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Disproportionality of African Americans in Special Education The Influence of Aversive Racism on Referrals.

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Presentation on theme: "Disproportionality of African Americans in Special Education The Influence of Aversive Racism on Referrals."— Presentation transcript:

1 Disproportionality of African Americans in Special Education The Influence of Aversive Racism on Referrals

2 Origination of the Project  Worked in child welfare  Decided to get my PhD  Discovered Disproportionality and the theory of Aversive Racism  Created hypotheses based on what I found

3 Racial Bias/Racism  Two types of racial bias  Overt - Old-fashioned racism- pre-Civil Rights Act of 1964, blatant, observable in action  Covert- Subtle, indirect, can be either conscious or nonconscious  Explicit- Conscious cognitions, beliefs in traditional American values. Measured :self- report -CoBRAS  Implicit - Nonconscious cognitions influencing race-related decisions. Beliefs and attitudes that they are not prejudice and believe in equality for all.

4 Aversive Racism  Theory of Aversive Racism- low explicit racial bias and high implicit racial bias, belief in equality but discriminate in action. Pro-ingroup.

5 Hypotheses  Teachers with low explicit racial bias and low implicit racial bias will have fewer referrals of African American students to special education when compared to teachers with high explicit racial bias.  Teachers with low explicit racial bias and low implicit racial bias will have fewer referrals of African American students to special education when compared to teachers with low explicit racial bias and high implicit racial bias.  Teachers with high explicit racial bias will have a similar number of referrals of African American students to special education as teachers with low explicit racial bias and high implicit racial bias.  When controlling for teachers self-efficacy, the effect of implicit and explicit bias on referral was reduced.  When controlling for teachers years of teaching experience, the effect of implicit and explicit racial bias on referral was reduced.

6 Data Collection Procedures  Factorial Survey Design  Each person received 5 randomly selected vignettes with 7 randomly selected dimensions of 7 key factors embedded in each vignette  Each vignette had 5 questions answered on a 6 point Likert scale

7 Data Collection (cont.) Student’s race – as indicated by White or African American sounding names White / African American Student’s gender Female /Male Length of time exhibiting behaviors one month/half the school year/most of the school year Academic performance Below grade-level/on grade- level/above grade-level Peer relationships Generally avoiding interacting with [his/her] peers / refusing to interact or work with [his/her] peers/ getting aggressive towards [his/her] peers Relationship with the teacher Ignoring or not responding to instructions you give [him/her]/ getting upset with you when given directions /being defiant or disrespectful towards you Inappropriate behaviors under normal circumstances Being disruptive, loud or rowdy in class/ throwing temper tantrums/ destroying or ruining classroom property

8 Data Collection (cont.)  ID: 1 Aisha has been having a difficult time in your class for one month. The behaviors you have noticed include: generally avoiding interacting with her peers, ignoring or not responding to instructions you give her, and throwing temper tantrums. Academically, she has been performing at grade-level.  ID: 3 Darnell has been having a difficult time in your class for one month. The behaviors you have noticed include: refusing to interact with or work with his peers, getting upset with you when you give him directions, and throwing temper tantrums. Academically, he has been performing at grade-level.  ID: 4 Brad has been having a difficult time in your class for most of the school year. The behaviors you have noticed include: refusing to interact with or work with his peers, getting upset with you when you give him directions, and being disruptive, loud or rowdy in class. Academically, he has been performing below grade-level.

9 Data Collection (cont.)  The seven factors believed to influence the decision making of teachers are the independent variables  The five decisions to be made about special education referral are the dependent variables.  Because the factors are virtually orthogonal and each factor dimension was assigned randomly to the vignettes, each decision was considered independent (Taylor, 2006).  These independent decisions and the independence of the factors, then allow for the sample size to be the number of vignettes evaluated rather than the number of participants in the study ( Landsman & Hartley, 2007; Stokes & Schmidt, 2012; Taylor, 2006).

10 Dependent Variables  How likely would you be to consult a peer about this child’s behaviors in the classroom?  How likely would you be to set-up a meeting with the parent/guardian to discuss the child's problem in the classroom?  How likely would you be to try a new classroom management technique to address the child's behavior (i.e. change the rules and routines in the classroom)?  How likely would you be to refer to the child to the RTI team?  How likely would you be to refer the child for an assessment for special education?

11 Data Collection (cont.)  The participants evaluated the five vignettes  Then participants completed demographic questions followed by:  The CoBRAS (explicit measure of racial bias)  The TSES (Teacher Self-Efficacy Scale)(control variable)  The IAT (difference scores in response latencies measuring implicit racial bias)

12 Goals  To run 5 regression models on my data  Determine what the regressions say about my data  Examine my descriptive statistics for interesting trends in who completed the survey  Ensure I am interpreting the analyses correctly and I am not missing any important pieces to the analyses

13 Current Progress of the Process  I have collected all the data and have closed the survey  My response rate was 7% (22/307) but with 110 vignettes (5 vig/person), I have enough statistical power to run my regressions  I have cleaned up the data so all variables with no data were excluded and all measures have been scored (i.e. CoBRAS, TSES, IAT)  I would like to be done analyzing the data by April 15 th so that I can begin writing the last 2 chapters of my diss (good to have a goal )


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