“At-Risk” Youth & Education

1. “At-Risk” Youth & Education Effects of Truancy, Importance of Graduation and Grades on School Effort

2. Introduction • Purpose

3. Literature Review • Importance of the topic • Defining “At-Risk” • The term “at-risk” has a wide variety of definitions • amount of risky behavior (e.g., early sexual behavior, truancy, tobacco/alcohol/drug use, running away from home/foster home, associating with delinquent peers • “at-risk” factors include race and ethnicity, poverty, dangerous neighborhoods, family dysfunction, low test scores, grade retention, low teacher and parent expectations, and early involvement in non-school risk behaviors Among the approximately 28 million adolescents in the United States, 10% or 2.8 million were at very high risk; 15% or 4.2 million were at high; 25% or 7 million were at moderate risk. -Dryfoos 1990

4. Review of the Literature • The problem of the “at-risk” youth and the difficulties in gaining access to fair and quality education is a product of a number of key factors: • the implementation of tracking • the process of exclusion • the growing achievement gap • and a lack of supportive, theoretically framed programs, among others • Society has consistently pushed the most “at-risk” students out of education systems where they have the greatest chance to flourish and make their way out of poverty. • Society has also formed programs to help these students who are pushed out of their schools: • Mentorship programs provide a role model to look up to • Alternative schools can foster the best relationship an “at-risk” youth has ever had with a teacher or administrator • Community service programs offer a sense of belonging and community responsibility to a young person who is “at-risk” • After-school programs provide a space for youth to become more involved in their school

5. Hypothesis

6. Methods • Dataset: Evaluation of the Children at Risk Program in Austin, Texas, Bridgeport, Connecticut, Memphis, Tennessee, Savannah, Georgia, and Seattle, Washington, 1993-1997 • Youth Interview Data • Sample Size: 867 youth • Funded by the United States Department of Justice, Columbia University, and United States Department of Health Procedure used: Logistic Regression • Independent Variables • Days of skipped class • 1) Never • 2) 1-2 days • 3) 3-5 days • 4) 6-9 days • 5) 10 or more days • Grades are important (Agree/Disagree) • Graduation is important (Agree/Disagree) Dependent Variable Try hard in school (Agree/Disagree)

7. This shows that the model significantly predicts group membership.

8. A perfect model would have a -2 Log Likelihood of 0. This shows that model was not a great fit. This will be addressed further in the discussion section.

9. This shows that the model is extremely accurate in classifying subjects.

10. Results • All effects are significant • Odds ratios are fairly large; therefore they indicate significant change in school effort

11. Truancy • Because Truancy was the only risk factor I was able to analyze I wanted to show the effect of truancy alone on school effort. It demonstrates even greater significance levels when separated. It also shows that school effort drastically decreases when students start skipping school.

12. Discussion • REJECT THE NULL FOR 3 HYPOTHESES • Importance of graduation and grades both have a significant effect on school effort and for every one-unit change importance of graduation and grades students are more likely to try hard in school • For truancy, the odds ratios decrease the more days students skip school. Therefore, an increase in truancy has a negative effect on school effort.

13. Limitations & Suggestions • The researchers did not include a variable differentiating sex or race so I could not test differences between male and female youth or different ethnicities • Many of the variables I wanted to use such as alcohol use, family dysfunction, and parent assistance and expectationswere not significant, so I settled for the variables used • Further research should test differences based on race and sex and the effects of other risky behavior on youth’s effort in school

14. References • Broussard, C. Anne, Susan Mosley-Howard, and Anita Roychoudhury. 2006. “Using Youth Advocates for Mentoring At-Risk Students in Urban Settings.” Children & Schools28(2):122-127. • De La Rosa, Dora A. 1998. “Why Alternative Education Works.” The High School Journal 81(4):268-272. • Dryfoos, Joy G. 1990. Adolescents at Risk: Prevalence and Prevention. Oxford, NY:Oxford University Press. • Inter-university Consortium for Political and Social Research (ICPSR). 2000. “Evaluation of the Children at Risk Program in Austin, Texas, Bridgeport, Connecticut, Memphis, Tennessee, Savannah, Georgia, and Seattle, Washington, 1993-1997 (ICPSR 2686).” Retrieved December 3, 2012. (http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/2686?q=car+program&permit%5B0%5D=AVAILABLE). • Noguera, Pedro A. 2003. “Schools, Prisons, and Social Implications of Punishment: Rethinking Disciplinary Practices.” Theory into Practice 42(4):341-350. • Prevatt, Frances and F. Donald Kelly. 2003. “Dropping out of school: A review of intervention programs.” Journal of School Psychology 41(5):377–395. • Resnick, Gary, and Martha Burt. 1996. “Youth At Risk: Definitions and Implications for Service Delivery”. American Journal of Orthopsychiatry 66(2):172-188. • Rios, Victor. 2012. “From 'At-Risk' to 'At-Promise': Supporting Teens to Overcome Adversity” Ted Talk. TEDxUCSB. Retrieved November 8, 2012. (http://www.youtube.com/watch?v=JZ5D_Je8tvo) • ———. 2011. Punished: Policing the Lives of Black and Latino Boys. NY: New York University Press. • Schmidt, Jennifer A., Lee Shumow, and Hayal Z. Kackar. 2012. “Associations of Participation in Service Activities with Academic, Behavioral, and Civic Outcomes of Adolescents at Varying Risk Levels.” Journal of Youth and Adolescence 41:932–947. • Thompson, Lynn A., and Lisa Kelly-Vance. 2001. “The Impact of Mentoring on Academic Achievement of At-risk Youth.” Children and Youth Services Review 23(3):227-242.