Same-Race Student–Teacher: Comparing Outcomes for Kindergartners With and Without Disabilities

Abstract

Although numerous studies have examined if students of color benefit from having a teacher of the same race/ethnicity, all attention has been paid to students without disabilities. We examine whether the same benefits hold for students with disabilities (SWDs). Using a nationally representative data set of kindergartners, we explored whether SWDs of color had different academic and social–emotional outcomes when with a teacher of the same race/ethnicity. We compared students of color with and without disabilities in the same classroom with regard to a same-race teacher match. Unlike students without disabilities, we do not find evidence in the data set that SWDs of color benefit from a same-race teacher match in terms of achievement and social–emotional development. Implications with regard to educational equity are discussed.

Keywords

education policy same-race national data

With a rising proportion of students of color in the U.S. education system, there is a concern among policy makers and stakeholders that these students are taught by a disproportionately high number of White teachers. The most recent data indicate that while students of color make up approximately 44% of all elementary and secondary schools, only 17.3% of teachers are of color (Ingersoll & May, 2016). In response to this imbalance, policy makers have begun initiatives at institutions that recruit and train new members of the teaching workforce. For example, the Every Student Succeeds Act (ESSA; 2015) explicitly targets federal funds to the recruitment of teachers from underrepresented racial minority groups. In addition, U.S. states have implemented recruitment initiatives designed to grow the number of teachers of color in the labor force (Achinstein, Ogawa, Sexton, & Freitas, 2010; Villegas, Strom, & Lucas, 2012).

When considering racial compositions in American classrooms, it is also important to acknowledge how the inclusion of students with disabilities (SWDs) contribute to these changing compositions as well. Including SWDs has been an expressed priority at the federal level, where SWDs are expected to spend as much time as possible in general education classrooms. Owing to the specific provisions in the Individuals With Disabilities Education Act (IDEA, 2004; for example, least restrictive environment) and the inclusion of SWDs in accountability expectations that all students make adequate yearly progress, schools have increasingly engaged SWDs in the general education classroom (McLeskey, Landers, Williamson, & Hoppey, 2012). For instance, in 1990, only 33% of all school-attending children in the United States spent a majority of their school day (80% of instructional time or more) in general education classrooms (U.S. Department of Education, National Center for Education Statistics [NCES], 2016). Whereas now, 62% of all school-attending children spent a majority of their time in the general education classroom in the fall of 2013 (U.S. Department of Education, NCES, 2016).

When discussing inclusion, it is also important to address racial diversity. Like students without disabilities, there is evidence that the population of SWDs is also racially diverse. In fact, students of color make up approximately half of all SWDs (NCES, 2016). Although little research exists that illustrates the racial diversity of teachers working with SWDs, some work has found a similar discrepancy to the general student population with students of color with disabilities being primarily taught by White teachers (Billingsley, Bettini, & Williams, 2017).

Critical to these policy conversations about ensuring the success of diverse student populations via the teaching population, kindergarten teachers are especially important. Kindergarten is a formative year of schooling where students experience new academic and social challenges. Specifically for SWDs who are more prone to experiencing academic and social difficulties in school (Janus, Lefort, Cameron, & Kopechanski, 2007; Kazak & Marvin, 1984; Ray, 2003), there is a rising need to ensure that schools maintain the appropriate teaching resources to support students during this year of school.

The empirical research that demonstrates that a diverse teaching workforce has clear benefits for students of color in the general student population (Wright, Gottfried, & Le, 2017; Dee, 2004; Egalite, Kisida, & Winters, 2015; Grissom, Kern, & Rodriguez, 2015; Rocha & Hawes, 2009; Villegas & Irvine, 2010). There is also a considerable push for SWDs to be educated in general education classrooms and schools. Thus, we consider whether SWDs of color benefit from having teachers who share their race/ethnicity in general education kindergarten classrooms. Specifically, we asked the following research questions:

Research Question 1: Does having a kindergarten teacher of the same race/ethnicity improve achievement or social–emotional outcomes for students of color with disabilities?

Research Question 2: How do these associations differ compared with students without disabilities?

Same-Race Matching and Achievement

Much literature validates the academic returns of student–teacher race/ethnic similarities in the classroom. For instance, Egalite et al. (2015) examined 8 years of longitudinal data from the Florida Department of Education and found that students—particularly students who were previously low-achieving—scored higher on achievement tests in math and reading when matched to teachers of the same race/ethnicity. Using data from Tennessee’s Project STAR, where students were randomly assigned teachers who shared their races/ethnicities, Dee (2004) examined the effect of same-race matching on student achievement and found the strongest results for Black students.

Of the numerous possible explanations for why sharing racial or cultural similarities benefit students of color, there are two with great empirical foundations that may apply to SWDs of color. First, White teachers may be more greatly dispositioned to exhibit implicit bias toward students of color in their classrooms. Implicit bias is a manifestation of stereotypical assumptions based on students’ race or culture, where teachers may show lower expectations for students and provide lower level instruction (Jacoby-Senghor, Sinclair, & Shelton, 2016). As a result of implicit bias, students may receive a lower quality of education and, therefore, do more poorly on exams (van den Bergh, Denessen, Hornstra, Voeten, & Holland, 2010). Second, it may be the case that White teachers are less likely to be culturally competent in their classrooms, particularly when it comes to teaching students of racially and culturally diverse backgrounds. Teachers who have backgrounds more similar to their students’ experiences may provide better and more relevant instruction for these students compared with teachers without these similarities (Brown, 2009; Ladson-Billings, 1992), which may lead to higher expectations for students of color in their classrooms (Mahatmya, Lohman, Brown, & Conway-Turner, 2016). In addition, teachers of color may serve as academic role models for their students and help students of color navigate their lives at school (Villegas & Irvine, 2010).

It may be possible to extrapolate from these findings that SWDs of color would also benefit academically have having a teacher of the same race/ethnicity. There is a link between teacher expectations and academic achievement for SWDs (Klehm, 2014), which likely exists because teachers’ expectations are connected to instructional time and content coverage (Kurz et al., 2014). If teachers in general have lower academic expectations for SWDs, then it might be the case that a teacher who shares a student’s race/ethnicity may actually increase expectations, per the mechanism described just above, and thereby improve instructional quality.

Same-Race Matching and Social–Emotional Outcomes

Some research has examined the link between student and teacher race/ethnicity and socioemotional skills assessments. Wright, Gottfried and Le (2017) examined nationally representative data to test the association between same-race teachers and students of color with social–emotional outcomes. The findings from this study illustrated that teachers of color who shared their race/ethnicity with their students were more greatly dispositioned to report these students as having fewer externalizing behavior problems compared who did not share racial/ethnic congruence. Similarly, Downey and Pribesh (2004) examined Early Childhood Longitudinal Study–Kindergarten (ECLS-K) Class of: 1999 and found that African American teachers rated their African American students as having fewer externalizing behavior problems than ratings from White teachers for their White students. Similarly, Dee (2005) found that students who did not share the same race/ethnicity with their teachers were more likely to be rated as disruptive and inattentive. Finally, Egalite and Kisida (2017) found that fourth- through eighth-grade students matched by race had higher self-reported positive feelings about school; the results were even stronger when matched by gender and race. It is important to note that there is also some literature that found no effect between the race-matching of students and teachers and students’ socioemotional ratings (Jennings & DiPrete, 2010).

To explain why race-matching might matter in this regard, racial/ethnic similarities is one proposed framing for understanding how teacher ratings on socioemotional skills assessments associates with shared race/ethnicity (Wright, Gottfried, & Le, 2017). Although, it is worth noting that there is wide cultural variability within racial/ethnic groups (Achinstein & Aguirre, 2008). Keeping this in mind, it still might be the case that students of color may struggle to adjust behaviorally in schools (Delpit, 1995), likely due to the dissonance experienced in a context dominated by White, middle-class customs, and ideals (Morris, 2005). These students may be labeled as acting out or otherwise misbehaving in school simply due to the lack of conformity in what is deemed acceptable. In this framework, a teacher who shares racial or cultural similarities with students may leverage common experiences in the classroom, and through these experiences, teachers of color offer students of color alternative and perhaps more familiar perspectives (Achinstein & Ogawa, 2011; Irvine, 1988; Ladson-Billings, 1992). In this case, one would expect that teachers of color would rate students of color more favorably on social–emotional skills assessments. This latter point brings up a critical issue. It may be that on one hand, students of color do indeed have more positive social–emotional outcomes when learning from a teacher of color. On the other hand, it might be that racial biases are shaping teachers’ ratings of student behavior. From these studies, it is not possible to conclude with certainty that more positive social–emotional outcomes for students of color are necessarily arising due to having teachers of color. Rather, all of these studies rely on teacher ratings of students, which stands in contrast to standardized testing outcomes discussed in the prior section.

Such framework informs the present study in extending this relationship between socioemotional skills ratings and race-matching for SWDs of color. Similar to the notion of how racially underrepresented students may be at odds with behavioral contexts in their schools, SWDs have routinely been seen as behaving less appropriately in school based on their disability (Lane, Wehby, & Cooley, 2006), and these attitudes are often shaped by the prevailing expectations at the school (MacFarlane & Woolfson, 2013). Specific to SWDs of color, a teacher who shares their race/ethnicity is already sharing a closer-aligned identity. This innate aspect of the teacher may help SWDs of color. Thus, the socioemotional ratings for these students who have a same-race teacher may certainly differ from those SWDs of color with a White teacher.

Method

Sample

The data used in this study come from the Early Childhood Longitudinal Study—Kindergarten Class of 2010-2011 (ECLS-K: 2011). Created by the NCES, ECLS-K: 2011 is the most current data available for young children and their schooling experiences in early education. During the 2010-2011 academic year, NCES collected data in the fall and spring about children in kindergarten through assessments as well as parent, teacher, and school administrator surveys. ECLS-K: 2011 used a three-stage stratified sampling strategy in which geographic region represented the first sampling unit, public and private schools represented the second sampling unit, and students stratified by race/ethnicity represented the third sampling unit.

We restricted our analytical sample of student-level observations based on three primary criteria. First, we analyzed only African American and Latinx (general education) teachers and students, with White teachers and students serving as the reference group. We did not include Asian American, Native American, or Pacific Islander teachers and students in our sample because there were very few same-race student–teacher matches for these groups (although our results are robust to their inclusion). Second, to identify student and teacher race/ethnicity and include student control variables in our regression specifications, we required nonmissing data on relevant teacher and student background characteristics and at least one social–emotional assessment, math score, or reading score. Third, we limited our sample to students assessed by the same teacher in the fall and spring surveys, thereby providing for consistency between assessment waves. These criteria resulted in 7,980 student-level observations in the final sample. To comply with NCES reporting standards, sample sizes were rounded to the nearest 10.

After completing these restrictions, we compared demographic differences between the original sample and the analytic sample. Most characteristics were almost identical or different by 1% or less. Hence, there are not many differences between these samples. The only exception was that dropped observations were more likely to be ELL (English language learner) students, students from lower socioeconomic status (SES) background, and more likely to come from a family where there is not biological or adoptive parents in the home.

Determination of Race/Ethnicity and Disability Status

Students’ race/ethnicity was designated by NCES as they collected data, and teachers’ race/ethnicity was self-reported through surveys. Students’ disability status was obtained through a parent interview and indicated whether the child had a disability diagnosed by a professional. Questions in the parent interview asked about the child’s ability to be independent and take care of himself or herself, ability to pay attention and learn, overall activity level, overall behavior and ability to relate to adults and children, emotional and psychological difficulties, ability to communicate, difficulty in hearing and understanding speech, and eyesight. Note, however, that the sample sizes of each of the 13 IDEA disability categories were not sufficient to examine specific disability category in this study. There were several additional tests of robustness in regard to the determination of disability status. First, disability status was restricted to include students with an individualized education program (IEP) on file in the kindergarten school year. Next, restrictions were broadened to include students who had an IEP on file in the 2011-2012, 2012-2013, or 2013-2014 school years. Note that regardless of criteria, the results of the primary finding of this study never changed.

Achievement Outcomes

NCES developed assessments of math and reading, and they were administered by trained and certified assessors in the fall and spring of the kindergarten year. The math assessment included questions on number sense, properties, and operations; measurement; geometry and spatial sense, data analysis, statistics, and probability; and patterns, algebra, and functions. The reading assessment consisted of questions on print familiarity, letter recognition, beginning and ending sounds, rhyming words, word recognition, vocabulary knowledge, and reading comprehension. The reliability coefficient ranged from 0.92 to 0.99 (Tourangeau et al., 2012). Additional details about these assessments are publicly available, through the NCES website.

Social–Emotional Outcomes

Teachers completed assessments of students’ social–emotional skills in the fall and spring of the kindergarten year. The surveys contained a series of question items that were then combined to create social–emotional scales. The social–emotional scales were constructed based on the Social Skills and Rating System (SSRS; Gresham & Elliot, 1990). NCES adapted the SSRS to create its own teacher Social Rating Scales (SRS). The SRS in the data set consisted of five scales that gauged the extent that students exhibited various social–emotional skills. The five-item externalizing behaviors scale assessed the frequency with which a child argued, fought, got angry, acted impulsively, and disturbed ongoing activities. The four-item internalizing behaviors scale measured the extent that the child exhibited anxiety, loneliness, low self-esteem, and sadness. The five-item interpersonal skills scale measured the frequency with which a child got along with others, formed and maintained friendships, helped other children, showed sensitivity to the feelings of others, and expressed feelings, ideas, and opinions in positive ways. The seven-item approaches to learning scale rated the frequency that the child kept his or her belongings organized, showed eagerness to learn new things, adapted to change, persisted in completing tasks, paid attention, and followed classroom rules. The four-item self-control scale measured the extent that the child was able to control his or her temper, respected others’ property, accepted his or her peers’ ideas, and handled peer pressure.

Teachers’ responses to each four-point Likert-type item were averaged to create scale scores. Higher scale scores indicated more frequently exhibited behaviors. For the externalizing and internalizing scales, a higher score reflects a less favorable outcome. On the three other scales, a higher score reflects a more favorable outcome. All the scales had high internal consistency, with the alpha reliability coefficients ranging from .79 to .89 (Tourangeau et al., 2012).

Control Variables

Student demographic characteristics

Our empirical analysis included control variables commonly associated with differences in social–emotional ratings and achievement test scores, including gender, age, race, disability status, and an indicator for ELL based on primary language spoken at home (Duncan & Magnuson, 2011; Garcia, 2015). In addition to these standard demographic measures, we also included a parental-rated scale of child health with a value of 1 being highest and 5 being lowest. Poor health has been linked to weaker social–emotional functioning, even from an early school age (Meijer, Sinnema, Bijstra, Mellenbergh, & Wolters, 2000).

Childcare

Prior research indicates a link between childcare in the years leading up to kindergarten and social–emotional outcomes once in kindergarten, (Loeb, Bridges, Bassok, Fuller, & Rumberger, 2007; Magnuson, Ruhm, & Waldfogel, 2007; Yamauchi & Leigh, 2011). Therefore, we included the following commonly employed childcare control variables as indicators that described a student’s care in the year prior to kindergarten: center-based care, head start, nonrelative care, and relative care (with parental care serving as the reference group). We also included an indicator to denote whether the child has ever participated in any type of center-based care as well as the number of nonparental weekly care hours to control for the fact that intensity of care might be linked to outcomes once in kindergarten (Loeb et al., 2007).

Family characteristics

Family characteristics included SES, family structure, and the home environment. Research has linked SES to social–emotional functioning in children (Bradley & Corwyn, 2002; Sarsour et al., 2011). Therefore, we included an NCES-created composite of SES, which were comprised of items relating to parental educational attainment, occupational prestige, and family income. We separated this composite into quartile indicators for our regression analysis. We also included information about whether two biological or adoptive parents were present in the student’s home, as it has been shown that parental structure can influence children’s social–emotional development (Amato, 2005; Kupersmidt, Griesler, DeRosier, Patterson, & Davis, 1995).

In addition, we replicated two scales from Votruba-Drzal, Li-Grining, and Maldonado-Carreño’s (2008) study that assessed the quality of the home environment. We controlled for home environment because previous studies have found the quality of the home environment to be positively correlated with students’ social–emotional outcomes (Harden & Whittaker, 2011). The first scale consisted of 10 items that were measured on a 4-point Likert-type metric. The scale assessed the frequency that parents engaged the child in various activities that promoted cultural, academic, or social enrichment. These activities included playing games, singing songs, and reading books. The second scale, comprised of 15 dichotomously scored items, assessed children’s access to learning materials. This scale assessed whether in the past month the child engaged in activities such as visiting a book store, taking music lessons, participating in recreational sports, or attending tutoring lessons. These activities represent whether a child is participating in learning activities, which may or may not be free to the family, offered by a child’s school or community, or paid for by another relative or friend of the family. These composite scores were transformed to have a mean of 0 and standard deviation of 1 within the sample.

Classroom characteristics

Previous literature has found a positive association between having more peers of the same race/ethnicity and positive socioemotional outcomes (Benner & Crosnoe, 2011). Because the proportion of same-race classmates was highly correlated with having a same-race teacher for students of color in our sample, it was imperative to control for this percentage (i.e., the percentage of African American or Latinx students in the classroom) to separately identify the association between having a same-race teacher and student outcomes. We included an indicator for whether the student attended full-day kindergarten. Finally, we included the number of hours the student spent outside of the general education classroom in instruction/services.

Analytic Approach

To assess whether students of color demonstrated academic or social–emotional gains from having a teacher of color of the same race/ethnicity, we used a gain-score model of student-level outcomes. We adopted a similar approach as other studies that have examined student–teacher race matching (Wright, Gottfried, & Le, 2017; Fairlie, Hoffman, & Oreopoulos, 2014) and estimated the gain score (spring score/rating minus fall score/rating), $y_{i c}$ , as:

\begin{array}{l} y_{i c} = α_{0} + α_{1} P C t e a c h_{c} + α_{2} P C s t u d_{i} + δ_{1} P C t e a c h_{c} \\ \times P C s t u d_{i} \times s a m e_{i c} + δ_{2} P C t e a c h_{c} \\ \times P C s t u d_{i} \times d i f f_{i c} + X_{i}^{’} β + ε_{i c} \end{array}

(1)

where students were indexed by i and classrooms by c. In the model, the indicator variable $P C t e a c h_{c}$ equaled 1 if teacher c was a person of color—African American or Latinx. Analogously, $P C s t u d_{i}$ equaled 1 if student i was a person of color—African American or Latinx. The indicator $s a m e_{i c}$ equaled 1 if student i and classroom teacher c shared the same race/ethnicity—that is, this variable took on a value of 1 if the student was African American and the teacher was African American or if the student was Latinx and the teacher was Latinx. The indicator $d i f f_{i c}$ equaled 1 if student i and classroom teacher c did not share the same race/ethnicity. The term $X_{i}$ in the equation represents all student-level control variables described above.

The parameter of interest, $δ_{1}$ , measured whether race-matched students of color had larger gains ( $y_{i c}$ ) relative to White students when each had a teacher of color compared with this difference in gains ( $y_{i c}$ ) when each was taught by a White teacher. In other words, $δ_{1}$ measured the differential gains in outcomes between race-matched students of color and White students based on having a teacher of color versus having a White teacher. To determine whether achievement or social–emotional gains from having a teacher of color of the same race/ethnicity varied by student disability status, we fully interacted binary indicators for whether the student did or did not have a disability with the regressors in Equation 1. In other words, the results presented show separate coefficients by subsamples.

One potential issue with Equation 1 is that we have not controlled for the myriad of unobserved classroom-specific factors that affect student achievement and social–emotional growth and assessment. Thus, we also included classroom fixed effects in our preferred specification. That is, we included binary variables for each classroom with one classroom omitted to serve as the reference category and dropped the collinear teacher of color indicator and full-day kindergarten indicator. As students were contained in one kindergarten classroom throughout the day, including classroom fixed effects means we have held constant all unobserved class-level experiences and teacher influences during the school year, such as the possibility that different teachers systematically assessed their students differently.

In all models, standard errors were clustered at the classroom level. Because students in the same classroom likely shared common but unobservable characteristics and experiences, clustering student data at the classroom level provided for a corrected error term given this nonindependence of student observations. Finally, observations were weighted using ECLS-K: 2011 sample weights to estimate representative effects.

Results

Descriptive Statistics

Descriptive statistics for the analytical sample are given in Table 1. Panel A of Table 1 gives student and teacher composition by race/ethnicity and Panel B gives the mean and standard deviation of the achievement (math and reading) and social–emotional outcomes by race/ethnicity and disability status. Approximately 11% of all general education students were students of color matched with teachers of color of the same race/ethnicity; within this subsample, 9% were students without disabilities and 2% were SWDs. In general, both samples, students of color have lower average achievement and social–emotional scores relative to White students.

Table 1.

Descriptive Statistics.

	Students		Teachers
	Mean	Total observation	Mean	Total observation
Panel A. Student and teacher shares by race/ethnicity and disability status		7,980		2,370
White	0.63		0.82
Person of color	0.37		0.18
Student with a disability	0.19		—
Share of observed person of color student–teacher same-race match, nondisabled students	0.09
Share of observed person of color student–teacher same-race match, disabled students	0.02
	White		Person of color
	Nondisabled	Disabled	Nondisabled	Disabled
Panel B. Mean of student outcomes by race/ethnicity and disability status
Math test score (fall)	0.29 (0.95)	0.03 (1.02)	−0.37 (0.91)	−0.47 (0.94)
Math test score (spring)	0.31 (0.89)	−0.02 (1.08)	−0.34 (0.95)	−0.55 (1.00)
Math observations: 7,930
Reading test score (fall)	0.21 (1.02)	−0.02 (1.02)	−0.24 (0.89)	−0.35 (0.93)
Reading test score (spring)	0.23 (0.95)	−0.07 (1.04)	−0.24 (0.96)	−0.41 (1.01)
Reading observations: 7,930
Externalizing behaviors (fall)	−0.11 (0.91)	0.24 (1.16)	0.01 (0.99)	0.29 (1.18)
Externalizing behaviors (spring)	−0.11 (0.93)	0.20 (1.13)	0.05 (1.01)	0.21 (1.09)
Externalizing observations: 7,570
Internalizing behaviors (fall)	−0.04 (0.95)	0.22 (1.08)	−0.07 (0.99)	0.22 (1.16)
Internalizing behaviors (spring)	−0.08 (0.93)	0.20 (1.07)	−0.01 (1.04)	0.29 (1.13)
Internalizing observations: 7,520
Interpersonal skills (fall)	0.12 (0.95)	−0.17 (1.05)	−0.04 (1.00)	−0.30 (1.10)
Interpersonal skills (spring)	0.14 (0.94)	−0.17 (1.08)	−0.03 (1.00)	−0.29 (1.05)
Interpersonal observations: 7,230
Approaches to learning (fall)	0.16 (0.95)	−0.24 (1.06)	−0.06 (0.99)	−0.40 (1.06)
Approaches to learning (spring)	0.16 (0.93)	−0.26 (1.06)	−0.05 (1.01)	−0.41 (1.05)
Approaches observations: 7,780
Self-control (fall)	0.13 (0.93)	−0.21 (1.09)	−0.04 (1.00)	−0.32 (1.11)
Self-control (spring)	0.14 (0.94)	−0.19 (1.08)	−0.07 (1.02)	−0.28 (1.05)
Self-control observations: 7,170

Note. All student outcomes are standardized to be mean zero and standard deviation one by assessment wave.

Achievement Outcomes

We report estimates of the persons of color student–teacher same-race interaction by student disability status for the math and reading gain-score outcomes in Table 2. Column 1 gives estimates from Equation 1 and column 2 gives estimates from the preferred specification with classroom fixed effects. We found no evidence that students of color with same-race teachers experienced gains in math or reading scores. This was true for both students with and without disabilities.

Table 2.

Estimated Effects of Teacher–Student Matching on Math and Reading Scores.

	1	2
Math test score
Persons of color student–teacher same-race interaction: Nondisabled students	0.09 (0.05)	0.03 (0.10)
Persons of color student–teacher same-race interaction: Disabled students	0.05 (0.08)	−0.02 (0.12)
Reading test score
Persons of color student–teacher same-race interaction: Nondisabled students	−0.09 (0.06)	−0.11 (0.10)
Persons of color student–teacher same-race interaction: Disabled students	−0.10 (0.06)	−0.05 (0.13)
Fixed effects
Classroom	No	Yes
Controls
Student controls	Yes	Yes

Note. Each pair of same-race interactions by disability status represents a separate ordinary least squares regression.

p < .05.

Social–Emotional Outcomes

We report estimates of the same-race interaction variables by disability status for the five social–emotional gain-score outcomes in Table 3. As in Table 2, column 1 reports estimates from Equation 1 and column 2 reports estimates from our preferred specification with classroom fixed effects. For externalizing behaviors, we found a statistically significant effect (p < .05) of student–teacher race match for nondisabled students of color, with the effect size suggesting that these behaviors improved by 0.31 standard deviations. However, improvements in disruptive behavior did not appear to carry over to SWDs; we could not reject that their race-match coefficient was statistically different from zero. The race-match coefficient was also null for internalizing behaviors, interpersonal skills, approaches to learning, and self-control for both disabled and nondisabled students. In addition, we found no effect of the different-race person-of-color interaction ( $δ_{2}$ in Equation 1) on any of the student outcomes using our preferred model. Hence, while SWDs did not benefit from a same-race teacher match, students without disabilities did for externalizing problem behaviors, as consistent with Wright, Gottfried and Le (2017).

Table 3.

Estimated Effects of Teacher–Student Matching on Social–Emotional Skills.

	1	2
Externalizing behaviors
Persons of color student–teacher same-race interaction: Nondisabled students	−0.08 (0.06)	−0.31* (0.13)
Persons of color student–teacher same-race interaction: Disabled students	−0.05 (0.12)	−0.30 (0.18)
Internalizing problem behaviors
Persons of color student–teacher same-race interaction: Nondisabled students	−0.14 (0.08)	−0.01 (0.17)
Persons of color student–teacher same-race interaction: Disabled students	−0.22 (0.14)	−0.10 (0.25)
Interpersonal skills
Persons of color student–teacher same-race interaction: Nondisabled students	0.07 (0.08)	0.10 (0.14)
Persons of color student–teacher same-race interaction: Disabled students	−0.01 (0.12)	0.01 (0.18)
Approaches to learning
Persons of color student–teacher same-race interaction: Nondisabled students	0.04 (0.07)	0.03 (0.12)
Persons of color student–teacher same-race interaction: Disabled students	−0.06 (0.10)	−0.09 (0.15)
Self-control
Persons of color student–teacher same-race interaction: Nondisabled students	−0.02 (0.08)	−0.01 (0.16)
Persons of color student–teacher same-race interaction: Disabled students	−0.16 (0.13)	−0.04 (0.21)
Fixed effects
Classroom	No	Yes
Controls
Student controls	Yes	Yes

Note. Each pair of same-race interactions by disability status represents a separate ordinary least squares regression.

p < .05.

Discussion

Students of color continue to grow as a proportion of the U.S. population (Ingersoll & May, 2016). Consequently, recent research and policy have called for the demographics of the teaching workforce to better represent the students it educates, given the disproportionately low number of teachers of color in our current education workforce (Ingersoll & May, 2011). As one evidence base to support the necessity for increasing the number of teachers of color, there has been a surge of studies examining whether students of color have higher schooling outcomes when taught by teachers of color and in elementary and secondary schooling (Wright, Gottfried, & Le, 2017; Dee, 2004; Egalite & Kisida, 2017; Egalite et al., 2015; Grissom et al., 2015; Rocha & Hawes, 2009; Villegas & Irvine, 2010).

That said, there has been a significant oversight in this line of inquiry—an oversight addressed in this present study. Namely, alongside changes to student racial demographics in our nation’s classrooms, the number of SWDs entering into general education classrooms and schools has also been increasing (McLeskey et al., 2012). Therefore, it is surprising that while much of recent research has focused on the effects of student–teacher race matching for students of color in the general education population, little attention has been paid on the same issues for students of color in the subpopulation of SWDs.

We addressed this oversight with two key foci in mind. First, we focused on SWDs in general education kindergarten classrooms. SWDs are increasingly being educated in general education classrooms and schools as prescribed by federal policy, namely IDEA (U.S. Department of Education, 2015). As a result, classroom demographics are changing, and, yet, little work has examined the dynamics of educating SWDs in these general education classrooms (Author et al., 2018). Therefore, better understanding of the context for SWDs in general education classrooms is underexplored, yet, extremely critical given this national shift with regard to where (and potentially how) SWDs are being educated. In other words, today’s classrooms are increasingly being composed of students from both minority and disability backgrounds.

Second, we focused on kindergarten. Kindergarten represents a major transition when children are engaging with new children and adults as well as taking on new educational and social experiences. Although it has been established for some time that kindergarten can often be difficult and stressful for all children (Ladd & Price, 1987), the first year of schooling might prove to be more difficult for SWDs who face physical, emotional, developmental, and intellectual challenges (Author et al., 2016; Janus et al., 2007; Kazak & Marvin, 1984; Ray, 2003). Hence, understanding how a student–teacher race match might support the transition into kindergarten for a particularly vulnerable group of students could provide insight into critical supports and resources that schools could use to ensure student success.

Therefore, for the first time in the field, we addressed whether SWDs of color paired with teachers of color had higher schooling outcomes (and whether this varied by disability). To address this, we relied on a nationally representative data set of kindergartners that contained information on disability as well as data on demographics of students and their teachers, along with other key measures. In addition, given that numerous students were sampled in the same classroom, we were able to rely on within-classroom variation on student–teacher race match, both for students of color with and without disabilities in the very same classroom. Thus, we could compare findings between students of color from both groups.

Answers to our research questions suggest that in kindergarten, SWDs of color did not experience any benefit from having teachers of the same race. However, students of color without disabilities did benefit from having teachers of the same race, when it came to reducing externalizing problem behaviors. Therefore, the null finding of student–teacher racial match is specific to the sample of SWDs, and there are several implications to consider.

The first implication is in regard to the kindergarten transition and teachers. Although kindergarten may be stressful, our analyses do not find evidence that the demographic student–teacher match for SWDs eases this transition, as no positive effects surfaced for this group of students. Further inquiry into this issue might address whether and why students of color without disabilities are truly benefiting from same-race teachers whereas SWDs of color do not appear to be doing so. This further line of investigation must ask whether same-race matching efforts will cause disabled–nondisabled gaps to emerge if it is the case that only one group seems to be benefiting. Therefore, as schools charge forward with ways to construct supportive general education classrooms along the lines of the interplay of teacher–student demographics, this study urges for policy makers and practitioners to consider how teacher characteristics also help SWDs benefit. If race matches do not serve to support SWDs’ success, we might consider what other teacher characteristics may. Otherwise, this recent surge and charge forward of using student–teacher race matching as a policy lever has the potential to leave SWDs behind in general education classrooms.

Second, in this regard, this study urges for further examination of how teachers might be able to influence SWD outcomes beyond demographic characteristics. For instance, for SWDs, the importance of teachers may be in training rather than in demographics. Teachers raise concerns that educating SWDs can be difficult (McLeskey et al., 2012). Therefore, it may not be the case that assessing a student–teacher demographic match is sufficient to improve outcomes for students who face additional educational challenges. Therefore, further inquiry in this area must turn to addressing additional ways that general education teachers might affect the outcomes of SWDs, such as through professional development and experience. These other characteristics, which focus more explicity on improving instructional quality, might prove to be more impactful for SWDs of color.

Finally, the null findings in this study do not alleviate concerns about the synergistic combination of being of color and having a disability. Although student–teacher race did not improve outcomes for SWDs of color, we might look for other ways to assess what factors support SWDs. That is to say, in this particular context of student–teacher match, there was no observed benefit of the interplay of race and disability status. This does not imply that in other school contexts, race and disability status would not have benefits. For example, there might be positive peer effects, given that prior research has found that the classroom overall has higher performance when SWDs and girls are paired together in kindergarten classrooms (Gottfried & Harven, 2015). These would merit further analysis.

In sum, as schools attempt to address how to best support SWDs, we did not find evidence that student–teacher matching serves as a silver-bullet strategy of doing so, at least for students in kindergarten. Our study highlights that students without disabilities do benefit from such a matching strategy and, therefore, cautions that prior research, which has ignored paying attention to SWDs, has failed to address how this practice might further exacerbate schooling gaps in general education classrooms. It is without doubt that teachers are important for student growth and development, as this is fairly uncontested in the research base and among policy makers and practitioners. However, further work is required to determine exactly how teachers (and the classrooms in which they teach) can best benefit those facing additional challenges.

Limitations

There are several limitations in this study that can be used to address future research. First, while important to examine the onset of formal schooling, a study of kindergarten cannot address how student–teacher race matching might influence outcomes at an older age. Perhaps, student–teacher race matching for SWDs becomes important in older grades. Thus, future research might examine how SWDs of color in later elementary, middle, or high school might have unique outcomes based on having a teacher of the same race. This might be particularly important when considering achievement outcomes, given the role of state assessments starting around third grade. An additional benefit of examining middle or high school is that students frequently move classes depending on subject area, and thus, this would open the possibility to examine the effects of numerous teachers vis-a-vis race matching.

Second, our social–emotional outcomes were teacher rated as students were too young in kindergarten to self-evaluate themselves. Therefore, it was not possible to evaluate feelings of belonging or self-efficacy among SWDs of color who have teachers of color. Although social–emotional outcomes might not change, it might be the case that SWDs of color do feel other, currently unmeasured connections to teachers of the same race—feelings that might help boost latter trajectories and outcomes. Future research might consider how to best measure these other attributes for young children, perhaps with a single site study.

Third, while this study was nationally representative of the kindergarten experience in general education classrooms, this did exclude children in special education kindergartens. The classroom experience of attending school in special education settings may differ significantly compared with those in general education classrooms (Stiefel et al., 2018). Although this does not necessarily bias the current study, it nonetheless does not offer a description of those in special education. In addition, it might be the case that general education kindergartners might serve SWDs who are more affluent or more White, and this study might provide a different perspective than if we also had included special schools. Although this study focused on inclusive settings, a future study might focus on comparing inclusive versus special settings as a next point of comparison. Therefore, a follow-on study of SWDs in special education classrooms or schools might help provide a richer portrait of the role of teacher–student race matching.

Finally, national data prove to be valuable in its scale and scope. However, it was not possible to draw conclusions about students and teachers in urban school systems, where there are higher percentages of students of color compare to using a nationally representative sample. Therefore, future research might consider exploring the findings here with those from our nation’s urban school systems, where student–teacher race match might be especially important for those students living in poverty. In addition, these national data—while representative—does not provide a sufficient enough sample size to examine specific IDEA disability categories when it comes to race matching. Again, large-scale urban district data might prove useful in this regard, where the sample sizes are much larger. Using alternative sources of data will help compare and collaborate findings, ultimately building a body of evidence used to support the education and growth of SWDs in classrooms and schools across the country.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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