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Racial differences in academic achievement among juvenile offenders
Learning and Individual Differences 36 (2014) 207–212
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Learning and Individual Differences journal homepage: www.elsevier.com/locate/lindif
Racial differences in academic achievement among juvenile offenders Andrew Tesoro ⁎, Kristin C. Thompson, Richard J. Morris University of Arizona, School Psychology Program, 1430 E. 2nd Street, PO Box 210069, Tucson, AZ 85721, United States
a r t i c l e
i n f o
Article history: Received 27 May 2013 Received in revised form 5 February 2014 Accepted 21 June 2014 Keywords: Juvenile delinquents Academic achievement Racial differences
a b s t r a c t Racial differences were examined in academic achievement among a large, diverse juvenile delinquent population in the Southwestern United States. Participant data were collected from the University of Arizona Juvenile Delinquency Project (UAJDP) database. Academic measures included school absences; grade point average; standardized reading, writing, and math achievement scores; and, special education placement. Results showed significant differences among racial groups on all measures of academic achievement. Whites had higher passage rates on standardized tests in math, reading, and writing, as well as higher GPA, compared to all racial minorities except for Asians. Native-American youth performed lower on most academic measures compared to other racial groups and had significantly more absences than any other racial group. Moreover, Whites had the highest rates of special education whereas Asians had the lowest. Implications of these findings are discussed in terms of future research and public policy issues. © 2014 Elsevier Inc. All rights reserved.
1. Introduction According to the 2010 United States (U.S.) Census, racial diversity continues to grow across the nation (U.S. Census Bureau, 2010). The Census projects that the non-Hispanic White population will peak in 2024 and then slowly decrease, whereas the population of Asian, Black, and Hispanic groups will increase in numbers up until 2060. In fact, the minority population in the U.S. is predicted to become the numerical majority by 2043 (U.S. Census Bureau, 2010). Consequently, the U.S. student population will continue to become more diverse, as well. Over the next decade, school enrollment numbers are expected to rise for Blacks, Hispanics, Asian/Pacific Islanders, Native American/ Alaska Natives, and students of two or more races, but fall for Whites (Hussar & Bailey, 2013). Hispanics, which make up the largest and fastest, growing minority group in the U.S., have already doubled in school enrollment numbers from 1990 to 2006 (Fry & Gonzales, 2008). Given the increase in racial diversity among American students, there is a growing concern regarding the academic achievement disparity between Whites and racial minorities. Racial disparity has existed in the U.S. for more than a century and has been a topic of concern in education since the U.S. Supreme Court's decision in Brown v. Board of Education (1954) in which it was decided that separate but equal
⁎ Corresponding author at: Department of Special Education, Rehabilitation, and School Psychology, University of Arizona, PO Box 210069, Tucson, AZ 85821, United States. Tel.: +1 510 499 3325. E-mail address: [email protected] (A. Tesoro).
http://dx.doi.org/10.1016/j.lindif.2014.06.004 1041-6080/© 2014 Elsevier Inc. All rights reserved.
education is unconstitutional. When the National Assessment of Education Progress (NAEP) first collected data on academic progress in 1970 for all U.S. students, it became evident that Black and Hispanic students were almost on average four years behind White students (Chubb & Loveless, 2002). Since then, educators and legislators have attempted to even the playing field for racial minorities through the passage of laws and policies (e.g., No Child Left Behind [NCLB]). However, the achievement gap between White students and most other minority students remains. For example, between 1971 and 2008, the achievement gap in reading and math between White and Black students remained quite large, with only slight narrowing beginning in 2004. The gap in reading and math between White and Hispanic students has also remained quite large, but has not narrowed since data were first collected in 1990 (Rampey, Dion, & Donahue, 2009). In addition, Native American students were found to lag behind their non-Native American peers, whereas Asian students were found to perform at achievement levels similar to White students (NAEP, 2011). Because White students appear to perform, in general, at a higher level academically, as well as on achievement tests, compared to Black, Hispanic and Native American students, this provides them with the opportunity to pursue higher education endeavors at a higher frequency which, in turn, often results in earning a higher income and experiencing less social adversity (Chubb & Loveless, 2002). Of equal importance to the achievement gap between Whites and racial minorities is the distinct issue of academic disparity occurring between juvenile offenders and non-offenders (Archwamety & Katsiyannis, 2000; Beebe & Mueller, 1993, Cottle, Lee, & Heilbrun, 2001; Foley, 2001; Katsiyannis, Ryan, Zhang, & Spann, 2008; Meltzer, Levine, Karniski, Palfrey, & Clarke, 1984, Zamora, 2005). For example,
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in a review of the academic characteristics of juvenile delinquents, Foley (2001) reported that these youth were one year to several years below expected grade levels and had high rates of academic failure and grade retention. Some studies have also found that the majority of juvenile delinquents held in detention centers read at an elementary school level despite an average age of approximately 15 years (Beebe & Mueller, 1993; Meltzer et al., 1984). In one study, Zamora (2005) used the Kaufman Test of Educational Achievement (KTEA) to determine the academic level of 327 delinquent males ages 10 to 17 years. The results indicated that nearly half of the juveniles both read and performed math at an elementary school-age level despite the fact that 86.6% of the juveniles were placed between 7th and 10th grade. Further, Katsiyannis and Archwamety (1997) reported that juvenile recidivists (repeat offenders) performed poorer in reading, math, and writing, compared to non-recidivists, suggesting an area of further study regarding a possible link between the low academic achievement and the recommitting of juvenile offenses. Despite the large body of evidence indicating that racial minority status and juvenile delinquency are both risk factors in predicting low academic achievement, few studies have specifically explored the racial differences in academic achievement among juvenile delinquents. To our knowledge, Baltodano, Harris, and Rutherford's (2005) study is the only investigation that attempts to examine these differences. However, their study lacked an adequate number of individuals within some of their racial categories, making data analysis and interpretation problematic across all racial groups. Also, like many other delinquency studies, their sample only included males. Furthermore, most juvenile delinquency studies on academic achievement have only included measures of math, reading, and writing, and have excluded other academic variables such as school attendance data, grade point average, and special education placement. In light of these limitations, the purpose of the present study was to provide a more comprehensive analysis of racial differences in academic achievement among juvenile delinquents, with particular interest in comparing academic outcomes between Whites and racial minorities. Our study advanced extant research in several ways. First, in contrast to many previous studies, our sample included a large, diverse sample of juvenile delinquents. This included all racial categories, which were well represented, and both males and females. Additionally, unique to our study is the inclusion of youth who were arrested, but not detained. Most studies have focused only on incarcerated youth, thus limiting their interpretation of achievement data to detained youth. Second, we included a large number of academic variables that were excluded in many previous delinquency studies (e.g. school attendance data, grade point average, and special education status). To investigate the relationship between race and academic achievement among juvenile delinquents, the following research questions and hypotheses were developed for this study: 1. What is the current level of academic achievement among juvenile delinquents across all racial groups? Given the wealth of delinquency research suggesting that juvenile delinquents are, on average, low academic performers, we hypothesize that youth in our sample will also show low levels of academic achievement compared to their peers. 2. Are there significant racial group differences with regard to total school absences and GPA among the juvenile delinquent population? No directional hypotheses were formulated regarding school attendance and grade point average since these measures have not yet been systematically studied across racial grouping. 3. Does performance on reading, math, and writing differ among racial groups? Although very few studies have studied racial differences in academic performance among juvenile delinquents, research among the general population suggests that White students, on average, perform significantly better than racial minority students. Thus, we hypothesize that significant differences in standardized achievement
tests of reading, writing, and math will be present among Asian, Black, Hispanic, Native American, and White delinquents. Specifically, we expect White delinquents to outperform all other racial groups on all academic measures. 4. Do racial groups differ in their likelihood of being in special education? No directional hypotheses were formulated regarding special education status since it has not yet been systematically studied across racial grouping. 2. Method 2.1. Participants Participants in this study consisted of 8996 male and female youth who were enrolled within a large public school district and arrested at least once between August 2006 and May 2011. For those participants who had been arrested multiple times during this time period, the most current data were used. Sixty-four percent of the participants were male and 36% were female. In addition, 1.3% were Asian, 9.8% Black, 52.9% Hispanic, 5.8% Native American, and 29.3% White. As can be seen from Table 1, this racial percentage distribution is consistent with the local school district's percentage breakdown of youth by race. Participants ranging in age from 8 to 17 years and from grades 1 through 12 were represented. 2.2. Procedure This project was approved by the University of Arizona's institutional review board. The data are part of the University of Arizona Juvenile Delinquency Project (UAJDP) database which was established through a cooperative intergovernmental agency signed agreement between the medium-size cooperating school district, participating juvenile court center, and the University of Arizona. This database consists of offense history, educational, school and demographic data that are obtained yearly through an intergovernmental agency data-sharing agreement (see Thompson & Morris, in 2013, for a more detailed description of the database). 2.3. Variables Academic measures and school demographic data in this study included: 1. School absence, given that truancy is a common problem among all delinquents and will negatively impact their academic functioning. School absence was defined as the total days the participant missed school of the year they were arrested. If they were arrested over multiple years, the most current school year data was used. 2. Grade point average (GPA; only available for high school offenders). Grade point average was used to determine current levels of achievement, independent of standardized achievement tests. It was reported on a scale from 0.0 to 4.0. Table 1 Comparing participant demographics with 2011–2012 Tucson Unified School District (TUSD) data. Variable Race/ethnicity White Black Hispanic Native American Asian Gender Male Female
Sample (%)
TUSD (%)
29.5 9.9 53.4 5.9 1.3
24.2 5.6 61.2 3.8 2.6
64 36
51.5 48.5
Note. 2011–2012 TUSD enrollment data was collected from tusdstats.tusd1.org.
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3. Academic achievement scores from the Arizona Instrument to Measure Standards (AIMS) standardized achievement tests. Standardized achievement test scores were used for a more objective measure of each participant's reading, writing, and math achievement, given that GPA will also be affected by school attendance and effort. These tests are administered yearly in the areas of reading, writing, and math until high school, at which point the student takes the test until they receive passing scores (Arizona Department of Education, 2011). Because standardized test scores vary between academic year and grade, scores were converted to a 1–4 scale to allow for comparison among all ages and grades. This conversion is consistent with that used by the Arizona Department of Education (2011). Specifically, data were categorized into four groups, including Falls Far Below Standards, Approaches Standards, Meets Standards, and Exceeds Standards. A dichotomous grouping was also created: passed versus failed. Falls Far Below Standards and Approaches Standards were combined to define those who failed a given skill area (i.e., reading, writing, or math) and Meets Standards and Exceeds Standards were combined to describe those that passed. 4. Special education status. Because juvenile delinquents with educational disabilities are overrepresented in the juvenile justice system (e.g., while 12% of the general population was receiving special education services, 25.3% of our sample was receiving special education services), and minority students are also overrepresented in special education, special education status was used as a variable. A dichotomous variable was used to indicate whether the juvenile was receiving special education services at the time of the arrest. Of the 25.3% of the sample receiving special education services, 52.7% of them were receiving services for a learning disability, 29.7% for a speech–language impairment, and 24.2% for an emotional disability. 2.4. Data analyses We used SPSS Version 19 to conduct all data analyses. For hypothesis (1), we analyzed the overall level of academic achievement among juvenile delinquents in our sample by calculating means of school absences and GPA, and computing percentages of those in our sample that passed the reading, math, and writing sections on the AIMS, as well as of those that are currently in special education. For hypothesis (2), we analyzed the racial differences in total school absences and GPA by conducting a one-way multivariate analysis of variance (MANOVA). Additional post-hoc comparisons were conducted to compare mean differences on school absences and GPA between racial groups. For hypothesis (3), we compared the likelihood of obtaining a passing score on the reading, math, and writing sections of the AIMS across racial groups by performing a chi-square test of independence. For hypothesis (4), we analyzed the likelihood of receiving special education based on racial group membership by conducting a chisquare test of independence. 3. Results 3.1. Overall level of academic achievement An analysis of the entire dataset revealed that the juvenile offenders included in this study missed an average of 17 days of school. Additionally, the average GPA for delinquents in grades 9–12 was 1.53 (on a 4.0 scale). In regard to academic achievement, only 40% of delinquents had taken the yearly-standardized achievement test and had documented AIMS scores. Of those with standardized achievement scores, only 45.1% obtained scores that Meets Standards or Exceeds Standards in reading, 30.5% obtained scores that Meets Standards or Exceeds Standards in math, and 51.1% obtained scores that Meets Standards or Exceeds Standards in writing. Also, 25.3% of the participants were in special education.
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3.2. School absences and GPA A one-way MANOVA was conducted to investigate the racial differences in school absences and GPA. Significant differences were found among racial groups on the combined dependent variables (school absences and GPA), Wilks' Λ = .94, F(8, 10,564) = 44, p b .01. The multivariate η2 based on Wilks' Λ was weak, .03. Table 2 contains the means and standard deviations on the dependent variables for all racial groups. Analyses of variances (ANOVAs) on the dependent variables were conducted as follow-up tests to the MANOVA. Using a Bonferroni correction method, each ANOVA was tested at the .025 level. The ANOVAs conducted for both school absences and GPA were significant, F(4, 5283) = 9.18, p b .01, η2 = .01 and F(4, 5283) = 86.07, p b .01, η2 = .06, respectively. Post hoc analyses to the univariate ANOVAs for both school absences and GPA consisted of conducting pairwise comparisons to find how school absences and GPA differed among racial groups, particularly between Whites and racial minorities (see Table 3). Each pairwise comparison was tested at the .025 divided by 2 or .0125 level to control for type 1 error. For school absences, Native Americans significantly differed from all other racial groups; no other racial groups significantly differed from one another. Regarding GPA, Whites had significantly higher GPAs compared to Blacks, Hispanics, and Native Americans, but not Asians. Significant differences in GPA also exist among all racial minority groups with Asians yielding the highest GPA followed by Blacks, Hispanics, and Native Americans.
3.3. Reading, math, and writing Chi-squared tests of independence were performed to examine the relationship between racial group and passing the AIMS test in reading, math, and writing. In regard to reading, results found a significant relationship between racial group and passing standardized reading tests, χ2 (4, N = 3675) = 116.88, p b .001. Upon further examination using 2 × 2 chi-square analyses (comparing the frequency of passing AIMS between two racial groups) and p-value set at .05, Whites were more likely to pass the AIMS in reading (Meets Standards or Exceeds Standards; 58.9%) compared to Blacks (43.7%), Hispanics (39.4%), and Native Americans (35.1%). Asians performed similarly to Whites (59.3%). Asians were also more likely to pass the AIMS in reading compared to Blacks, Hispanics, and Native Americans. Also, Blacks and Hispanics were more likely to pass than Native Americans, but did not significantly differ in frequency from each other. The relationship between racial group and passing the AIMS in math was also significant, χ2 (4, N = 3740) = 126.99, p b .001. Further analysis on the distribution of race on AIMS math performance revealed a similar pattern to that of race on AIMS reading: Whites had higher rates of passing the AIMS in math (43.4%) compared to Blacks (25.5%), Hispanics (26.5%), and Native Americans (16.3%), but not Asians (46.3%). Among the racial minority groups, Asians were more likely to pass the AIMS in math than any other racial minority group. Further, Blacks and Hispanics were more likely to pass than Native Americans, but did not differ significantly from each other.
Table 2 Means and standard deviations of GPA among racial groups. Group
White Black Hispanic Native American Asian Note. N = 5288.
Absences
GPA
M
SD
M
SD
14.14 14.64 15.46 19.26 12.14
.345 .63 .27 .86 1.63
1.90 1.59 1.43 1.20 2.10
.02 .27 .02 .06 .11
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Table 3 Post hoc analysis of school absences and GPA among racial groups.
Absences White Black Hispanic Native American GPA White Black Hispanic Native American
White Black
Hispanic Native American Asian
– – – – – – – –
.024 1.00 – – b.001⁎ .004⁎ – –
1.00 – – – b.001⁎ – – –
b.001⁎ b.001⁎ b.001⁎ – b.001⁎ b.001⁎ .001⁎ –
1.00 1.00 .436 .001⁎ .70 b.001⁎ b.001⁎ b.001⁎
Note. N = 5288. ⁎ p b .0125.
Finally, the relationship between racial group and passing the AIMS writing test was significant, as well, χ2 (4, N = 3257) = 37.54, p b .001. Consistent with the findings thus far, Whites had higher percentages of passing the AIMS test in writing (59.4%) when compared to Blacks (49.5%), Hispanics (48%), and Native Americans (45.4%), but not Asians (64.3%). Comparing racial minority groups, Asians were more likely to pass the AIMS in writing compared to Hispanics and Native Americans. No other significant differences were found among racial minorities. Table 4 displays the AIMS passage rates among the different racial groups. 3.4. Special education A chi-squared test of independence was used to investigate differences in the expected versus observed frequencies across racial grouping in special education status. The results showed that significant differences exist, χ2 (4, N = 8911) = 38.84, p b .001. In examining special education status within racial group, Whites had the highest percentage of youth receiving special education services (29%), followed by Blacks (26.7%) Native Americans (24.9%), of Hispanics (23.3%), and Asians (13%). Among all special education recipients, Hispanics made up the largest percentage (49%) followed by Whites (33.9%), Blacks (10.4%), Native Americans (5.8%), and Asians (0.7%); however, it is important to note that Hispanics comprised of more than half of the juvenile population in our sample, thus contributing to the large proportion of Hispanics among special education recipients. 4. Discussion The purpose of this study was to provide a comprehensive analysis of the racial differences in academic achievement within a large, diverse juvenile offender population. The study found that overall academic achievement is low among diverse delinquent youth, with more than half of the juvenile delinquents in this study failing to meet state standards in reading, math, and writing. These findings are consistent with the literature (Foley, 2001; Katsiyannis et al., 2008; Meltzer et al., 1984). Given the large emphasis on poor reading skills among youth in the delinquency literature, it was interesting to find that juvenile delinquents in our study fared much worse on math than on reading,
Table 4 Passage rate for AIMS reading, writing, and math among racial groups in a sample of juvenile delinquents. Variable
White
Black
Hispanic
Native American
Asian
AIMS Reading Writing Math
58.9 59.4 43.4
43.7 49.5 25.5
39.4 48.0 26.5
35.1 45.4 16.3
61.2 64.3 46.3
Note. N = 3675 for reading. N = 3740 for writing. N = 3257 for math.
thus highlighting the importance of quality interventions in both reading and math. Of those with valid AIMS scores, only 31.5% were passing state standards in math , whereas 45.1% were passing state standards in reading. An explanation for this discrepancy is beyond the purview of this article, but further examination is warranted. Beyond investigating core academic subjects, the study also found that juveniles in our sample amassed several school absences, obtained low GPAs, and were overrepresented in special education when compared to national special education data (NCES, 2012). In our sample, juveniles missed an average of 17 days of school in the same year they were arrested, and the average GPA was 1.53 (on a 4.0 scale), which equates to a “D” average. Furthermore, 25.3% of our sample is in special education, compared to 13.1% of the general population (NCES, 2012). This finding is concerning given that having a disability is associated with worse outcomes for juvenile offenders. Compared to juvenile offenders without disabilities, juvenile offenders with disabilities have higher rates of recidivism, are detained for longer periods of time, and have shorter amounts of time between repeat offenses (Zhang, Barrett, Katsiyannis, & Yoon, 2011). The second area of investigation involved examining the racial differences in academic achievement, especially between Whites and racial minorities. Results from this inquiry revealed that the relationship between racial group and school absences and GPA was statistically significant; however, effect sizes were nominal and clinically insignificant. It is likely that the large sample size contributed to the statistical significance. However, statistically and clinically significant differences were observed in regard to differences in academic achievement between whites and minorities. When the distribution of standardized scores in reading, math, and writing performance across race was examined, differences were significant. Overall, White incarcerated youth met state standards in reading, math, and writing, at a higher frequency compared to Blacks, Hispanics, and Native Americans, but not Asians. Finally, racial differences in special education eligibility were statistically significant. Although Hispanics made up the largest percentage of youth receiving special education in our sample, they were also the most representative group overall (53.4% of total sample). When examining special education status within racial group, Whites had the highest percentage of special education recipients. This finding is inconsistent with Baltodano et al. (2005), which indicated that incarcerated black youth had the highest percentage of special education recipients. Although both studies were conducted in a similar geographical area, the main distinction is that our study included youth who were arrested, but not necessarily detained, which might explain the different findings. It is possible that black youth with disabilities are vastly overrepresented in juvenile corrections, but less so among the population of youth who are arrested but not detained. It would be worth examining the factors that contribute to such differences in future research. 4.1. Implications Given that delinquent youth as a whole perform worse academically than non-delinquent youth, it is concerning to see that achievement gaps still exist among delinquents of different races, particularly between Whites and minorities. Discrepancy in academic achievement can create different life trajectories for youth leaving detention. For example, youth with high academic achievement compared to low achievement are significantly more likely to return to school post release, and youth with above average attendance were significantly less likely to reoffend at 1 year-post release (Bloomberg, Bales, & Piquero, 2012), which suggests that academic achievement may play a protective role against recidivism. However, the same study found that of high academic achievement had a greater positive impact on post release behavior for Blacks than for Whites. In a similar vein, research has also shown that low academic achievement is associated with significantly higher rates of delinquency for Blacks compared to Whites (Voelkl, Welte, & Wieczorek, 1999). These findings suggest
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that formal education can have a profound influence on life outcomes of juvenile offenders, especially for Blacks and possibly for other racial minorities as well. Education plays an important role in instilling critical life skills, as well building academic proficiencies that make youth marketable for future employment. Research indicates that school absences and poor school performance can increase one's risk of recidivism, as well as significantly hamper one's potential for employment (Kasen, Cohen, & Brook, 1998x; Lockwood, Nally, Ho, & Knutson, 2012). Thus, the achievement gap may place racial minority delinquents further at risk of reoffending, and not just as youth, but as adults as well. In fact, racial minorities are overrepresented in the adult prison population, and have significantly lower rates of high school or GED completion compared to Whites (Harlow, 2003; Harrison & Beck, 2006). Because education can alter life outcomes for juvenile offenders, particularly for racial minorities, there is a desperate need for academic interventions. There is already evidence that academic interventions can reduce delinquent behavior (Maguin & Loeber, 1996). Specifically, interventions that target reading problems have been found to reduce youth incarceration (Christle & Yell, 2008). Programs like Corrective Reading Program (CRP), which is an intensive remedial reading program that utilizes direct instruction, has achieved positive gains in reading for low-achieving incarcerated youth over a short time period (Malmgren & Leone, 2000). Similarly, in using a systematic, intensive literacy program, Drakeford (2002) was able to increase reading fluency, reading placement, and attitude toward reading among Black juveniles in corrections. In the study, most participants expressed interest in returning to school, finding employment, reading independently, and obtaining general education development certificates (GEDs). For a brief review on empirically based literacy instruction, see Leone, Krezmien, Mason, and Meisel (2005). There has been less research on effective math instruction for juvenile delinquents, particularly with racial minorities. However, Maccini, Gagnon, Mulcah and Leon (2006) suggest using effective instructional strategies for students with ED and LD, a population highly overrepresented among incarcerated youth. Specifically, these authors suggest using the following empirically-validated approaches: (a) advance organizers, (b) direct instruction, (c) use of technology and real-world problem solving tasks, (d) use of varied student grouping, (e) presenting information in a graduated instructional sequence, and (f) strategy instruction. Advance organizers typically involve orienting the learner to the lesson through visual and verbal aides, connecting current lessons with past lessons, and reviewing objectives. Direct instruction encompasses reviewing previously learned skills; teacher modeling, guided, and independent practice; monitoring student performance; providing corrective feedback; and use of cumulative review. Technology-based instruction and real-world problem solving tasks provide a more interactive approach to learning. , with teachers encouraging the use of calculators and making math problems more relevant to the real-world. Use of varied student grouping involves often dividing class into one-on-one, small-group, cooperative (e.g. peer tutoring), or whole group instruction. Using graduated instruction sequencing helps students move from concept development to skill acquisition. Lastly, strategy instruction involves teaching strategies (e.g. planning) to students so they can become self-learners. All of these strategies can be used for instructing student with ED on any subject area. See Hodge, Riccomini, Buford, and Herbst (2006) for a review of more efficacious math interventions targeting youth with emotional and behavioral disorders. Furthermore, preventative efforts must take place in schools to ensure that racial minorities are not falling behind academically and becoming at risk for delinquency. Our research suggests that preventing academic failure in racial minorities may be pivotal in preventing future delinquency. Implementation of Response to Intervention (RTI) is one preventative method that schools can use to ensure that academic progress is continually monitored throughout the school year for every student, and that empirically-based academic interventions are provided
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to struggling learners at increasing levels of intensity to meet their level of need. RTI has been proven to be useful in addressing the disproportionality of racial inequity in special education by allowing for more accurate identification and effectively reducing learning problems in Black youth (VanDerHeyden & Witt, 2005). Though research on RTI is still somewhat limited due to its recent emergence, it appears promising in addressing issues related to racial disproportionality in academic achievement (Hosp & Madyun, 2007), which may in turn prevent racial minority youth from entering the school-to-prison pipeline. 4.2. Limitations and future directions Our study did present with several limitations. First, the strongest limitation to the present study was the abundance of missing data. As indicated previously, standardized achievement scores were available for only 40% of the sample. Given that the students are required to take standardized achievement tests even if they are incarcerated, it is reasonable to assume that those with missing scores are not attending school. Consequently, they may be a more underachieving group academically. Second, the study did not examine possible mediating and moderating variables. It is possible, for example, that socioeconomic status plays a more important role on education than racial group; this investigation is worthy of future research. Third, data for GPA were only collected for high school students and cannot be generalized for juveniles in primary education. In fact, it might be worth investigating if age plays a role on the relationship between race and education. Fourth, although this study investigates racial differences in academic achievement among delinquent youth, it does not examine whether these academic differences are significantly different from what exists in the general population. Fifth, the current sample was representative of the school district in Arizona, where there is a higher percentage of Hispanic youth than is generally found in the nationwide delinquent population. Thus, the generalizability of this study is limited. 4.3. Conclusion Despite the study's limitations, the findings reported provide evidence that significant academic differences do exist among racial groups in the juvenile detention population, particularly between Whites and racial minorities. Considering the increased risk of delinquency and recidivism among low academic achievers, this study highlights the importance of academic intervention for juvenile delinquents as a way to prevent future offenses. The racial differences observed in academic achievement among delinquent youth suggest that intensive academic intervention is necessary, especially for Blacks, Hispanics, and Native Americans. High quality education that serves their unique needs may be the key to shifting their life trajectory in a positive direction. Acknowledgments The preparation of this article was supported by the University of Arizona's Jacqueline Anne Morris Memorial Foundation's Children's Policy and Research Project. References Archwamety, T., & Katsiyannis, A. (2000). Academic remediation, parole violations, and recidivism rates among delinquent youths. Remedial and Special Education, 21, 161–170, http://dx.doi.org/10.1177/074193250002100306. Arizona Department of Education (2011). Guide to test interpretation: AIMS and Stanford 10. Retrieved from. http://www.azed.gov/wp-content/uploads/PDF/AIMS_GTI_s11_ Web.pdf Baltodano, H. M., Harris, P. J., & Rutherford, R. B. (2005). Academic achievement in juvenile corrections: Examining the impact of age, ethnicity, and disability. Education & Treatment of Children, 28(4), 361–379 (Retrieved from http://ehis.ebscohost.com. ezproxy2.library.arizona.edu). Beebe, M. C., & Mueller, F. (1993). Categorical offenses of juvenile delinquents and the relationship to achievement. Journal of Correctional Education, 44, 193–198.
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Learning and Individual Differences journal homepage: www.elsevier.com/locate/lindif
Racial differences in academic achievement among juvenile offenders Andrew Tesoro ⁎, Kristin C. Thompson, Richard J. Morris University of Arizona, School Psychology Program, 1430 E. 2nd Street, PO Box 210069, Tucson, AZ 85721, United States
a r t i c l e
i n f o
Article history: Received 27 May 2013 Received in revised form 5 February 2014 Accepted 21 June 2014 Keywords: Juvenile delinquents Academic achievement Racial differences
a b s t r a c t Racial differences were examined in academic achievement among a large, diverse juvenile delinquent population in the Southwestern United States. Participant data were collected from the University of Arizona Juvenile Delinquency Project (UAJDP) database. Academic measures included school absences; grade point average; standardized reading, writing, and math achievement scores; and, special education placement. Results showed significant differences among racial groups on all measures of academic achievement. Whites had higher passage rates on standardized tests in math, reading, and writing, as well as higher GPA, compared to all racial minorities except for Asians. Native-American youth performed lower on most academic measures compared to other racial groups and had significantly more absences than any other racial group. Moreover, Whites had the highest rates of special education whereas Asians had the lowest. Implications of these findings are discussed in terms of future research and public policy issues. © 2014 Elsevier Inc. All rights reserved.
1. Introduction According to the 2010 United States (U.S.) Census, racial diversity continues to grow across the nation (U.S. Census Bureau, 2010). The Census projects that the non-Hispanic White population will peak in 2024 and then slowly decrease, whereas the population of Asian, Black, and Hispanic groups will increase in numbers up until 2060. In fact, the minority population in the U.S. is predicted to become the numerical majority by 2043 (U.S. Census Bureau, 2010). Consequently, the U.S. student population will continue to become more diverse, as well. Over the next decade, school enrollment numbers are expected to rise for Blacks, Hispanics, Asian/Pacific Islanders, Native American/ Alaska Natives, and students of two or more races, but fall for Whites (Hussar & Bailey, 2013). Hispanics, which make up the largest and fastest, growing minority group in the U.S., have already doubled in school enrollment numbers from 1990 to 2006 (Fry & Gonzales, 2008). Given the increase in racial diversity among American students, there is a growing concern regarding the academic achievement disparity between Whites and racial minorities. Racial disparity has existed in the U.S. for more than a century and has been a topic of concern in education since the U.S. Supreme Court's decision in Brown v. Board of Education (1954) in which it was decided that separate but equal
⁎ Corresponding author at: Department of Special Education, Rehabilitation, and School Psychology, University of Arizona, PO Box 210069, Tucson, AZ 85821, United States. Tel.: +1 510 499 3325. E-mail address: [email protected] (A. Tesoro).
http://dx.doi.org/10.1016/j.lindif.2014.06.004 1041-6080/© 2014 Elsevier Inc. All rights reserved.
education is unconstitutional. When the National Assessment of Education Progress (NAEP) first collected data on academic progress in 1970 for all U.S. students, it became evident that Black and Hispanic students were almost on average four years behind White students (Chubb & Loveless, 2002). Since then, educators and legislators have attempted to even the playing field for racial minorities through the passage of laws and policies (e.g., No Child Left Behind [NCLB]). However, the achievement gap between White students and most other minority students remains. For example, between 1971 and 2008, the achievement gap in reading and math between White and Black students remained quite large, with only slight narrowing beginning in 2004. The gap in reading and math between White and Hispanic students has also remained quite large, but has not narrowed since data were first collected in 1990 (Rampey, Dion, & Donahue, 2009). In addition, Native American students were found to lag behind their non-Native American peers, whereas Asian students were found to perform at achievement levels similar to White students (NAEP, 2011). Because White students appear to perform, in general, at a higher level academically, as well as on achievement tests, compared to Black, Hispanic and Native American students, this provides them with the opportunity to pursue higher education endeavors at a higher frequency which, in turn, often results in earning a higher income and experiencing less social adversity (Chubb & Loveless, 2002). Of equal importance to the achievement gap between Whites and racial minorities is the distinct issue of academic disparity occurring between juvenile offenders and non-offenders (Archwamety & Katsiyannis, 2000; Beebe & Mueller, 1993, Cottle, Lee, & Heilbrun, 2001; Foley, 2001; Katsiyannis, Ryan, Zhang, & Spann, 2008; Meltzer, Levine, Karniski, Palfrey, & Clarke, 1984, Zamora, 2005). For example,
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in a review of the academic characteristics of juvenile delinquents, Foley (2001) reported that these youth were one year to several years below expected grade levels and had high rates of academic failure and grade retention. Some studies have also found that the majority of juvenile delinquents held in detention centers read at an elementary school level despite an average age of approximately 15 years (Beebe & Mueller, 1993; Meltzer et al., 1984). In one study, Zamora (2005) used the Kaufman Test of Educational Achievement (KTEA) to determine the academic level of 327 delinquent males ages 10 to 17 years. The results indicated that nearly half of the juveniles both read and performed math at an elementary school-age level despite the fact that 86.6% of the juveniles were placed between 7th and 10th grade. Further, Katsiyannis and Archwamety (1997) reported that juvenile recidivists (repeat offenders) performed poorer in reading, math, and writing, compared to non-recidivists, suggesting an area of further study regarding a possible link between the low academic achievement and the recommitting of juvenile offenses. Despite the large body of evidence indicating that racial minority status and juvenile delinquency are both risk factors in predicting low academic achievement, few studies have specifically explored the racial differences in academic achievement among juvenile delinquents. To our knowledge, Baltodano, Harris, and Rutherford's (2005) study is the only investigation that attempts to examine these differences. However, their study lacked an adequate number of individuals within some of their racial categories, making data analysis and interpretation problematic across all racial groups. Also, like many other delinquency studies, their sample only included males. Furthermore, most juvenile delinquency studies on academic achievement have only included measures of math, reading, and writing, and have excluded other academic variables such as school attendance data, grade point average, and special education placement. In light of these limitations, the purpose of the present study was to provide a more comprehensive analysis of racial differences in academic achievement among juvenile delinquents, with particular interest in comparing academic outcomes between Whites and racial minorities. Our study advanced extant research in several ways. First, in contrast to many previous studies, our sample included a large, diverse sample of juvenile delinquents. This included all racial categories, which were well represented, and both males and females. Additionally, unique to our study is the inclusion of youth who were arrested, but not detained. Most studies have focused only on incarcerated youth, thus limiting their interpretation of achievement data to detained youth. Second, we included a large number of academic variables that were excluded in many previous delinquency studies (e.g. school attendance data, grade point average, and special education status). To investigate the relationship between race and academic achievement among juvenile delinquents, the following research questions and hypotheses were developed for this study: 1. What is the current level of academic achievement among juvenile delinquents across all racial groups? Given the wealth of delinquency research suggesting that juvenile delinquents are, on average, low academic performers, we hypothesize that youth in our sample will also show low levels of academic achievement compared to their peers. 2. Are there significant racial group differences with regard to total school absences and GPA among the juvenile delinquent population? No directional hypotheses were formulated regarding school attendance and grade point average since these measures have not yet been systematically studied across racial grouping. 3. Does performance on reading, math, and writing differ among racial groups? Although very few studies have studied racial differences in academic performance among juvenile delinquents, research among the general population suggests that White students, on average, perform significantly better than racial minority students. Thus, we hypothesize that significant differences in standardized achievement
tests of reading, writing, and math will be present among Asian, Black, Hispanic, Native American, and White delinquents. Specifically, we expect White delinquents to outperform all other racial groups on all academic measures. 4. Do racial groups differ in their likelihood of being in special education? No directional hypotheses were formulated regarding special education status since it has not yet been systematically studied across racial grouping. 2. Method 2.1. Participants Participants in this study consisted of 8996 male and female youth who were enrolled within a large public school district and arrested at least once between August 2006 and May 2011. For those participants who had been arrested multiple times during this time period, the most current data were used. Sixty-four percent of the participants were male and 36% were female. In addition, 1.3% were Asian, 9.8% Black, 52.9% Hispanic, 5.8% Native American, and 29.3% White. As can be seen from Table 1, this racial percentage distribution is consistent with the local school district's percentage breakdown of youth by race. Participants ranging in age from 8 to 17 years and from grades 1 through 12 were represented. 2.2. Procedure This project was approved by the University of Arizona's institutional review board. The data are part of the University of Arizona Juvenile Delinquency Project (UAJDP) database which was established through a cooperative intergovernmental agency signed agreement between the medium-size cooperating school district, participating juvenile court center, and the University of Arizona. This database consists of offense history, educational, school and demographic data that are obtained yearly through an intergovernmental agency data-sharing agreement (see Thompson & Morris, in 2013, for a more detailed description of the database). 2.3. Variables Academic measures and school demographic data in this study included: 1. School absence, given that truancy is a common problem among all delinquents and will negatively impact their academic functioning. School absence was defined as the total days the participant missed school of the year they were arrested. If they were arrested over multiple years, the most current school year data was used. 2. Grade point average (GPA; only available for high school offenders). Grade point average was used to determine current levels of achievement, independent of standardized achievement tests. It was reported on a scale from 0.0 to 4.0. Table 1 Comparing participant demographics with 2011–2012 Tucson Unified School District (TUSD) data. Variable Race/ethnicity White Black Hispanic Native American Asian Gender Male Female
Sample (%)
TUSD (%)
29.5 9.9 53.4 5.9 1.3
24.2 5.6 61.2 3.8 2.6
64 36
51.5 48.5
Note. 2011–2012 TUSD enrollment data was collected from tusdstats.tusd1.org.
A. Tesoro et al. / Learning and Individual Differences 36 (2014) 207–212
3. Academic achievement scores from the Arizona Instrument to Measure Standards (AIMS) standardized achievement tests. Standardized achievement test scores were used for a more objective measure of each participant's reading, writing, and math achievement, given that GPA will also be affected by school attendance and effort. These tests are administered yearly in the areas of reading, writing, and math until high school, at which point the student takes the test until they receive passing scores (Arizona Department of Education, 2011). Because standardized test scores vary between academic year and grade, scores were converted to a 1–4 scale to allow for comparison among all ages and grades. This conversion is consistent with that used by the Arizona Department of Education (2011). Specifically, data were categorized into four groups, including Falls Far Below Standards, Approaches Standards, Meets Standards, and Exceeds Standards. A dichotomous grouping was also created: passed versus failed. Falls Far Below Standards and Approaches Standards were combined to define those who failed a given skill area (i.e., reading, writing, or math) and Meets Standards and Exceeds Standards were combined to describe those that passed. 4. Special education status. Because juvenile delinquents with educational disabilities are overrepresented in the juvenile justice system (e.g., while 12% of the general population was receiving special education services, 25.3% of our sample was receiving special education services), and minority students are also overrepresented in special education, special education status was used as a variable. A dichotomous variable was used to indicate whether the juvenile was receiving special education services at the time of the arrest. Of the 25.3% of the sample receiving special education services, 52.7% of them were receiving services for a learning disability, 29.7% for a speech–language impairment, and 24.2% for an emotional disability. 2.4. Data analyses We used SPSS Version 19 to conduct all data analyses. For hypothesis (1), we analyzed the overall level of academic achievement among juvenile delinquents in our sample by calculating means of school absences and GPA, and computing percentages of those in our sample that passed the reading, math, and writing sections on the AIMS, as well as of those that are currently in special education. For hypothesis (2), we analyzed the racial differences in total school absences and GPA by conducting a one-way multivariate analysis of variance (MANOVA). Additional post-hoc comparisons were conducted to compare mean differences on school absences and GPA between racial groups. For hypothesis (3), we compared the likelihood of obtaining a passing score on the reading, math, and writing sections of the AIMS across racial groups by performing a chi-square test of independence. For hypothesis (4), we analyzed the likelihood of receiving special education based on racial group membership by conducting a chisquare test of independence. 3. Results 3.1. Overall level of academic achievement An analysis of the entire dataset revealed that the juvenile offenders included in this study missed an average of 17 days of school. Additionally, the average GPA for delinquents in grades 9–12 was 1.53 (on a 4.0 scale). In regard to academic achievement, only 40% of delinquents had taken the yearly-standardized achievement test and had documented AIMS scores. Of those with standardized achievement scores, only 45.1% obtained scores that Meets Standards or Exceeds Standards in reading, 30.5% obtained scores that Meets Standards or Exceeds Standards in math, and 51.1% obtained scores that Meets Standards or Exceeds Standards in writing. Also, 25.3% of the participants were in special education.
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3.2. School absences and GPA A one-way MANOVA was conducted to investigate the racial differences in school absences and GPA. Significant differences were found among racial groups on the combined dependent variables (school absences and GPA), Wilks' Λ = .94, F(8, 10,564) = 44, p b .01. The multivariate η2 based on Wilks' Λ was weak, .03. Table 2 contains the means and standard deviations on the dependent variables for all racial groups. Analyses of variances (ANOVAs) on the dependent variables were conducted as follow-up tests to the MANOVA. Using a Bonferroni correction method, each ANOVA was tested at the .025 level. The ANOVAs conducted for both school absences and GPA were significant, F(4, 5283) = 9.18, p b .01, η2 = .01 and F(4, 5283) = 86.07, p b .01, η2 = .06, respectively. Post hoc analyses to the univariate ANOVAs for both school absences and GPA consisted of conducting pairwise comparisons to find how school absences and GPA differed among racial groups, particularly between Whites and racial minorities (see Table 3). Each pairwise comparison was tested at the .025 divided by 2 or .0125 level to control for type 1 error. For school absences, Native Americans significantly differed from all other racial groups; no other racial groups significantly differed from one another. Regarding GPA, Whites had significantly higher GPAs compared to Blacks, Hispanics, and Native Americans, but not Asians. Significant differences in GPA also exist among all racial minority groups with Asians yielding the highest GPA followed by Blacks, Hispanics, and Native Americans.
3.3. Reading, math, and writing Chi-squared tests of independence were performed to examine the relationship between racial group and passing the AIMS test in reading, math, and writing. In regard to reading, results found a significant relationship between racial group and passing standardized reading tests, χ2 (4, N = 3675) = 116.88, p b .001. Upon further examination using 2 × 2 chi-square analyses (comparing the frequency of passing AIMS between two racial groups) and p-value set at .05, Whites were more likely to pass the AIMS in reading (Meets Standards or Exceeds Standards; 58.9%) compared to Blacks (43.7%), Hispanics (39.4%), and Native Americans (35.1%). Asians performed similarly to Whites (59.3%). Asians were also more likely to pass the AIMS in reading compared to Blacks, Hispanics, and Native Americans. Also, Blacks and Hispanics were more likely to pass than Native Americans, but did not significantly differ in frequency from each other. The relationship between racial group and passing the AIMS in math was also significant, χ2 (4, N = 3740) = 126.99, p b .001. Further analysis on the distribution of race on AIMS math performance revealed a similar pattern to that of race on AIMS reading: Whites had higher rates of passing the AIMS in math (43.4%) compared to Blacks (25.5%), Hispanics (26.5%), and Native Americans (16.3%), but not Asians (46.3%). Among the racial minority groups, Asians were more likely to pass the AIMS in math than any other racial minority group. Further, Blacks and Hispanics were more likely to pass than Native Americans, but did not differ significantly from each other.
Table 2 Means and standard deviations of GPA among racial groups. Group
White Black Hispanic Native American Asian Note. N = 5288.
Absences
GPA
M
SD
M
SD
14.14 14.64 15.46 19.26 12.14
.345 .63 .27 .86 1.63
1.90 1.59 1.43 1.20 2.10
.02 .27 .02 .06 .11
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Table 3 Post hoc analysis of school absences and GPA among racial groups.
Absences White Black Hispanic Native American GPA White Black Hispanic Native American
White Black
Hispanic Native American Asian
– – – – – – – –
.024 1.00 – – b.001⁎ .004⁎ – –
1.00 – – – b.001⁎ – – –
b.001⁎ b.001⁎ b.001⁎ – b.001⁎ b.001⁎ .001⁎ –
1.00 1.00 .436 .001⁎ .70 b.001⁎ b.001⁎ b.001⁎
Note. N = 5288. ⁎ p b .0125.
Finally, the relationship between racial group and passing the AIMS writing test was significant, as well, χ2 (4, N = 3257) = 37.54, p b .001. Consistent with the findings thus far, Whites had higher percentages of passing the AIMS test in writing (59.4%) when compared to Blacks (49.5%), Hispanics (48%), and Native Americans (45.4%), but not Asians (64.3%). Comparing racial minority groups, Asians were more likely to pass the AIMS in writing compared to Hispanics and Native Americans. No other significant differences were found among racial minorities. Table 4 displays the AIMS passage rates among the different racial groups. 3.4. Special education A chi-squared test of independence was used to investigate differences in the expected versus observed frequencies across racial grouping in special education status. The results showed that significant differences exist, χ2 (4, N = 8911) = 38.84, p b .001. In examining special education status within racial group, Whites had the highest percentage of youth receiving special education services (29%), followed by Blacks (26.7%) Native Americans (24.9%), of Hispanics (23.3%), and Asians (13%). Among all special education recipients, Hispanics made up the largest percentage (49%) followed by Whites (33.9%), Blacks (10.4%), Native Americans (5.8%), and Asians (0.7%); however, it is important to note that Hispanics comprised of more than half of the juvenile population in our sample, thus contributing to the large proportion of Hispanics among special education recipients. 4. Discussion The purpose of this study was to provide a comprehensive analysis of the racial differences in academic achievement within a large, diverse juvenile offender population. The study found that overall academic achievement is low among diverse delinquent youth, with more than half of the juvenile delinquents in this study failing to meet state standards in reading, math, and writing. These findings are consistent with the literature (Foley, 2001; Katsiyannis et al., 2008; Meltzer et al., 1984). Given the large emphasis on poor reading skills among youth in the delinquency literature, it was interesting to find that juvenile delinquents in our study fared much worse on math than on reading,
Table 4 Passage rate for AIMS reading, writing, and math among racial groups in a sample of juvenile delinquents. Variable
White
Black
Hispanic
Native American
Asian
AIMS Reading Writing Math
58.9 59.4 43.4
43.7 49.5 25.5
39.4 48.0 26.5
35.1 45.4 16.3
61.2 64.3 46.3
Note. N = 3675 for reading. N = 3740 for writing. N = 3257 for math.
thus highlighting the importance of quality interventions in both reading and math. Of those with valid AIMS scores, only 31.5% were passing state standards in math , whereas 45.1% were passing state standards in reading. An explanation for this discrepancy is beyond the purview of this article, but further examination is warranted. Beyond investigating core academic subjects, the study also found that juveniles in our sample amassed several school absences, obtained low GPAs, and were overrepresented in special education when compared to national special education data (NCES, 2012). In our sample, juveniles missed an average of 17 days of school in the same year they were arrested, and the average GPA was 1.53 (on a 4.0 scale), which equates to a “D” average. Furthermore, 25.3% of our sample is in special education, compared to 13.1% of the general population (NCES, 2012). This finding is concerning given that having a disability is associated with worse outcomes for juvenile offenders. Compared to juvenile offenders without disabilities, juvenile offenders with disabilities have higher rates of recidivism, are detained for longer periods of time, and have shorter amounts of time between repeat offenses (Zhang, Barrett, Katsiyannis, & Yoon, 2011). The second area of investigation involved examining the racial differences in academic achievement, especially between Whites and racial minorities. Results from this inquiry revealed that the relationship between racial group and school absences and GPA was statistically significant; however, effect sizes were nominal and clinically insignificant. It is likely that the large sample size contributed to the statistical significance. However, statistically and clinically significant differences were observed in regard to differences in academic achievement between whites and minorities. When the distribution of standardized scores in reading, math, and writing performance across race was examined, differences were significant. Overall, White incarcerated youth met state standards in reading, math, and writing, at a higher frequency compared to Blacks, Hispanics, and Native Americans, but not Asians. Finally, racial differences in special education eligibility were statistically significant. Although Hispanics made up the largest percentage of youth receiving special education in our sample, they were also the most representative group overall (53.4% of total sample). When examining special education status within racial group, Whites had the highest percentage of special education recipients. This finding is inconsistent with Baltodano et al. (2005), which indicated that incarcerated black youth had the highest percentage of special education recipients. Although both studies were conducted in a similar geographical area, the main distinction is that our study included youth who were arrested, but not necessarily detained, which might explain the different findings. It is possible that black youth with disabilities are vastly overrepresented in juvenile corrections, but less so among the population of youth who are arrested but not detained. It would be worth examining the factors that contribute to such differences in future research. 4.1. Implications Given that delinquent youth as a whole perform worse academically than non-delinquent youth, it is concerning to see that achievement gaps still exist among delinquents of different races, particularly between Whites and minorities. Discrepancy in academic achievement can create different life trajectories for youth leaving detention. For example, youth with high academic achievement compared to low achievement are significantly more likely to return to school post release, and youth with above average attendance were significantly less likely to reoffend at 1 year-post release (Bloomberg, Bales, & Piquero, 2012), which suggests that academic achievement may play a protective role against recidivism. However, the same study found that of high academic achievement had a greater positive impact on post release behavior for Blacks than for Whites. In a similar vein, research has also shown that low academic achievement is associated with significantly higher rates of delinquency for Blacks compared to Whites (Voelkl, Welte, & Wieczorek, 1999). These findings suggest
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that formal education can have a profound influence on life outcomes of juvenile offenders, especially for Blacks and possibly for other racial minorities as well. Education plays an important role in instilling critical life skills, as well building academic proficiencies that make youth marketable for future employment. Research indicates that school absences and poor school performance can increase one's risk of recidivism, as well as significantly hamper one's potential for employment (Kasen, Cohen, & Brook, 1998x; Lockwood, Nally, Ho, & Knutson, 2012). Thus, the achievement gap may place racial minority delinquents further at risk of reoffending, and not just as youth, but as adults as well. In fact, racial minorities are overrepresented in the adult prison population, and have significantly lower rates of high school or GED completion compared to Whites (Harlow, 2003; Harrison & Beck, 2006). Because education can alter life outcomes for juvenile offenders, particularly for racial minorities, there is a desperate need for academic interventions. There is already evidence that academic interventions can reduce delinquent behavior (Maguin & Loeber, 1996). Specifically, interventions that target reading problems have been found to reduce youth incarceration (Christle & Yell, 2008). Programs like Corrective Reading Program (CRP), which is an intensive remedial reading program that utilizes direct instruction, has achieved positive gains in reading for low-achieving incarcerated youth over a short time period (Malmgren & Leone, 2000). Similarly, in using a systematic, intensive literacy program, Drakeford (2002) was able to increase reading fluency, reading placement, and attitude toward reading among Black juveniles in corrections. In the study, most participants expressed interest in returning to school, finding employment, reading independently, and obtaining general education development certificates (GEDs). For a brief review on empirically based literacy instruction, see Leone, Krezmien, Mason, and Meisel (2005). There has been less research on effective math instruction for juvenile delinquents, particularly with racial minorities. However, Maccini, Gagnon, Mulcah and Leon (2006) suggest using effective instructional strategies for students with ED and LD, a population highly overrepresented among incarcerated youth. Specifically, these authors suggest using the following empirically-validated approaches: (a) advance organizers, (b) direct instruction, (c) use of technology and real-world problem solving tasks, (d) use of varied student grouping, (e) presenting information in a graduated instructional sequence, and (f) strategy instruction. Advance organizers typically involve orienting the learner to the lesson through visual and verbal aides, connecting current lessons with past lessons, and reviewing objectives. Direct instruction encompasses reviewing previously learned skills; teacher modeling, guided, and independent practice; monitoring student performance; providing corrective feedback; and use of cumulative review. Technology-based instruction and real-world problem solving tasks provide a more interactive approach to learning. , with teachers encouraging the use of calculators and making math problems more relevant to the real-world. Use of varied student grouping involves often dividing class into one-on-one, small-group, cooperative (e.g. peer tutoring), or whole group instruction. Using graduated instruction sequencing helps students move from concept development to skill acquisition. Lastly, strategy instruction involves teaching strategies (e.g. planning) to students so they can become self-learners. All of these strategies can be used for instructing student with ED on any subject area. See Hodge, Riccomini, Buford, and Herbst (2006) for a review of more efficacious math interventions targeting youth with emotional and behavioral disorders. Furthermore, preventative efforts must take place in schools to ensure that racial minorities are not falling behind academically and becoming at risk for delinquency. Our research suggests that preventing academic failure in racial minorities may be pivotal in preventing future delinquency. Implementation of Response to Intervention (RTI) is one preventative method that schools can use to ensure that academic progress is continually monitored throughout the school year for every student, and that empirically-based academic interventions are provided
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to struggling learners at increasing levels of intensity to meet their level of need. RTI has been proven to be useful in addressing the disproportionality of racial inequity in special education by allowing for more accurate identification and effectively reducing learning problems in Black youth (VanDerHeyden & Witt, 2005). Though research on RTI is still somewhat limited due to its recent emergence, it appears promising in addressing issues related to racial disproportionality in academic achievement (Hosp & Madyun, 2007), which may in turn prevent racial minority youth from entering the school-to-prison pipeline. 4.2. Limitations and future directions Our study did present with several limitations. First, the strongest limitation to the present study was the abundance of missing data. As indicated previously, standardized achievement scores were available for only 40% of the sample. Given that the students are required to take standardized achievement tests even if they are incarcerated, it is reasonable to assume that those with missing scores are not attending school. Consequently, they may be a more underachieving group academically. Second, the study did not examine possible mediating and moderating variables. It is possible, for example, that socioeconomic status plays a more important role on education than racial group; this investigation is worthy of future research. Third, data for GPA were only collected for high school students and cannot be generalized for juveniles in primary education. In fact, it might be worth investigating if age plays a role on the relationship between race and education. Fourth, although this study investigates racial differences in academic achievement among delinquent youth, it does not examine whether these academic differences are significantly different from what exists in the general population. Fifth, the current sample was representative of the school district in Arizona, where there is a higher percentage of Hispanic youth than is generally found in the nationwide delinquent population. Thus, the generalizability of this study is limited. 4.3. Conclusion Despite the study's limitations, the findings reported provide evidence that significant academic differences do exist among racial groups in the juvenile detention population, particularly between Whites and racial minorities. Considering the increased risk of delinquency and recidivism among low academic achievers, this study highlights the importance of academic intervention for juvenile delinquents as a way to prevent future offenses. The racial differences observed in academic achievement among delinquent youth suggest that intensive academic intervention is necessary, especially for Blacks, Hispanics, and Native Americans. High quality education that serves their unique needs may be the key to shifting their life trajectory in a positive direction. Acknowledgments The preparation of this article was supported by the University of Arizona's Jacqueline Anne Morris Memorial Foundation's Children's Policy and Research Project. References Archwamety, T., & Katsiyannis, A. (2000). Academic remediation, parole violations, and recidivism rates among delinquent youths. Remedial and Special Education, 21, 161–170, http://dx.doi.org/10.1177/074193250002100306. Arizona Department of Education (2011). Guide to test interpretation: AIMS and Stanford 10. Retrieved from. http://www.azed.gov/wp-content/uploads/PDF/AIMS_GTI_s11_ Web.pdf Baltodano, H. M., Harris, P. J., & Rutherford, R. B. (2005). Academic achievement in juvenile corrections: Examining the impact of age, ethnicity, and disability. Education & Treatment of Children, 28(4), 361–379 (Retrieved from http://ehis.ebscohost.com. ezproxy2.library.arizona.edu). Beebe, M. C., & Mueller, F. (1993). Categorical offenses of juvenile delinquents and the relationship to achievement. Journal of Correctional Education, 44, 193–198.
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