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Disproportionality in School Discipline in the Road Map Region

Disproportionality in School Discipline in the Road Map Region. by Kristina Johnson, MPA Candidate 2012 Evans School of Public Affairs. A Well Documented Pattern. Percent. 1973. 2006. Source: Skiba & Losen , 2010. . The Road Map Project. 7 Districts: Auburn Federal Way Highline

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Disproportionality in School Discipline in the Road Map Region

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  1. Disproportionality in School Discipline in the Road Map Region by Kristina Johnson, MPA Candidate 2012 Evans School of Public Affairs

  2. A Well Documented Pattern Percent 1973 2006 Source: Skiba& Losen, 2010.

  3. The Road Map Project • 7 Districts: • Auburn • Federal Way • Highline • Kent • Renton • Seattle(South Seattle schools only) • Tukwila • Demographics • 60% students of color • 54% FRL eligible • 17% ELL students

  4. The Road Map Project Goal “…is to double the number of students … who are on track to graduate from college or earn a career credential by 2020.” “…committed to closing the unacceptable achievement gaps for low-income students and children of color, and increasing achievement for all students from cradle to career.”

  5. Outline • Context and explanations of exclusionary discipline • Findings from data analysis: Are subgroups of students disproportionally represented in exclusionary discipline in the Road Map Region? • Best practice interventions and policies that reduce disproportionality and exclusionary discipline rates

  6. Context and Explanations for Disproportionality

  7. Exclusionary Discipline • In school suspension • Out of school suspension • Expulsion

  8. Zero Tolerance Policies • Use of exclusionary discipline has risen due to zero tolerance policies • Concerning trend is use of zero tolerance and suspension for minor behaviors • However, evidence shows that punishment and suspension are the least effective strategies for changing student behavior (CCBD, 2002)

  9. Explanations for Disproportionality Low-income students • Cultural differences between socio-economic classes • Face risk factors that contribute to lower social-emotional and behavioral outcomes Race/ethnicity • Low-income status – evidence to the contrary • Higher rates of misbehavior – evidence to the contrary • Different communication styles and other cultural differences • Discrimination based on race Special education • Many students referred to special education for behavioral reasons Males • Higher rates of discipline are a proportionate response to higher rates of misbehavior

  10. Impacts of Exclusionary Discipline on Students • More likely that they will fall behind in school • Decreases engagement & connection • More likely to drop-out • More likely to end up in the juvenile justice system “School to prison pipeline” (APA, 2008; Christle, et al., 2005; Costenbader, et al., 1998)

  11. Data • District data - from districts and Office of the Superintendent of Public Instruction • School year 2009-10 • 7th – 9th grades, N = 26,406 • Student- level data, not incident level • Auburn not included in analysis • South Seattle only • No in-school suspension for South Seattle • Low-income data not available for Seattle and Kent • Highline missing 25% of race/ethnicity data • Analysis does not include the race category “two or more races” due to unclear inferences

  12. Methods • Literature Review • Descriptive statistics • Disproportionality: • Comparison of Rates or Risk of Suspension (t-tests)

  13. Preliminary Findings

  14. Out of School Suspensions Rates: All Road Map Districts by Gender, Low-income and Special Education Status Source: OSPI and districts, 2009-2010 Seattle data only includes portion of district within the Road Map region Free & reduced lunch data available for four districts only

  15. Source: OSPI and districts, 2009-2010 Seattle data only includes portion of district within the Road Map region Highline missing 25% of race/ethnicity data

  16. Discussion of Findings • Unlikely that disproportionality and high exclusionary discipline rates are explained solely byhigher rates of misbehavior for all subgroups • Exclusionary discipline has proven to be ineffective at reducing problem behaviors and increasing positive school climate

  17. Best Practice Program Models • Positive Behavior Intervention & Supports • Cultural Sensitivity & Awareness

  18. Positive Behavior Intervention & Supports (PBIS) • PBIS – proactive (vs. reactive) • Positive behavior expectations understood by all students, teachers and administrators • Data-driven decision making • Evidence-based behavior support practices • School-wide systems (Vincent et al., 2011) • Evidence • Reduces exclusionary discipline rates • Increases student achievement • Increases positive school climate Not a curriculum; a decision-making framework: • Peer Mediation, Classroom Management Training AND…

  19. Cultural Sensitivity & Awareness • Successful schools combine PBIS and cultural awareness training • Illinois successful schools “were committed to having tough conversations about race/ethnicity” • Professional development options that: Assist educators in understanding their own cultural framework and how this affects their perceptions of behavior

  20. Best Practice in District Policy Short-term next best steps for districts: • Improve data collection & analysis • Shorten the allowable length of suspensions • Support or require the adoption of best practice programs • Establish and state publicly the goal of reducing suspensions & disproportionality Encourage a new approach towards school disciplinethat is: • Proactive • Inclusive • Preventative

  21. Thank you! Kristina Johnson johnsk24@uw.edu Acknowledgements Kirsten “Avery” Avery, MPA Project Associate, Community Center for Education Results Andrew Sahalie, PhD Senior Data Manager, Community Center for Education Results Mary Jean Ryan, MPA Executive Director, Community Center for Education Results Mary Kay Gugerty, PhD, Advisor Associate Professor, UW Evans School of Public Affairs MariekaKlawitter, PhD Associate Professor, UW Evans School of Public Affairs Sheryl Johnson, PhD Lecturer, UW – Bothell School of Business

  22. Areas for Further Research • Why are discipline rates so much higher for the subgroups identified in this research? • What kinds of behaviors or offenses are subgroups referred for? • What behaviors typically result in suspension? • Are certain groups of students punished more severely for similar behaviors? • Do particular schools have significantly higher rates of suspension and disproportionality than other schools? • How has Highline learned from its several year experiment with PBIS? • What are student, parent and teacher perceptions of discipline policies in the Road Map region? • What is the feasibility of implementing recommended strategies in Road Map districts?

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