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It’s Complicated: Understanding Disproportionality

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Disproportionality first came into the public consciousness during the tail end of the civil rights movement in the 1960s (Cruz & Rodl, 2018; Morgan, Farkas, Hillemeier, Mattison, Maczuga, Li, & Cook, 2015; Skiba, Artiles, Kozleski, Losen, & Harry, 2016; Skiba, Poloni-Staudinger, Simmons, Renae Feggins-Azziz, & Chung, 2005; Sullivan and Bal, 2013). It is the idea that ethnic, racial, and language minority students are grossly overrepresented in special education (Cruz & Rodl, 2018; Morgan et al., 2015). Because of the Individuals with Disabilities Act (IDEA), there are many school children with disabilities who receive Free Appropriate Education (FAPE) across the United States. If disproportionality is the issue, then there are children receiving services that don’t need it. If it is truly an issue of underrepresentation, then minority students are not getting the services they need. It is important to understand what the true characteristics of disproportionality are. Not only does it affect those serviced by IDEA, it affects policymakers as well. IDEA only provides funds for overrepresentation and not underrepresentation (Morgan et al., 2015).

There is a large amount of research examining disproportionality with some areas of agreement, largely in terms of future research. Many pertinent suggestions ranged from more studies at the local and individual level to having a national, large scale study across several grade levels (Skiba et al, 2016; Cruz & Rodl, 2018; Skiba et al, 2005; Sullivan & Bal, 2013; Morgan et al., 2015). Even though there are certain areas in which researchers agree, the findings of the research often conflict.

There seems to be a lack of overall consistency in several areas. Several studies have used different data sets, different systems of analysis, only examined certain minority groups and certain disabilities to name a few (Cruz & Rodl, 2018). Several studies discuss how disproportionality is a multifaceted issue rife with contradictions between studies. Some researchers mentioned a “frog pond effect”. The two studies that mention this gave two different definitions. One states that the “frog pond effect” is when high minority schools tend to be lower performing and thus less likely than high performing schools to identify lower performing minorities for special education (Morgan et al., 2015). The other states that “frog pond” is when lower performing students in high achieving schools are at a greater increase for being placed in special education (Sullivan & Bal, 2013). Interestingly, both studies referred to the same article when mentioning this term.

Morgan et al. (2015) argued that it is not overrepresentation but rather underrepresentation plaguing minorities. Most researchers disagree and feel some groups are more marginalized that others and some are overrepresented (Sullivan & Bal, 2013, Skiba et al., 2016). This can vary by individual schools and school districts among others (Sulivan & Bal, 2013, Skiba et al, 2005). Skiba et al. (2016) pointed out several critical errors in Morgan et al. (2015) study such as using a poor data set and using one model that had controls to compare data and one without. Again, this is the common back and forth discourse seen troubling the issue. The debate of disproportionality rages on.

Synthesis of the Literature

While there is a wide body of literature examining disproportionality, only five studies were chosen for this synthesis. There were common threads found in all the articles. Several believed that disproportionality has varying factors affecting it. These range from socioeconomic status (SES), academic achievement, and even rate of suspensions to name a few (Skiba et al, 2005, Sullivan and Bal 2013). All the studies feel future research is needed to truly understand the issue. There were several mentions of longitudinal studies at the national or local level across a student’s schooling life (Skiba et al, 2016; Cruz & Rodl, 2018; Skiba et al, 2005; Sullivan & Bal, 2013; Morgan et al., 2015). Others had brief mentions of the possibility of qualitative studies being used to examine the issue (Morgan et al., 2015; Curz & Rodl, 2018). Most of the research understands and knows its limitations such as not being representative of every state and only examined students during a small period of their schooling life (Sullivan & Bal, 2013; Morgan et al, 2015; Skiba et al., 2005). Even though there is agreement on some aspects of disproportionality, there are several key areas in which the current body of research contradicts itself. Currently, the research feels that there should be consistent data sets and systems of analysis used (Cruz and Rodl, 2018). Following a set of agreed upon standards, might make it easier to parse the issue and prevent conflicting results across studies.

Agreements in the Literature

Both Sullivan and Bal (2013) and Skiba et al. (2005) found there are some areas in which minorities are overrepresented and others where they are not. They also talk about different factors that may cause this like poverty or race or both combined. Morgan et al. (2015) suggests poverty is the main issue. All the studies in this synthesis agree future, more detailed research needs to be done. There were several suggestions of longitudinal national studies because most were done at the state and local school district level (Skiba et al, 2016; Cruz & Rodl, 2018; Skiba et al, 2005; Sullivan & Bal, 2013; Morgan et al., 2015). Having a more uniform system of analysis and consistent data set was all so suggested (Cruz and Rodl, 2018). Studies should consider a qualitative approach (Morgan et al., 2015; Cruz & Rodl, 2018) And factor in an individual’s perception and perspective (Morgan et al., 2015; Cruz& Rodl, 2018) Skiba 2005 and Sullivan and Bal (2013) seem to agree school suspension rates can be a possible cause of disproportionality. There are also calls for more studies focused on other minorities and disabilities (Cruz & Rodl, 2018).

Disagreements in the Literature

Several of the studies agree overrepresentation is an issue but the cause varies, and different confounding variables can affect the results (Morgan et al. 2015; Cruz &Rodl, 2018; Skiba et al. 2005). It just is not a simple issue; many things can cause overrepresentation or underrepresentation. It is important to know there are several factors can increase or decease overrepresentation.

Cruz and Rodl (2018) conducted a literature synthesis across several studies over many years. They found not all minorities are equally represented in the data, neither are all disabilities. The studies also seem to vary by state and district. There is no simple way to parse the issue. It is possible views of disabilities have changed over time. There has been a focus on African American students and is suggesting poverty is the root cause (Morgan et al., 2015). It is very difficult to nail down the cause of disproportionality due to the varying results of the research. Perhaps a common methodology is needed to accurately analyze the data.

Different Data Sets. Several of the research examined used different data sets that could have affected the results. Morgan et al. (2015) used Early Childhood Longitudinal Study-Kindergarten Cohort while Sullivan and Bal (2013) only used data from one school district in Wisconsin. Skiba et al. (2005) used data from an entire school district in Indiana. It is also important to mention some studies were only conducted at the state level and others at the school district level (Skiba et al., 2005; Sullivan & Bal 2013). So not only were the data sets different, but the amount of data was as well. The research commonly stresses the data in these studies are

a small representation of the bigger picture. The data could be unique to the school, the district, or the state (Skiba et al., 2005; Sullivan & Bal, 2013).

Varying Analysis Systems. There appears to be no uniform way to analyze the data in disproportionality research. Skiba et al. (2005) said that the systems currently used even have flaws. It will be difficult to understand what causes disproportionality if there is lack on uniformity. Almost all the studies used different analysis systems to examine the data (Cruz & Rodl, 2018). This is likely the reason the results of the studies on disproportionality vary.

Disproportionality is a complex issue that suffers from lack of consistency and a prevalence of conflicting research results. While there are some areas in which researchers agree, there are several more in which they disagree.

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