to White students  as having a disability due to their own perceptual biases or other factors, then this may help explain current disparities in special education. Although teachers may not always act on their perception, if there are no racial disparities in teacher perception of student disabilities, then this challenges, to an extent, the role of teachers in special education disproportionality. Teacher perception of student disability also matters because teachers may have lower expectations for the achievement and behavior of students with disabilities (Cook, 2001; Hornstra, Denessen, Bakker, van den Bergh, & Voeten, 2010). Examining disparities in teacher perception of student disability can help ensure students receive equal educational opportunities and identify areas for teacher training and development.


In the next section, I provide an overview of the research literature on teacher perception of students and review past research on teacher bias in special education referral decisions. This is followed by a description of the methodology and presentation of the findings. I conclude with a discussion of the study’s limitations and implications for policy and research.


BACKGROUND AND CONTEXT


TEACHER PERCEPTION OF STUDENTS: DETERMINANTS, ACCURACY, AND BIAS


The potential consequences of teacher perception of students’ academic abilities in educational decisions like special education referral raise two related issues concerning the determinants and accuracy of this perception. For the most part, research shows teacher perception of student ability is influenced by the performance and behavior of students (Feinberg & Shapiro, 2003; Mesiels, Bickel, Nicholson, Xue, & Atkins-Burnett, 2001). Disparities in how teachers perceive students in terms of ability and behavior tend to reflect differences in achievement and skills. Studies find that conditioning on academic performance and students’ cognitive skills reduces racial differences in teacher perception of students’ present or future achievement (Ferguson, 2003; Jussim, Eccles, & Madon, 1996). Researchers also show that teachers’ judgments about students are related to certain teacher characteristics, such as job experience (Bianco & Leech, 2010; Impara & Plake, 1998) and race (Downey & Pribesh, 2004). Overall, the literature indicates that teacher perception and expectations of students are fairly accurate assessments of student achievement (Jussim & Harber, 2005). In the context of the current study, research suggests that while there may be racial disparities in teacher perception of student disabilities (Tenenbaum & Ruck, 2007), these differences should be reduced after accounting for student background and teacher characteristics.


Although much of the research on teacher perception of students focuses on the achievement of students individually, this perception is likely influenced by the performance and behavior of other students. A student’s school peers serve naturally as a referent group for teachers to base decisions about certain students. Consequently, the school context is particularly relevant for how teachers may identify students for special education, especially for high-incidence disabilities (e.g., learning disability) where identification often relies on social norms rather than medical examinations (e.g., deafness) (Hibel et al., 2010). Teacher perception about whether a student has a disability is likely relative to how the student’s peers perform or behave. Whether a student stands out at school may also be related to contextual factors not related to their achievement or behavior. Studies show that the percentage of students in special education, for a given race, is inversely related to the percentage of that racial group in the school population (Coutinho et al., 2002; Serwatka, Deering, & Grant, 1995). In short, accounting for these contextual factors is important to understanding teacher perception of students.


Implicit in this discussion of potential bias in teacher perception of student disability is a benchmark that defines neutrality. Although there are many definitions of teacher bias in the literature, I use Ferguson’s (2003) classification of racial bias to understand disproportionality in teacher perception. In the first type, unconditional race neutrality, teacher perception and expectations of children are the same regardless of individual background differences. This is in contrast to conditional race neutrality, which assumes that teacher perception is unbiased if based on observable differences in student performance, such as test scores. These classifications permit situations where differences may be expected, such as the possibility that disparities in teacher perception of student disabilities may reflect academic differences among students.2 Thus, in this study, I rely on these two definitions of race neutrality to evaluate racial disparities in teacher perception and account for the student and school factors associated with disabilities.


RESEARCH ON RACIAL BIAS IN TEACHER PERCEPTION OF STUDENT DISABILITY


Research on racial bias in teacher perception of student disability, conducted mostly in the 1980s and 1990s, tended to focus on teachers’ decisions during the student referral and evaluation stages. These studies were often randomized experiments where teachers were asked to recommend students for services based on their reading of fictitious or real profiles of students with or without disabilities from different racial backgrounds. In one of the earlier studies, for instance, Zucker & Prieto (1977) found special education instructors were more likely to refer Latino students to special services after reading identical case studies of students with mild mental retardation, differing only in race. Other simulated case studies that involved emotional or behavior disorders demonstrated similar biases against minority students in terms of special education placement (Prieto & Zucker, 1981; Tobias, Cole, Zibrin, & Bodlakova, 1982).


On the other hand, studies have also found teacher biases against White students related to disability and special education. Cullinan and Kauffman (2005) examined teachers’ perception of emotional disorder and behavioral problems among Black and White students and concluded that White students were judged to exhibit these behavioral characteristics more frequently than Black students. The authors concluded, “The results did not support the position that, among students with ED [emotional disorder], overrepresentation of African Americans arises from racial bias in teachers’ perceptions of emotional and behavioral problems” (p. 393). Similar studies of teacher perception found little evidence of racial bias (Bahr, Fuchs, Stecker, & Fuchs, 1991; Gottlieb, Gottlieb, & Trongone, 1991; Shinn, Tindal, & Spira, 1987). MacMillan, Gresham, Lopez, and Bocian (1996) examined the characteristics of children recommended for special education and found that although Black and Hispanic students had higher referral rates, they also had lower average reading achievement scores and more reported behavioral problems.


Qualitative studies of special education meetings among school officials present a picture of inconsistency and bias in the decision-making processes. Ethnographic work from Knotek (2003) and Harry and Klingner (2014) found that referral decisions often relied more on educators’ personal beliefs about special education or specific student background traits and less on students’ actual performance. Mehan, Hertweck, and Meihls’ (1986) study of individual education program (IEP) meetings revealed a system that favored the technical expertise of school officials over the knowledge of parents. Wilkinson, Ortiz, Robertson, and Kushner (2006) reviewed learning disability placement for English language learners (ELL) with an external panel and found that at one school only one quarter of the decisions were appropriate.


STUDY GOALS AND HYPOTHESES


Although previous work on teacher perception of student disability has provided insight into a potential source of racial disproportionality in special education, the current study addresses several key limitations in the literature. Primarily, the use of experimental vignettes means that while the evaluations of teacher bias have strong internal validity, these studies lacked information about how teachers would perceive their own students. Basing a referral decision on reading a student vignette is different from assessing an actual student based on daily interactions (Stinnett, Bull, Koonce, & Aldridge, 1999). In contrast, this study examined teachers’ perceptions of their own students. I hypothesized that any racial disparities in teacher perception of student disability would be smaller than those in vignette studies but comparable to current racial disparities in special education placement (Gliner. Haber, & Weise, 1999).


Second, many of the prior studies were unable to examine how school contextual factors may influence teachers’ perceptions of student disability. This study explored the link between teacher perception of student disability and student background characteristics and school contexts. Based on current disparities in special education placement, I hypothesized that teachers would be more likely to perceive Black, Hispanic, and Native American students than White or Asian American students as having a disability. However, I expected that these disparities would be attenuated when controlling for student background traits and school contextual factors, which are likely to influence teacher perception of student disability. Recent studies also show that controlling for confounding factors can result in parity or the underrepresentation of racial minorities in special education (e.g., Hibel et al., 2010; Morgan et al., 2015).


Third, many studies on teacher perception of student disability use small sample sizes that limit the external validity of the findings. This study used nationally representative data from the Education Longitudinal Study of 2002 (ELS:2002), which sampled more than 13,000 high school students and 1,000 teachers. A related concern about external validity is that most prior studies focused on elementary school students. Although students with disabilities are likely to be identified in earlier grades, they also transition into and out of special education from year to year for different reasons (Holt, McGrath, & Herring, 2007). These transitions may also occur in high school where teacher perception of student disabilities could potentially play a role in special education decisions. As a result, this study focused on high school, a critical period for students with disabilities as they transition to adulthood.


Lastly, research examining Asian American students in special education is limited. Studies tend to focus on the overrepresentation of Black students in special education while ignoring the underrepresentation of Asian Americans.3 However, low enrollment numbers may suggest that some students are not receiving services guaranteed under federal law. Understanding teacher perception of Asian American students can provide insight into their underrepresentation in special education. This is important for the fastest growing and largest group of new immigrants in the United States (Pew Research Center, 2012). While quantitative research on Asian American students in special education is often limited by small sample size, ELS:2002 sampled more than 1,000 Asian American students. Given the model minority perception of Asian Americans (Lee, 2005; Louie, 2004), I hypothesized that teachers would be less likely to perceive Asian American students as having a disability, even after adjusting for background characteristics and any differences in school contexts.


To summarize, this study draws on rich secondary data to assess how teachers perceive their own students in terms of disability. I ask the following research questions:

1)

To what extent are there racial disparities in teacher perception of student disability?

2)

Do any disparities in teacher perception persist after controlling for student background, teacher characteristics, and school contextual factors?


METHODOLOGY


DATA SOURCES


I used public data from the Educational Longitudinal Study of 2002 (ELS:2002) (Ingels, Pratt, Rogers, Siegel, & Stutts, 2004). The ELS:2002 contains information on a nationally representative sample of 16,197 10th-graders as they transitioned from high school to postsecondary education and work. Data were collected from students in 752 public and private schools in 2002 with follow-up in 2004, 2006, 2012, and college transcripts in 2013. Students were asked about their school experiences and assessed in mathematics and reading. Most important for this study, ELS:2002 surveyed both the English and mathematics teachers of each student about their own professional backgrounds and perceptions of their students. The current study focuses on the 10th-grade sample in 2002 since teachers were only surveyed that year. The unique pairing of each of the 16,197 students with two teachers results in 32,394 possible paired student-teacher observations. Since some teachers did not submit surveys at all, I removed these cases from the sample and retained a final dataset of 23,818 student-teacher observations for 13,348 students.


While there are certainly limitations to using a dataset that is more than a decade old, there are also considerable advantages to using the ELS:2002. To my knowledge, this is the only nationally representative survey that specifically asked teachers about their own students regarding disability.4 ELS:2002 also includes a large sample of Asian Americans, an underexplored group in the context of special education. The generalizability of the findings is a tradeoff that can provide additional insight into teacher perception of student disability and disproportionality in special education.


MEASURES


Dependent Variable.


The outcome is a dichotomous measure of whether a teacher perceived the student to have a disability. In the ELS:2002 survey, teachers were asked: “In your opinion, does this student have a learning, physical, or emotional disability that affects his/her school work?” Approximately 13.0% of teachers reported “yes.” There are two limitations associated with this measure of teacher perception of student disability. First, it combined several disability categories into one. Since the variable broadly included the main disabilities, it should be interpreted as teacher perception of any disability. Second, although the question was intended to ask about a teacher’s opinion, it is possible that it also captured knowledge of a student’s disability status for some teachers. I discuss the implications further in the limitation section and additional analyses that can help separate perception from knowledge about a student disability.


Question Predictor.


The key question predictor is student race, which I specified using a vector of dichotomous variables for Asian, Black, Hispanic, Native American, and White. In the ELS:2002 data, nearly 65% of students were White, followed by 16% Hispanic, 14% Black, 4% Asian, and 1% Native American.


Controls Variables.


I controlled for confounds at the student, teacher, and school levels when estimating the extent to which any observed disparities in teacher perception of student disability are attributable to students’ race. At the student level, research shows disparities in special education by gender and family socioeconomic status (SES) (Coutinho & Oswald, 2005; Hosp & Reschly, 2003). I included a variable for student gender and parent SES, a continuous composite measure of both parents’ income, education level, and occupation generated by the test developers with strong reliability. Studies also indicate that academic achievement and behavior are predictors of special education and disabilities (Abidin & Robinson, 2002; Hibel et al., 2010; Morgan, Farkas, Hillemeier, & Maczuga, 2012). For achievement, I used students’ reading and mathematics test scores. In the reading assessment, students were asked to read passages and tested on their ability to understand the meaning of words in context, identify figures of speech, interpret the author’s perspective, and evaluate passages. The mathematics assessment consisted of word problems, graphs, equations, quantitative comparisons, and geometric figures. For parsimony and to better assess overall student achievement, I used a composite of reading and mathematics achievement (M=50, SD=10) generated by ELS:2002 (I found similar results when using separate measures in the regression models). Lastly, I included a self-reported measure of misbehavior from the student survey, which asked students how often in the first semester of the school year they “got in trouble for not following school rules.” The responses were never (0), 1–2 times (1), 3–6 times (2), 7–9 times (3), and 10 or more times (4).


At the classroom level, I included teacher characteristics that may influence their perception of student disability. Research suggests that more experienced, educated, or effective teachers may be more adept at identifying student difficulties (Tournaki & Podell, 2005). Thus, I used indicators for master’s degree or higher, teacher certified or not, teaching experience in years, and general characteristics like gender and race (I dichotomized the variable as White or not since 90% of the teachers were White). I also included a continuous measure of the number of hours of training or professional development on teaching special education students teachers had in the last 3 years. Lastly, I controlled for the class subject (English or mathematics).


At the school level, I focused on peer contextual factors that may influence teacher perception of student disability. As noted earlier, the composition of the student body tends to be related to special education enrollment rates for certain students. Thus, I included measures of whether the student body was mostly White (75% or more), the percent of limited English-proficient students (10% or more), the average student SES of the school, and the school’s mean score for the reading/mathematics achievement composite.5 Finally, I controlled for school sector (public or private) and geographic location (urban, rural, or suburban).


Disability Status.


The ELS:2002 base year administration contains a record of whether each student had an individualized education program (IEP) for a disability. About 8.6 percent of students had an IEP.6 The extent to which IEP records were available to teachers raises the possibility that some teachers may have known whether a student had a disability and responded accordingly in the teacher survey. Although the outcome variable asked teachers about their opinion of whether a student had a disability, the question may capture teacher knowledge. The IEP record, however, provides a useful analysis of disproportionality and a robustness check of the results. For instance, if there are raw racial disparities in teacher perception of whether a student has a disability, then controlling for the presence of an IEP record should reduce these differences. Another strategy is to remove students with IEP records from the analytic sample and examine whether there are still racial disparities in teacher perception among students without a documented disability. In Table 1, I present descriptive statistics of all variables.



Table 1. Univariate Descriptive Statistics of Selected Covariates From Educational Longitudinal Study of 2002 (Child Observations = 13,348; Teacher Observations = 23,818)

Variables

Mean

Standard Error*

Student Characteristics

  

 Asian

0.040

0.003

 Black

0.144

0.007

 Hispanic

0.158

0.009

 Native American

0.010

0.002

 White

0.648

0.011

 Male

0.503

0.006

 Socioeconomic status

0.002

0.015

 Reading and math test composite

50.241

0.222

 Misbehavior

0.616

0.012

 Individualized Education Plan (IEP)

0.086

0.004

Teacher Perception of Disability



 All Students

0.127

0.004

Teacher Characteristics



 Male

0.350

0.009

 White

0.891

0.007

 Master's degree or higher

0.480

0.011

 Standard teaching certification

0.860

0.006

 Experience in years

14.059

0.209

 Hours of special education training

7.425

0.281

Classroom Characteristics



 English

0.490

0.003

 Math

0.510

0.003

School Characteristics



 Majority White (>75%)

0.434

0.018

 LEP students (>10%)

0.181

0.017

 Average SES

-0.009

0.015

 Reading test score (standardize)

-0.040

0.019

 Urban

0.289

0.009

 Suburb

0.506

0.009

 Rural

0.205

0.007

 Public

0.923

0.003

Note. Socioeconomic status range = -2.11 to 1.82; Misbehavior range = 0 (never) to 4 (10 or more times). School characteristics for majority White and LEP are dichotomous indicators. *All analyses include sample weights (BYSTUWT) with linearized standard errors.



DATA ANALYSIS


To address my research questions, I modeled a binary outcome—whether a teacher perceived a student to have a disability—as a function of student race, student background characteristics, and school contextual factors. Since students were observed twice, one can think of the teacher perception of disability as being nested within students. Although one option is to use a multilevel logistic regression model with a student-specific random intercept, the odds ratios derived from such a random intercept model would then have an individual-specific interpretation (Rabe-Hesketh & Skrondal, 2012). For variables that remain constant within individuals, such as the key race predictors in this study, this interpretation can be unrealistic. For example, the log-odds obtained from such a fitted model would be interpreted as the odds that a given Black student would be perceived to have disability, compared to had the same student been White. Instead, to obtain population-averaged or marginal relationships, I fitted the following standard logistic regression model to address my first research question:7


[39_21755.htm_g/00001.jpg]


The baseline model in Equation (1) predicts the log-odds of student i being perceived to have any disability in school j, where pij represents the population probability of teacher perception of disability. To account for the dependency within the pair of observations for each student and the nesting of students within schools, I adjusted the standard errors for student clustering at the higher school level, a common practice that leads to larger standard errors and more conservative inferences (Cameron, Gelbach, & Miller, 2011). The antilog of the slope parameters, b1 to b4, is the fitted odds ratio of the associated racial group, relative to White students (omitted reference category), of being perceived to have a disability by a teacher. A statistically significant value above 1 on any of these parameters indicates that the racial minority group has higher odds of being perceived to have a disability relative to White students.


To address my second research question about whether any disparities in teacher perception are attenuated by student and contextual factors, I added covariates sequentially at each level. Fitted odds ratios greater than 1, after conditioning on observables, provide evidence of teacher bias against minority students in their perception of student disability and a violation of conditional racial neutrality. I conducted all analyses using Stata 13.1 and specified the clustering units and sample weights to incorporate the survey design of ELS:2002.8


MISSING DATA


As noted earlier, I excluded students and teachers who did not return surveys at all. Most students in the final sample (about 90%) had full data, or missing values on one or two variables (usually at the teacher or school levels). Since students with missing data tended to have lower test scores and teachers with fewer years of experience, this did not satisfy the missing-completely-at-random (MCAR) assumption required for ignoring these cases in the analyses. However, the dataset included variables on students, teachers, and schools that can help account for the mechanisms that may have led to missing data. I imputed missing values using chained equations in Stata that then pooled together results from five imputed datasets. I present the main model results using multiple imputation in this paper but found that the parameter estimates and standard errors were similar to results from listwise deletion.


RESULTS


RACIAL DISPARITIES IN STUDENT BACKGROUNDS


Since racial disparities in teacher perception of students may reflect background differences in students rather than bias, I first present select characteristics of students and their schools by race in Table 2. The results show that Asian and White students tended to have higher parental SES and reading/mathematics achievement, and less self-reported misbehavior compared to Native American, Black, and Hispanic students. In the right half of Table 2, I summarize the average SES, average achievement level, and racial composition of the schools (i.e., if majority White). The results here indicate that Native American, Black, and Hispanic students were more likely to attend schools of low SES, achievement, and with fewer White peers. If teachers base their perception relative to other students, this suggests that Native American, Black, and Hispanic students may be less likely to stand out in these schools and be identified for disabilities. Overall, Table 2 highlights the importance of controlling for individual and contextual factors to understand any racial disparities in teacher perception of disability.



Table 2. Means of Select Student- and School-Level Variables by Student Race/Ethnicity and Dataset for ELS:2002 (n=13,348)

 

Student Mean

School Mean

 

Family SES

Read/Math

Composite

Mis-

behavior

Family SES

Read/Math

Composite

Majority White

 Asian

 0.035

 52.506

 0.390

 0.032

 50.851

 0.126

 Black

 -0.249

 43.758

 0.693

 -0.169

 46.831

 0.089

 Hispanic

 -0.451

 44.847

 0.662

 -0.253

 47.258

 0.100

 Native Am.

 -0.154

 45.853

 0.739

 -0.132

 48.408

 0.270

 White

 0.167

 53.005

 0.602

 0.084

 51.598

 0.614

Note. Student mean represents the average of the variable for all students in the racial group. School mean represents the average of the school-level characteristics for the racial group. All analyses include sample weights (BYSTUWT).





RQ 1: Are there racial disparities in teacher perception of student disability?


I present a series of logistic regression models in Table 3 that examined the extent of racial disparities in teacher perception of student disability. To understand the unadjusted racial disparities in teacher perception, I included only the predictors describing race in Model A. All parameter estimates were antilogged and presented as odds ratios. The results indicate that Black, Hispanic, and Native American students had the highest odds of being perceived to have a disability. The odds for Black and Hispanic students were 1.42 to 1.56 times higher than the odds for Whites, while Native Americans had more than twice the odds (all estimates p < .01). Asian American students, on the other hand, had only half the odds (p < .001) of being perceived to have a disability compared to White students. Overall, these results show clear racial disparities in teacher responses when they were asked whether they believed a specific student had a disability. These disparities in teacher perception tend to mirror past and present patterns in special education enrollment reflecting the overidentification for Black and Native American students and the underidentification of Asian students (U.S. Department of Education, 2006, 2012). The exception is Hispanic students, who nationally have similar identification rates as White students. However, it is unclear from these unadjusted disparities alone in Model A whether they reflected potential teacher bias or other confounds related to students’ racial and ethnic backgrounds that may influence teachers perception, which I focus on next.


RQ2: Do any racial disparities in teacher perception of student disability persist after controlling for student background traits and school contextual factors?


In Model B of Table 3, I examined whether racial disparities in teacher perception of student disabilities persist after controlling for student factors associated with disabilities. The results show that male students (OR = 1.51, p < .001) with high levels of self-reported misbehavior (OR = 1.28, p < .001) were more likely to be perceived to have a disability, while students with high reading and mathematics composite scores were less likely (OR = 0.89, p < .001). These trends are found within the special education literature, but surprisingly, family SES was not associated with teacher perception, when controlling for the other student characteristics. The key finding is that the parameter estimates associated with student race were not only attenuated but also reversed in some cases. Asian American students still had lower odds of a teacher perceiving them to have a disability than White students (OR = 0.43, p < .001). Native American students now had the same odds as White students. For Hispanic and Black students, the fitted odds were 0.59 to 0.63 (p < .001) times that of their White peers, meaning they were less likely to be perceived to have a disability. Thus, initial disparities in teacher perception were in part explained by student background differences.


In Model C, I examined the influence of teacher demographic and professional characteristics on teacher perception of student disability. The results indicate that male teachers were less likely to perceive students as having a disability, while teachers with a master’s degree or higher were more like to do so. Also of interest was the role of teachers’ own racial background, if any, on their perception of students. I found White teachers were more likely to perceive students as having a disability than non-White teachers. In a separate model not presented, I disaggregated teachers’ race (Black, Hispanic, White, or Other) but found no significant main effects or interactions with student race. Although years of experience was not associated with teacher perception of student disability, teachers with more hours of special education training were more likely to perceive students as having a disability (OR = 1.02, p < .001). While teacher characteristics influenced teacher perception of students, the main finding is that even after controlling for these variables, the results were similar to Model B in which minority students (Asian, Black, and Hispanic) were less likely to be perceived to have a disability.


Lastly, in Model D I analyzed the potential influence of school-level characteristics on teacher perception. Students in schools with higher average student achievement levels had higher odds of being perceived to have a disability (OR = 1.04, p < .001), while those in schools with more LEP (limited English proficient) students were less likely (OR = 0.79, p < .001). However, the odds ratios on the race variables and pattern remained about the same as Model B and C. Overall, the trends in Table 3 show that controlling for student background characteristics attenuated or reversed initial racial differences in teacher perception. In Figure 1, I plot the raw odds ratios with the adjusted odds ratios for each racial group. The bars, from left to right, highlight the extent of unconditional (first bars for each group) and conditional race neutrality in teacher perception.


Table 3. Estimated Odds Ratios From a Taxonomy of Logistic Regression Models Predicting Teacher Perception of Student Disability by Student Race, Controlling for Student, Teacher, and School Characteristics, ELS:2002 (N = 23,432 Student-Teacher Observations)

 

Model A

Model B

Model C

Model D

Model E

Student Characteristics

     

  Asian

0.513***

0.446***

0.484***

0.507***

0.583**

  Black

1.563***

0.625***

0.645***

0.696***

0.785*

  Hispanic

1.417***

0.593***

0.615***

0.709**

0.824~

  Native American

2.135**

0.882

0.945

1.051

1.072

  Male


1.513***

1.501***

1.525***

1.295***

  SES


1.030

1.044

0.973

0.943

  Read-Math Composite


0.889***

0.893***

0.885***

0.925***

  Misbehavior


1.277***

1.270***

1.261***

1.303***

Teacher Characteristics






  Male



0.782**

0.792**

0.819*

  White



1.446**

1.303**

1.404**

  Master's or higher



1.217**

1.190**

1.153

  Certified



0.947

0.915

0.956

  Experience in years



0.999

1.000

0.999

  Special education hours



1.020***

1.020***

1.011***

  Mathematics class



0.892~

0.883*

0.831*

School Characteristics






  Percent White




0.914

0.907

  Percent LEP




0.794*

0.792~

  SES Average




1.174

1.062

  Reading­Math Average




1.043***

1.019

  Urban




0.973

0.985

  Suburb




0.938

0.985

  Public




1.184

0.930

Disability Record (IEP)





16.029***

Intercept

0.134***

29.270***

15.637***

3.010***

1.009

Note. White students are the race reference group. English is the subject reference category. Rural is the geography reference group. All analyses include sample weights and standard errors are adjusted for students clustering at the school level. ~p<0.10; *p<0.05; **p<0.01; ***p<0.001.



SENSITIVITY ANALYSES USING STUDENT IEP RECORD


As noted earlier, one concern is that teacher perception, as operationalized in this study, may also capture knowledge of students’ actual disability status. I tested the robustness of the results in two ways. First, to the extent that teacher perception reflects knowledge of student disability, controlling for whether a student has an IEP should greatly reduce the racial disparities in teacher perception of student disability. In Model E of Table 3, I found results similar to previous models after controlling for IEP. Asian, Black, and Hispanic students were still less likely to be viewed as having a disability compared to White students. The high odds ratios associated with IEP (OR = 16.03, p < .001) can be interpreted as knowledge of student disability or the fact that students with IEPs struggle academically, scoring nearly 1.0 SD lower on the reading and math tests than students without IEPs. That is, teachers were likely to notice these students’ performance even without knowledge of their IEP status.


A second way to test the robustness of the results is to remove students with IEPs from the analytic sample and fit the same models in Table 3. In other words, among students without IEPs (i.e., without documented disabilities), would there still be racial disparities in teacher perception of students in terms of disability? In Table 4, I replicated Models A–D in Table 3 using a sample that excluded students with IEPs. The main findings were nearly the same, showing that while teachers were more likely to perceive Black, Hispanic, and Native American students as having a disability, the trend was reversed or attenuated after controlling for student background characteristics. The exception is Asian Americans, who were consistently less likely to be perceived to have a disability. Thus, the results in Table 4 suggest that even among students without formal IEPs, there were still racial disparities in teacher perception of whether a student had a disability that appear to reflect differences in student backgrounds.


Figure 1. A comparison of estimates odds ratios of teacher perception of student disability, by racial group (relative to White students) and covariates added sequentially to logistic regression models. IEP = individualized education program


[39_21755.htm_g/00003.jpg]


Table 4. Estimated Odds Ratios From a Taxonomy of Logistic Regression Models Predicting Teacher Perception of Student Disability by Student Race, Controlling for Student, Teacher, and School Characteristics for Students Without Individualized Education Program (IEP) Records (n = 22,298 Student-Teacher Observations)

 

Model A

Model B

Model C

Model D

Student Characteristics

    

  Asian

0.556**

0.505***

0.528**

0.529**

  Black

1.613***

0.775*

0.764*

0.752*

  Hispanic

1.431***

0.720**

0.725**

0.765*

  Native American

2.215**

1.123

1.047

1.078

  Male


1.349***

1.352***

1.373***

  SES


0.998

0.992

0.934

  Read-Math Composite


0.918***

0.918***

0.912***

  Misbehavior


1.360***

1.356***

1.347***

Teacher Characteristics





  Male



0.946

0.954

  White



1.340*

1.285*

  Master's or higher



1.177~

1.156~

  Certified



0.970

0.970

  Experience in years



0.998

0.998

  Special education hours



1.011***

1.012***

  Mathematics class



0.883~

0.879~

School Characteristics





  Percent White




0.862

  Percent LEP




0.797~

  SES Average




1.121

  Reading-Math Average




1.311~

  Urban




1.026

  Suburb




0.964

  Public




0.975

Intercept

0.080***

4.237***

3.103***

5.067***

Note. White students are the race reference group. English is the subject reference category. Rural is the geography reference group. All analyses include sample weights and standard errors are adjusted for students clustering at the school level. ~p<0.10; *p<0.05; **p<0.01; ***p<0.001.


DISCUSSION


This study examined how teachers perceive students in terms of disability. Since teachers are often the first ones to refer students for special education, I asked a descriptive question: To what extent are there racial disparities in teacher perception of student disability? Understanding the extent of these disparities in teacher perception of students provides insight into the referral and placement process and current disproportionality trends in special education. Unlike many previous studies that used vignettes to understand teacher perception, I focused on how teachers perceived their own students in the classroom with national data. Given that teacher perception of student disability may reflect background differences across students and school contexts, I investigated the trends while controlling for these confounding factors.


To summarize, the results show that teachers were on average more likely to perceive Black, Hispanic, and Native American students as a having a disability than White students. Asian American students, on the other hand, were less likely to be perceived to have a disability. However, these raw disparities were attenuated or reversed upon controlling for background factors, especially student achievement and behavior, and remained so even after accounting for whether a student has an IEP. Teacher characteristics and school contextual factors, such as the special education training of teachers and the average achievement level of other students in the same school, also predicted teacher perception of student disability, but did not influence racial disparities after controlling for student background characteristics.


To make the main findings more concrete, consider a teacher who is given a class roster list similar to the one used in ELS:2002 and asked to identify struggling students who may have a disability affecting classwork. The teacher completes the list, and when the raw numbers are totaled, Black students have 1.56 times the odds of being perceived as having a disability compared to White students. If the benchmark for teacher bias is Ferguson’s (2003) unconditional racial neutrality, then the teacher appears biased against Black students. However, this estimate does not account for differences in achievement and other background characteristics between Black and White students. Now, suppose on the roster list is a Black male student with a low reading and mathematics composite score of 45, an average family SES composite of 0.04, and an average misbehavior score of 0.62. Also on the list is a White student with identical characteristics. If the benchmark for teacher bias is conditional racial neutrality, then the odds of being perceived as having a disability should be similar for both students, given that both have the same observable traits, except their race. However, the estimated odds that the teacher will perceive the Black student as having a disability are now about 0.62 times the odds of the White student or nearly 40% lower. In other words, the teacher is less likely to identify the Black student as having a disability when accounting for student background.


Theses results are consistent with recent studies that have found minority children to be less likely to be identified for special education than White children. For instance, studies examining racial disparities in special education placement in elementary and high school found that the raw odds ratios for Black students relative to White students dropped from 1.4–1.6 to 0.5–0.7 after controlling for student background factors (Hibel et al., 2010; Shifrer, Muller, & Callahan, 2011). Morgan et al. (2012) found similar patterns when examining racial minority representation in early childhood special education. Sullivan and Bal (2013), analyzing student data from a large urban district, also observed that racial disparities in special education placement were attenuated after accounting for student-level variables but note that Black students were still overrepresented. More recently, Morgan et al. (2015) found longitudinal evidence that racial minority children were less likely to be identified as having a disability than similar White children after adjusting for potential child- and family-confounds. Although these findings may appear to contradict previous literature on the overrepresentation of minorities in special education, these studies were also able to account for confounding factors that may influence special education placement (for a full review see Morgan et al., 2015).


Theories about the underrepresentation of some minority children in special education tend to focus on socioeconomic and cultural factors. For instance, minority families may decline services if they rely on extended family supports (García Coll et al., 1996) or if they attribute lower academic achievement to nondisability factors (Baker, Miller, Dang, Yaangh, & Hansen, 2010; Yeh, Forness, Ho, McCabe, & Hough, 2004). The stigma of a disability, limited English proficiency, and lack of access to health care may also help explain the underrepresentation of some minority groups in special education (Flores & Committee on Pediatric Research, 2010; Green, 2003; Park, Turnbull, & Park, 2001). However, the present study raises the possibility that teachers and school officials may overlook minority students as well. Although limitations in the dataset preclude knowing whether teachers acted on their perception and referred students for special education, the finding that teachers were less likely to report perceiving minority students as having a disability when they shared similar background characteristics as their White peers challenges the extent that teachers are believed to directly contribute to overrepresentation. This is not to imply that teachers do not behave in other ways that may lead to racial disparities in special education. Harry and Klingner’s (2014) ethnographic study of race and disability in schools showed that special education decisions are complex, often a product of interactions between teachers’ personal beliefs about special education, institutional structures, and school quality that can indirectly contribute to decisions about special education identification.


This study also provides more insight into the experiences of Asian American students who have the lowest special education enrollment rate relative to other racial groups (U.S. Department of Education, 2012). It is unclear whether this disparity stems from parents withholding their children from special education due to language barriers and cultural differences (Baker et al., 2010; Hwa-Froelich & Westby, 2003), or schools struggling to identify Asian American students with disabilities (Lo, 2008). Results from this study show that teachers are consistently less likely to perceive Asian American students as having any disability, with or without controlling for student backgrounds. If teachers are less likely to perceive Asian American students as having a disability, especially when achievement and behavioral levels are similar to those of other students, then this may partly explain the low representation of Asian American students in special education. For some teachers, the model minority perception of Asians may be incongruent with academic struggles due to a disability (Hui-Michael & Garcia, 2009). Indeed, lack of cultural sensitivity and awareness may contribute to teachers overlooking Asian Americans and other students with disabilities who may need services. Scholars also argue that the lack of culturally relevant curricula and teaching in schools contributes to racial disproportionality in special education (Chamberlain, 2005; Gay, 2002).


Lastly, the results do raise the question of why teachers may be less likely to perceive certain minority students as having a disability after controlling for background characteristics. Research in social psychology suggests that minority students may receive less critical feedback from majority group educators who may be concerned with avoiding the appearance of bias (Croft & Schmader, 2012; Shelton, Richeson, & Vorauer, 2006). If criticism can be interpreted as racial bias, majority group educators may be reluctant to provide comments or emphasize positive feedback. This “feedback withholding bias” may be amplified in special education, where districts regularly monitor racial disparities and the teacher workforce is predominantly White (Tyler, Yzquierdo, Lopez-Reyna, & Flippin, 2004). Educators are also likely more aware of racial disparities in special education now than before (Donovan & Cross, 2002). Indeed, accountability laws penalize schools for not improving the achievement of disadvantaged groups each year. Local educational agencies are monitored in terms of disproportionality and, under the most recent authorization of IDEA, may have funding redirected to minimize overrepresentation (Albrecht, Skiba, Losen, Chung, & Middelberg, 2012). To the extent that teachers want to avoid appearing racially biased or fear sanctions for racial disparities in special education at their school, they may be more hesitant to identify minorities as having a disability when their achievement or behavior is similar to that of their White peers (Hibel et al., 2010; Skiba et al., 2006).


LIMITATIONS


This study has several limitations. The first concerns the outcome variable, which asks whether a teacher feels that a student has a learning, physical, or emotional disability that affects his or her schoolwork. Although the survey is framed as an opinion, it is possible that teachers are unable to detect whether a student actually has a disability. Some teachers may actually know whether a student has a disability. However, in the latter case, the results are the same when controlling for IEP status or removing students with IEPs from the analysis. In addition, the survey question groups three disabilities (physical, emotional, or learning) together. Grouping physical, emotional, and learning disabilities together leads to measurement error in the dependent variable, resulting in larger standard errors that reduces the change of detecting statistically significant estimates (Gelman & Hill, 2006). Thus, to the extent that there is measurement error in teacher perception of student disability, the inferences in the study may be more conservative than expected.


A second limitation is that the study cannot examine with the ELS:2002 data whether teachers act on their perception of student disability and refer students for special education services. Thus, I cannot estimate a direct link between disparities in teacher perception of student disability and disproportionality in special education. Although this study is an improvement on the earlier simulated studies using vignettes, it must assume that how teachers perceive students influences classroom decisions like special education referral. This assumption is supported by research showing that teacher perception of student disability does predict referral for special education (Abidin & Robinson, 2002; Podell & Soodak, 1993; Schwartz et al., 1997). A related concern is that ELS:2002 surveyed students and their teachers in the 10th grade. If students have already been sorted into different classes based on prior achievement or disability, then this may impact their current academic performance and how teachers perceive them. Furthermore, at this later grade level teachers may be less likely to take the steps to refer students for special education. More qualitative research is needed to understand whether teacher perception of disability in high school impact racial disparities in special education referrals.


Third, I cannot fully account for the nonrandom sorting of students into schools and classrooms. For instance, parents may choose schools that have high expectations and educate students identically regardless of disability. To the extent that the parents of Black and Native American students have less access to these schools, this may contribute to the racial disparities in teacher perception in this study. Although omitted variable bias is always an issue, I mitigate some of the bias by controlling for a range of student and school factors. Lastly, the generalizability of the results may be limited to the data collection period (i.e., early 2000s). Although teacher perception of student disability may have changed since then, the influence of student background characteristics on perception would likely remain.


IMPLICATIONS FOR PRACTICE AND RESEARCH


The study shows that teacher perception of student disability is in part related to student characteristics like academic performance and behavior. However, teachers are less likely to identify minority students as having a disability when their academic performance and behavior are similar to those of White students. This suggests that although teacher perception of student disability is informed to an extent by these factors, teachers may need additional assistance in detecting disabilities among culturally and linguistically diverse students. Indeed, research shows that cultural mismatch in behavior and expectations between teachers and students can contribute to racial disparities in special education (Tyler et al., 2004). Part of the challenge for educators is to openly discuss broader racial disparities in education (Skiba et al., 2006) and recognize how race, class, and culture can serve as barriers to educational opportunities for students (Blanchett, Klingner, & Harry, 2009).


The concern that students are not receiving services or are not perceived to have a disability highlights a different side of disproportionality in special education that receives less attention in research and practice: the underrepresentation of certain groups. Waitoller et al. (2010) argue that overrepresentation is like “a miner’s canary” warning of unequal access to educational opportunities, but the same can be said of underrepresentation. Few studies examine underrepresentation, particularly of Asian American students, but low enrollment numbers may mean that certain students are not receiving needed services consistently. This study shows that disproportionality can change from overrepresentation to underrepresentation with the inclusion of statistical controls. Whereas underrepresentation based on unadjusted descriptive comparisons of racial groups may suggest low overall enrollment, the presence of underrepresentation with statistical controls indicates that more research is needed in understanding the mechanisms by which students are identified in classrooms. Using nationally representative data in this study addresses population trends, but ethnographic and qualitative methods can provide deeper insight into the decision processes of teachers. In short, educators should monitor both types of disproportionality in special education, while researchers should explore how the mechanisms may be similar or different for each.   


It should be noted that data collection for ELS:2002 occurred before pre-referral strategies and response to intervention (RTI) became a focal point of IDEA (2004) and No Child Left Behind (Fuchs & Fuchs, 2006). The goal of RTI is to identify and support students at risk of academic failure using a multitier approach that differentiates the intensity of instruction and intervention for students depending on their needs. RTI serves as an alternative to identify students with disabilities that emphasizes intervening prior to special education referral. The rise of RTI and similar strategies suggest that teacher perception of student disability may matter less for identifying students for special education. Future research should explore how these interventions impact racial disparities in teacher perception of student disability and ultimately disproportionality in special education.


Lastly, although the racial disparities in teacher perception of student disability in this paper reflected observed differences among students, it is important to remember that perception affect students even if they do not lead directly to special education services. A longstanding concern with special education is that the signaling of an actual disability via an IEP or label may lead to lower academic expectations of students. However, the same possibility exists with teachers thinking that a student may have a disability. Teachers may then have lower expectations of the student, which can affect educational opportunities and achievement. Furthermore, self-fulfilling prophecies can occur when erroneous teacher expectations lead students to perform at a level consistent with those expectations. In future studies, researchers should examine the extent to which teacher perception of disability may affect student outcomes like academic expectations, classroom engagement, and social skills.


Notes


1. Unfortunately, the ELS:2002 dataset used in this study does not contain information on whether a teacher who perceived a student to have a disability also referred the same student for special education. Teacher referral information is not available. See Hosp and Reschly (2003) for a meta-analysis of studies examining referrals.

2. Ferguson notes a third type, racial neutrality conditional on potential, focusing on bias in estimating a child’s full potential. Since future potential is difficult to measure, the third type of bias is harder to assess and less relevant for the present study.

3. Although special education rates for Latino students are low relative to other students at the national level, research indicates that disproportionality for Latinos varies by region (see Pérez, Skiba, & Chung, 2008).

4. The High School Longitudinal Study of 2009 (HSLS:09) is a more recent version of ELS:2002 that follows another cohort of 10th graders. Unfortunately, HSLS:09 did not survey teachers about student disability.

5. The school variables for percent minority and LEP students come from the school administrator survey. The variables are on an ordinal scale (e.g., 1 = 0 to 10%, 5 = 75% or more). For parsimony, I dichotomized the variables based on the distribution.

6. Although IEP information is available in the ELS:2002 data, Shifrer, Muller, and Callahan (2011) observed that some schools only sent in records when a student had a disability, meaning that the variable is coded as missing for students without a disability when it should be “no.” They developed an imputation method to account for this trend that is also used in this study.

7. I found the results were similar when using a random intercept model.

8. I used the sample weight (BYSTUWT), strata (STRAT_ID), and primary sampling unit (PSU) in all analyses.


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Cite This Article as: Teachers College Record Volume 119 Number 7, 2017, p. 1-32
https://www.tcrecord.org ID Number: 21755, Date Accessed: 11/27/2021 9:09:59 PM

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About the Author
  • North Cooc
    University of Texas at Austin
    E-mail Author
    NORTH COOC is an assistant professor of special education and a core faculty member in the Center for Asian American Studies at the University of Texas at Austin. His research focuses on racial disparities in the identification and academic outcomes of children with disabilities at different developmental phases. Some of his recent work has been published in the Journal of Adolescence and Educational Researcher.
 
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