Differential Access to Books and School Librarians in Pennsylvania

While there is not voluminous evidence about the relationship between access to librarians and student achievement, the extant research does suggest a positive relationship such that students that have access to a school library staffed by a qualified librarian tend to have greater achievement as well as growth in achievement, even after controlling for other factors (Krashen, Lee, & McQuillan, 2012; Lance, & Hofschire, 2012; Lonsdale, 2003; Subramaniam, Ahn, Waugh, Taylor, Druin, Fleischmann, & Walsh, 2015). Moreover, this finding is strongest for students living in poverty since they tend to have less access to books at home and increasingly have less access to books through public libraries (Krashen, 2010; Park & Yau, 2014; Pribesh, Gavigan, & Dickinson, 2011). Further, Constantino (2005) notes that many students in affluent communities have access to more books than students living in poverty have access to through all sources in aggregate. Finally, access to libraries and librarians has also been found to be positively associated with children engaging with literature, developing hobbies, and developing social skills (Jones, 2009).

In the study attached below, I examine access to books at home and access to school librarians for Black, Hispanic, and White students in Pennsylvania.

CEEPA White Paper 2017-3_Access to Librarians in Pennsylvania by Student Race

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Access to School Librarians, Nurses, and Counselors in the Commonwealth of Pennsylvania

Executive Summary

While teachers and school leaders clearly have the strongest school-based influence on student outcomes, researchers have also found that professional support personnel also can have an important influence on both cognitive and non-cognitive student outcomes. Moreover, school support personnel have a particularly critical influence on the outcomes for students living in poverty—nearly 800,000 students in Pennsylvania schools in 2015.

In this White Paper, I examine access to three types of professional support personnel—librarians, nurses, and counselors. To varying degrees, research has found that access to librarians, nurses, and counselors can positively impact various student cognitive and non-cognitive outcomes.

Overall Findings

            There are three major findings that are consistent across all three roles (librarians, nurses, and counselors). First, the results clearly document a disturbing pattern of inequity with respect to access to librarians, nurses, and counselors in which schools enrolling the students most in need of additional support are the least likely to offer the additional support. This pattern of inequity is driven by an antiquated and clearly inequitable system of school funding that remains in place despite recent changes by the Pennsylvania legislature. This inequitable pattern demonstrates that students most in need of access to professional support personnel such as librarians, nurses, and counselors. The failure of the Commonwealth to ensure that these students have access to the professional support staff that their wealthier and White peers have access to creates a two-tiered system of education of haves  and have-nots. The continuation of this system has negative ramifications for the Commonwealth in that fewer students than would otherwise be the case are well-prepared to enroll in and successfully complete post-secondary education.

Second, schools enrolling relatively few students are far less likely to provide their students access to professional support staff (librarians, nurses, and counselors). While this finding is driven in part by charter schools not employing professional support staff, the smallest public schools are still less likely to employ these professional support staff than larger schools. Research suggests that smaller schools—especially those located in smaller districts—simply cannot afford to employ such staff, particularly at a full-time level.

Third, despite having the economic means to do so, very few charter schools employ librarians, nurses, and counselors. Why this is the case is unclear. But lack of financial ability is certainly not a viable reason given that: (a) hundreds of millions of dollars sent to charter schools for special education instruction is not spent on special education students; and, (b) charter schools close to $1,000 more per student on administration than public school districts, even after removing the influence of district size and school location in the state. Because charter schools are located primarily in major urban centers, students in Pennsylvania cities increasingly must choose between public schools that do not employ these professional support staff and charter schools that do not employ these professional support staff. This is not real choice.

 

Librarians

Students in high-poverty schools, schools with large proportions of students of color, schools in low-wealth districts, and urban schools have less access to both part-time and full-time librarians.

Charter schools were much less likely to provide their students with access to any librarian or a full-time librarian. In fact, fewer than 15% of charter schools employed any type of librarian at any school. In comparison, at least 66% of public schools offered a librarian of any type across all three school levels.

Consistent with prior research, a far lower percentage of schools with the smallest student enrollments than schools with the greatest student enrollments employed a librarian of any type and especially a full-time librarian. For a full-time librarian, the differences were at least 50 percentage points across all three school levels

Finally, a much lower percentage of urban schools than schools in other locales employed any librarian and a full-time librarian. Sadly, less than 22% of urban schools across all three levels employed a full-time librarian—even though urban schools tend to have larger enrollments than other schools.

 

Nurses

The most consistent related to nurses is that a far lower percentage of charter schools employed any nurse or a full-time nurse, regardless of whether or not the nurse . In fact, 30% or fewer charter schools employed a full-time nurse. Startlingly, only 15% of elementary charter schools employed a full-time nurse compared 34% of public elementary schools.

The second most consistent finding is that smaller schools across all three school levels were less likely to employ any nurse or a full-time nurse. This is consistent with prior research from other states.

The third consistent finding was that a lower percentage of schools located in towns employed a full-time nurse. While partially a result of schools located in towns being of smaller size, rural schools are typically even smaller but are more likely than town schools to employ a full-time nurse. Thus, some other factor is influencing the lack of access to nurses provided by schools in Pennsylvania towns.

At the secondary school level, a lower percentage of schools with the highest concentrations of students living in poverty employed any nurse and a full-time nurse as compared to schools with the lowest concentrations of students in poverty. The differences were larger at the middle school level than the high school level.

 

Counselors

At the secondary school level, students in schools serving the highest concentrations of students living in poverty and students of color had far less access to either a part-time or a full-time counselor than schools with the lowest concentrations of students living in poverty and students of color. Moreover, students in secondary schools located in low-wealth districts had less access to either a part-time or a full-time counselor than their peers enrolled in schools located in high-wealth districts.

Students in charter schools were far less likely to have access to a either a part-time or a full-time counselor across all three school levels. Strikingly, fewer than 52% of charter schools at the elementary school or middle school levels employed either a part-time or a full-time counselor. At the high school level, less than 70% of schools employed either a part-time or a full-time counselor as compared to at least 90% of public schools. In fact, even when comparing schools with similar student enrollments, charter schools were less likely than public schools to employ either a part-time or a full-time counselor.

At the secondary level, a lower percentage of schools located in urban districts employed any counselor or a full-time counselor. The same was true for the employment of any counselor at the elementary school level, but the results were mixed with respect to the employment of a full-time counselor. Thus, the evidence shows a lower percentage of urban districts employed counselors as compared to schools in other locales.

Finally, consistent with prior research, school size (number of students enrolled) is strongly associated with the employment of a counselor and especially with employment of a full-time counselor. Specifically, smaller schools were less likely to employ any counselor or a full-time counselor. This was true across all three school levels.

The full report can be found at: CEEPA White Paper 2017-2_Access to Nurses, Librarians, and Counselors in Pennsylvania_FINAL

 

Problems and Prospects for Pennsylvania’s School Accountability System

School accountability systems have become a fixture of the US education landscape. While there is some evidence that school accountability efforts have had some positive effects on student achievement[i], evidence also suggests that accountability systems have created as many problems as solutions.[ii] Indeed, there is widespread agreement that accountability systems adopted under NCLB, as well as through programs such as Race to the Top and NCLB waivers, had significant flaws. In an effort to remedy these flaws, the new version of ESEA—entitled the Every Student Succeeds Act (ESSA)—provides much greater flexibility to states in developing their school accountability systems. Further, ESSA includes some mandates that push states to address some flaws of the former accountability systems. Most important of these mandates is that states must include some non-academic indicators in their systems.

Thus, state policymakers have the opportunity to create accountability systems that more accurately capture school effectiveness in terms of both student achievement and other important student outcomes not related to test scores. The opportunity to redesign accountability systems also provides state policymakers the opportunity to re-build some of the trust lost between educators and local, state, and federal policymakers over the past decades due to poorly constructed accountability systems and the use of accountability results in educator evaluation systems. Pennsylvania policymakers are already in the midst of developing a new SPP to be called Future Ready PA. This White Paper reviews the basis of state accountability systems, the purposes of such systems, the issues with each metric in the SPP, and the issues with proposed metrics in Future Ready PA. Finally, we propose a new accountability system to spur discussion about what metrics should be included in Future Ready PA and how those metrics should be measured.

The full White Paper is at:CEEPA White Paper-Problems and Prospects with the Pennsylvania School Performance Profile_FINAL

You may also email me for a copy at ejf20@psu.edu

[i] Braun, H. (2004). Reconsidering the impact of high-stakes testing. Education Policy Analysis Archives, 12(1), 1-43; Carnoy, M., & Loeb, S. (2002). Does external accountability affect student outcomes? A cross-state analysis. Educational Evaluation and Policy Analysis(24), 305-331.
  Chiang, H. (2009). How accountability pressure on failing schools affects student achievement. Journal of Public Economics, 93(9-10), 1045-1057.
  Dee, T., & Jacob, B. (2011). The Impact of No Child Left Behind on Student Achievement. Journal of Policy Analysis and Management, 30(3), 418-446.
  Figlio, D., & Rouse, C. (2006). Do accountability and voucher threats improve low-performing schools? Journal of Public Economics, 90(1-2), 239-255.
  Hanushek, E., & Raymond, M. (2005). Does school accountability lead to imprvoed student performance? Journal of Policy Analysis and Management(24), 297-327.
  Reback, R., Rockoff, J., & Schwartz, H. (2014). Under pressure: Job security, resource allocation, and productivity in schools under NCLB. American Economic Journal: Economic Policy, 6(3).
  Winters, M., Trivitt, J., & Greene, J. (2010). The impact of high-stakes testing on student proficiency in low-stakes subjects: Evidence from Florida’s elementary science exam. Economics of Education Review, 29(1), 138-146.
[ii] Davidson, E., Reback, R., Rockoff, J. E., & Schwartz, H. L. (2015). Fifty ways to leave a child behind: Idiosyncrasies and discrepancies in states’ implementation of NCLB. Educational Researcher, 44(6), 347–358; Polikoff, McEachin, Wrabel, & Duque, 2013.

The Irony of Charter CEO Claim about “ZIP code doesn’t doom your life like it does now in traditional districts”

In a recent Pittsburgh Post Gazette story [http://www.post-gazette.com/news/education/2016/12/01/New-study-links-Pa-charter-school-growth-loss-of-district-resources/stories/201612010064] that reviewed a new Economic Policy Institute paper on the fiscal impact of charter school expansion on city school districts [http://www.epi.org/publication/exploring-the-consequences-of-charter-school-expansion-in-u-s-cities/] by Bruce Baker at Rutgers University, the reporters quote Anthony Pirrello, CEO of Montessori Regional Charter School in Erie, as stating:

“ZIP code doesn’t doom your life like it does now in traditional districts.”

Before accepting this statement, let’s look at some actual facts about the performance of the Montessori Regional Charter School and elementary schools in the Erie School District.

First, let’s examine the characteristics of the schools in question. The Montessori Charter Schools enrolls a substantially different set of children than the Erie Public Schools. Specifically, the charter school enrolls a far greater percentage of White and Asian students and far lower percentages of economically disadvantaged, English Language Learner (ELL), and special education students than the Erie public schools. In short, it appears that the Montessori Charter School is skimming–either intentionally or unintentionally–more advantaged students from the Erie Public Schools.

table-1_sch-characteristics

Given that school performance of highly correlated with student characteristics–especially the percentage of economically disadvantaged students and the percentage of White/Asian students–one would expect that the Montessori Charter School would have higher levels of performance than the Erie Public Schools. And, in fact, the Montessori School does appear to academically outperform many of the Erie Public Schools as shown in the first three columns of Table 2 below.

table-2-sch-performance

However, when I use regression analysis to remove the influence of student characteristics (% economically disadvantaged students , % White/Asian students, % ELL students, % female students, % gifted students, and % special education students) and school size on the three student outcome measures (Overall School Performance Profile score, % scoring proficient or advanced on the PSSA reading test, and % scoring proficient or advanced on the PSSA mathematics test), we see a different story.

With respect to the adjusted SPP score and the adjusted PSSA scores in reading and mathematics, the Montessori Charter School performs below average relative to all schools in the state and would only be in the middle of the pack when compared to Erie Public Schools.

Finally, and most importantly, when we look at PVAAS student growth scores in reading and mathematics, the Montessori Charter School has growth that is slightly lower than expected in reading and growth that is substantially lower than expected in mathematics. In fact, the Montessori Charter School would have the LOWEST mathematics growth score in the entire Erie Public School District.

So, I am unclear as to how the Montessori Charter School is ensuring that living in a particular zip code doesn’t doom a student to low performance. The Montessori Charter School performs below other schools across the state (after removing the influence of student characteristics) and has lower student growth scores than schools across the state. At best, the Montessori Charter School is on par with the average Erie Public School. This is breaking the connection between zip code and student performance? It does not look like that to me.

How Equitable is Access to Advanced Coursework in Pennsylvania High Schools?

Executive Summary

Research has consistently found that high school students who successfully complete high-quality advanced coursework are much better prepared to be successful when enrolled in higher education (Adelman, 1999). Indeed, this finding holds true even after removing the influence of personal characteristics such as parental level of education and income. Yet, despite such findings, reports have consistently found that many states do not ensure that all students have equitable access to advanced courses.

This study uses data from the Pennsylvania School Performance Profile (SPP) to examine which Pennsylvania schools provide their students with access to at least one advanced course in English Language Arts, social studies, mathematics, science, and at least one advanced course in each of these four subject areas. While the SPP data provides information on Advanced Placement ® course, International Baccalaureate ® courses, and other courses designated as advanced by the Pennsylvania Department of Education (PDE) as being advanced courses, I chose to combine all of this information into one indicator of whether or not a school offered any advanced course in the subject area.

I examined access by a number of school characteristics, including: number of 11th and 12th grade students enrolled in the school, percentage of students participating in the federal free and reduced price meals program (FARM), percentage of students of color enrolled in the school (African American, Hispanic American Indian, and mixed race students), percentage of female students, percentage of special education students, percentage of gifted students, charter school status, magnet school status, geographic locale, and district instructional expenditures.

Findings

The most consistent finding in prior research and in this analysis is that smaller schools were less likely to offer advanced courses, particularly in mathematics and science. The impact of the number of 11th and 12th grade students was, by far, the school characteristic most strongly associated with offering an advanced course.

A lower percentage of 11th and 12th grade African American and Hispanic students were enrolled in schools that offer advanced courses. This result held true for each individual subject area as well as for offering at least one advanced course across all four subject areas. African American students, in particular, were less likely to be enrolled in schools offering advanced courses. For example, only 58% of all African American 11th and 12th grade students were enrolled in schools offering at least one advanced course in each of the four subject areas. In comparison, 87% of White students were enrolled in such schools.

A lower percentage of brick-and-mortar charter schools offered advanced courses as compared to traditional public schools. This was true for all five outcomes, even after adjusting the results for student enrollment. However, when adjusting the results for student enrollment and school characteristics, brick-and-mortar charter schools had lower odds of offering at least one advanced course in mathematics and science as well as lower odds of offering at least one advanced course in each of the four subject areas combined. Regardless of the statistical adjustments, the fact remained that students enrolled in brick-and-mortar charter schools generally had less access to advanced courses.

A lower percentage of schools that enrolled greater proportions of students of color (African American, Hispanic, American Indian, and mixed race students) offered advanced courses in all four of the subject areas than schools with lower proportions of such students. More specifically, without adjusting the results by any other school characteristics, schools that enrolled greater than 50% students of color were much less likely to offer advanced courses. Once the analysis was adjusted for student enrollment and school characteristics, schools serving at least 60% students of color had lower odds of offering at least one advanced course in mathematics and science. Regardless of the effects of other factors, the results made very clear that students in schools with high concentrations of students of color were less likely to offer advanced courses.

 A lower percentage of high-poverty schools than low-poverty schools offered advanced courses. This finding was particularly true with respect to science and mathematics. However, when adjusted for school enrollment and school characteristics, the odds of a high-poverty school offering advanced courses were significantly lower for only for the English Language Arts and social studies subject areas.

Identifying the effect of the percentage of students living in poverty on a school’s odds of offering advanced courses was difficult because the percentage of students living in poverty tends to be highly correlated with a number of other school characteristics. In particular, the percentage of students living in poverty and the percentage of students of color (defined here as African American, Hispanic, American Indian, and mixed race students) was highly correlated. Thus, when the percentage of students of color was removed from the analyses, the percentage of students living in poverty was always statistically significantly and negatively associated with the odds of offering advanced courses. Likewise, when the percentage of students living in poverty was removed from the analyses, the percentage of students of color is always statistically significantly and negatively associated with the odds of offering advanced courses. Such results strongly suggest that students living in poverty and students of color generally have less access to advanced courses than other students.

Schools in the Philadelphia School District generally have lower odds of offering advanced courses than schools across the state. Indeed, the percentage of Philadelphia School District schools offering advanced courses was substantially lower than the average for other urban districts and the average for all schools in the Commonwealth. Even after adjusting the results for student enrollment and the student characteristics of schools, the Philadelphia School Districts schools still had lower odds of offering advanced courses across all four subject areas.

Finally, schools in districts with greater actual instructional expenses per weighted average daily membership had greater odds of offering advanced courses. This was true with respect to offering at least one advanced course in each of the four subject areas as well as across all four subject areas combined. This finding remained accurate even after I adjusted the results by student enrollment and the characteristics of students in the school. Thus, in short—money matters with respect to the ability of schools to offer advanced courses. Money matters because offering advanced courses can incur additional costs to schools. This is particularly true in regards to AP and IB classes which require schools to expend funds to participate. Moreover, because advanced courses often have smaller class sizes, they can be more costly to staff.

INTRODUCTION

One of the more consistent findings in education research is that access to advanced coursework—particularly high-quality advanced coursework such as Advanced Placement or International Baccalaureate course—is associated with students being college and career ready (Adelman, 1999). Indeed, students enrolling in and successfully completing such courses are more likely to enroll in post-secondary institutions, complete a post-secondary degree, and complete such a degree within a shorter time frame. Thus, state and federal policymakers have long discussed policies and strategies that would increase enrollment in such classes as a means to improve college attendance and completion.

Concomitantly, researchers have also consistently found that access to advanced coursework is not equitably distributed across students and schools. For example, researchers have consistently found that students living in poverty, students of color, English Language Learner students, and special education typically have lower enrollment in such classes as compared to their peers within the same schools. Differences exist across schools as well. Specifically, students enrolled in schools with high percentages of students living in poverty, students of color, English Language Learner students, and special education often have less access to advanced coursework than their counterparts in other schools.

In the Commonwealth, both the state legislature and Pennsylvania Department of Education (PDE) have underscored the importance of enrollment in and completion of advanced courses. PDE, in fact, has concluded that access to advanced coursework is an important indicator of school quality and includes several indicators of course access in the School Performance Profile (SPP) data files.[i]

In this policy brief, I examine school-level offerings of advanced courses, including Advanced Placement courses, International Baccalaureate courses, and courses designated as advanced by PDE. In addition, I examine the school characteristics associated with offering such courses in English Language Arts, mathematics, science, and social studies. I also examine the school characteristics associated with a school offering advanced courses in all four subject areas. The remainder of this policy brief describes out data and methods followed by a presentation of findings and then concluding with policy implications and recommendations.

[i] Available at: http://www.paschoolperformance.org/Downloads

DATA AND METHODS

 Data for this analysis was downloaded from the PDE website, thus is available to the public. The primary data used to identify schools that offer advanced courses included the following elements:

  • School offered at least one Advanced Placement (AP) course in English language arts, mathematics, science, or social sciences-history.
  • School offered at least one International Baccalaureate (IB) course in English language arts, mathematics, science, or social sciences-history.
  • School offered at least one course (including AP and IB classes) in English language arts, mathematics, science, or social sciences-history identified by PDE as being an advanced course in that subject area.

By combining all three of the above data points, I created one variable that indicated if the school offered an advanced course for each of four subject areas (English, mathematics, science, and social studies). Thus, in my analyses, I examine if a school offered any type of advanced coursework in each of the four subject areas.

I also created an additional variable that indicated if a school offered at least one advanced course in each of the four subject areas. This variable was coded with a “1” if the school offered at least one advanced course in each of the four subject areas and “0” if the school did not offer at least one advanced course in each of the four subject areas. Thus, a school offering at least one advanced course in three of the subject areas would be coded with a “0” while a school offering at least one advanced course in each of the four subject areas was coded with a “1”. In terms of data accuracy, I assume that the data was accurate given that the results are used in the Commonwealth’s School Performance Profile.

FINDINGS

Research has consistently found that schools with lower enrollments are less likely than schools with more students to offer advanced courses due to issues such as lack of student demand for the courses, low funding levels, and lack of access to teachers with appropriate training to offer the courses. To examine the relationship between the number of 11th and 12th grade students enrolled in a school and access to advanced courses, I divided schools into eight enrollment categories that are shown in Table 1 below. This grouping approach was selected as a way to differentiate schools by the number of 11th and 12th grade students enrolled in a school rather than as a way to create eight groups with an equal number of schools or students. In Table 1, I include the number and percentage of schools for each of the eight groups as well as the number and percentage of 11th and 12th grade students for each group of schools. Note that this analysis includes only schools that enrolled 11th and 12th grade students in the 2014-15 school year as well as had data reported on advanced coursework. Thus, this analysis excludes 80 schools that enrolled 11th and 12th grade students but did not have advanced coursework data. Of these 80 schools, 78 were career and technical education schools. The other two schools had only one 11th and 12th grade students enrolled in the school.

Note that about 66% of schools enrolled 400 or fewer 11th and 12th grade students, but such schools enrolled only about 36% of all 11th and 12th grade students. At the other end of the spectrum, about 18% of schools enrolled more than 600 11th and 12th grade students and these schools enrolled almost 42% of all 11th and 12th grade students. Thus, the 125 largest schools enrolled more 11th and 12th grade students than the 452 schools with 400 or fewer 11th and 12th grade students. It is important to remember, then, that larger schools that offer advanced courses can provide access to advanced courses to far more students than smaller schools that offer advanced coursework.

Table 1: Number and Percent of Schools and Students
for Schools Enrolling 11th and 12th Grade Students by Enrollment Grouping
adv-course-access_table-1

Data Source: PDE Student Enrollment file, 2015[ii]

[ii] See http://www.education.pa.gov/Data-and-Statistics/Pages/Enrollment%20Reports%20and%20Projections.aspx#tab-1

The strong relationship between the number of students enrolled in a school and the offering of advanced coursework in a school revealed in the aforementioned national research is also evident in the Pennsylvania data. Indeed, as shown in Figure 1, only about 23% of the schools with the lowest enrollments offering advanced courses in all four areas as compared to 97% of schools with the largest enrollments. Note that once enrollments exceeded about 300 students, the vast majority of schools offered at least one advanced course in each of the four subject areas. Further, less than 5% of schools with 11th and 12th grade enrollments greater than 600 students did not offer at least one advanced course in each of the four subject areas. Thus, undoubtedly, the number of 11th and 12th grade students enrolled in a school is strongly associated with a school offering advanced courses in these four subject areas.

Figure 1: Percentages of Schools Offering Advanced Coursework
in All Four Core Course Areas by Student Enrollment in Grades 11 and 12 (2015)
adv-course-access_figure-1

Data Source: PDE Student Enrollment file, 2015

Table 2: Percentage of Schools Offering at Least One Advanced Course
by Subject Area and Student Enrollment in 11th and 12th grades (2015)
adv-course-access_table-2

Data Source: PDE Student Enrollment file, 2015; PDE School Performance Profile 2014-15 [Located at: http://www.paschoolperformance.org/Downloads]

Access to Advanced Coursework by School Characteristics

 In this section of the report, I examine access to advanced coursework by four school characteristics: percentage of economically disadvantaged students, percentage of minority students, and geographic locale (urban, suburban, town, and rural), and charter school status.

Access to Advanced Coursework by School Poverty

In this analysis, I define students living in poverty as those students participating in the federal free and reduced-price meals (FARM) program. While such data does not provide information on the range or depth of student poverty, this is the only available information on student poverty that is publicly available. For this analysis, I divided schools into five equally sized groups based on the percentage of students enrolled in the school living in poverty. Each group had either 135 or 136 schools. Table 3 below provides the ranges of the percentages of students living in poverty.

Table 3: Ranges in the Percentage of Students Living in Poverty
for the Quintiles of Schools by Student Poverty
adv-course-access_table-3

Data Source: PDE Student Enrollment data file, 2015;
PDE School Performance Profile data file, 2014-15

As shown in Figure 2, a far greater percentage of the lowest-poverty than the highest-poverty schools offered advanced courses in all four subject areas with the greatest disparities in science (53.7 percentage points) and mathematics (41.9 percentage points). Strikingly, in science, only about 44% of the highest-poverty schools offered any advanced course as compared with nearly 98% of the lowest-poverty schools. Finally, 94% of the lowest-poverty schools offered at least one advanced course in all four subject areas as compared to only about 33% of the highest-poverty schools—a difference of 61% percentage points.

Thus, undoubtedly, students enrolled in the high-poverty schools have less access to advanced courses in the four subject areas than their peers in the lowest-poverty schools. This inequity likely leaves students in the highest-poverty schools less prepared for the rigors of higher education than if such students had access to advanced courses.

Figure 2: Percentages of Schools Offering Advanced Coursework
in All Four Core Course Areas by Percentage of Students Participating in FARM (2015)
adv-course-access_figure-2
Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Access to Advanced Coursework by Percentage of Students of Color

In this analysis, I define students of color (SoC) as students that identify as African American, Hispanic, and American Indian students as well as students that identify as being of a mixed race background. I divided schools into five equally sized groups based on the percentage of students of color enrolled in the school. Each group had either 135 or 136 schools. Table 4 below provides the ranges of the percentages of students of color. Schools with the lowest percentage of students of color enrolled fewer than 3.2% students of color. At the other end of the spectrum, schools with the greatest percentages of students of color enrolled more than 46.9% students of color.

Table 4: Ranges in the Percentage of Students of Color
for the Quintiles of Schools by Student of Color
adv-course-access_table-4

Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Figure 3 reveals an interesting pattern: a lower percentage of the most segregated schools—specifically schools with the lowest percentage of students of color and schools with the greatest percentages of students of color—than schools in quintiles 2 through 4 offered advanced coursework in the four subject areas. However, clearly a far lower percentage of the schools with the greatest percentages of students of color clearly offered advanced coursework than other schools. As with the students in poverty analysis, this analysis shows that the greatest disparity in access was for mathematics and science. Specifically, the difference between the schools with the lowest and greatest percentages of students of color were 33 percentage points in science and nearly 30 percentage points in mathematics. In both cases, a greater percentage of schools with the lowest percentages of students of color offered advanced courses than schools with the greatest percentages of students of color.

Thus, students enrolled in schools serving at least 47% students of color had less access to advanced courses than other students.  This inequity leaves students in schools greater percentages of students of color less prepared for the rigors of higher education than if such students had access to advanced courses as in schools with few students of color.

Figure 3: Percentages of Schools Offering Advanced Coursework
in All Four Core Course Areas by Percentage of Students of Color (2015)
Adv Course Access_Figure 3.jpg
Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Access to Advanced Coursework by Geographic Locale

In this analysis, I focus on the percentage of schools offering advanced courses by four geographic locales: urban, suburban, town, and rural. I use the National Center for Education Statistics information on geographic locale to identify the locales of Pennsylvania schools.[To read about the descriptions of the geographic locales, see: http://nces.ed.gov/ccd/commonfiles/localedescription.asp I collapsed all city classifications into urban, all suburban classifications into suburban, all town classifications into town, and all rural classifications into rural.]

As shown in Figure 4, a far lower percentage of city schools offered advanced courses than schools in any of the other three locales. Specifically, only slightly more than 50% of city schools offered at least one advanced course in mathematics and only slightly more than 40% of city schools offered at least one advanced science class. Not surprisingly, then, the greatest disparities between city schools and schools in other locales were for mathematics and science.

There only minimal differences between suburban, town, and rural schools in offering advanced courses in the four subject areas, but there were differences between the three with respect to offering at least one advanced course in all four subject areas. Specifically, a greater percentage of suburban schools than town and rural schools offered advanced courses in all four subject areas. Further, a greater percentage of town schools than rural schools offered advanced courses in all four subject areas.

Figure 4: Percentages of Schools Offering Advanced Coursework
in All Four Core Course Areas by Geographic Locale (2015)

adv-course-access_figure-4

Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Since Philadelphia skews the results because of the large number of schools in the district, I also calculated the percentages of city schools offering advanced courses for city schools in the Philadelphia school district and city schools not in the Philadelphia school district. As shown in Figure 5, a lower percentage of Philadelphia schools offered advanced courses for each of the four subject areas as well as for the measure across all four subject areas combined. The differences were rather large—greater than 13 percentage points–for mathematics, science, and across all four subject areas.

 Figure 5: Percentages of Schools Offering Advanced Coursework
in All Four Core Course Areas for Philadelphia and Other Pennsylvania Cities (2015)

adv-course-access_figure-5

Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Access to Advanced Coursework by Charter School Status

Because of the strong relationship between student enrollment and schools offering advanced courses, this analysis compares advanced courses in charter schools and public schools but disaggregated the results by the number of 11th and 12th grade students enrolled in the school. Table X documents the number of charter schools and public schools by the ranges of 11th and 12th grade students enrolled in the school. Because of the much smaller number of charter schools with greater than 300 students in the 11th and 12th grades, I collapsed groups of schools. Specifically, I created an enrollment grouping with between 301 and 600 students in the 11th and 12th grades and an enrollment grouping with greater than 600 students enrolled in the 11th and 12th grades. Despite collapsing these groups, there were still fewer than 10 charter schools in the two larger enrollment groupings. Because of the small number of charter schools in these groups, the reader should take caution in making conclusions about schools in these two groups. Also note that 46 of the 75 charter schools included in the analysis were located in either urban or suburban locales. Of the remaining charter schools, 11 were cyber charter schools, thus had no geographic locale. Thus, a far greater proportion of charter schools were located in large metro areas in which schools would arguably have an easier time finding a well-qualified teacher to instruct advanced courses.

Table 5: Number of Charter Schools and Public Schools
by 11th and 12th Grade Enrollment Groupings

Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

As shown in Figure 6, a lower percentage of charter schools offered advance courses across all of the enrollment groups. Moreover, the gaps were rather large—greater than 20 percentage points for groups 2 and 4 and greater than 30 percentage points for the other groups. In particular, note that only about 4% of charter schools with 100 or fewer students offered advanced courses in all four subject areas. Of the charter schools included in this analysis, 36% were in this enrollment grouping. In comparison, almost 39% of public schools with 100 or fewer 11th and 12th grade students offered at least one advanced course in each of the four subject areas. This analysis makes clear that students in charter schools were far less likely to have access to advanced courses than students in public schools.

Figure 6: Percentages of Public and Charter Schools Offering Advanced Coursework
in All Four Core Course Areas by Student Enrollment in Grades 11 and 12 (2015)adv-course-access_figure-6Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Table 6 presents information about access for each of the four core course subject areas as well as for all four subject areas combined for both charter schools and public schools by the number of 11th and 12th grade students enrolled in the school. For groups 1 through 4, a greater percentage of public schools than charter schools offered at least one advanced course for each of the five outcomes. The gaps in access were greatest for the schools with the smallest enrollments and less for schools with greater enrollments. For example, while 66.7% of public schools with less than 100 11th and 12th grade students offered at least one advanced course in science, only 11.1% of charter schools with similar enrollments offered at least one advanced course. For schools with more than 600 11th and 12th grade students, a greater percentage of charter schools offered at least one advanced course for all but science. It is important to note that there were only four charter schools in this category and all four were cyber charter schools.

 Table 6: Percentage of Public and Charter Schools Offering Advanced Courses
by the Number of 11th and 12th Grade Students (2015)

adv-course-access_table-6

Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Statistical Analysis of Access to Advanced Coursework for All Schools

Because other school factors also influence the degree to which schools offer advanced coursework, I used a statistical approach called logistic regression to simultaneously examine the influence of various factors on the odds that a school offered an advanced course. In this type of analysis, the outcome variable is binary—meaning there are only two possible outcomes. In this case, the outcome variables indicate whether a school offers an advanced course (Yes) or it does not (No). The approach also allows for the inclusion of a number of explanatory variables that potentially influence the outcome variable. For example, as shown above, the number of 11th and 12th grade students enrolled in a school heavily influences whether a school offers an advanced course. I include the following variables to explain the odds that a school offers an advanced course:

  • Indicators of the number of 11th and 12th grade students enrolled in the school;
  • Percentage of White and Asian students;
  • Percentage of students living in poverty;
  • Brick and mortar charter school indicator;
  • Cyber charter school indicator;
  • Magnet school indicator;
  • Career and technical school indicator;
  • Philadelphia School District indicator; and,
  • Pittsburgh School district indicator.

The logistic regression analysis was a single-level model rather than multi-level model. A multi-level logistic regression analysis of this data that models schools nested within districts might yield slightly different results, but I am confident that the direction of the relationships between the various variables and the odds of a school offering advanced coursework would remain unchanged.

The results are shown in Table 7. Across the top of the columns are the names of five outcome variables that indicate whether or not a school offered: (1) advanced courses in each of the four subject areas; (2) at least one advanced course in mathematics; (3) at least one advanced course in science; (4) at least one advanced course in English language arts; and, (5) at least one advanced course in social studies.

Under each of these columns are two columns: “stat sig” and “odds ratio”. The “stat sig” column indicates if the factor has a statistically significant influence on the odds that a school offers an advanced course. In this analysis, I use any value of less than 0.100. Although researchers often use values of less than 0.05 to identify statistically significant relationships, values between 0.05 and 0.10 are suggestive of a statistically significant relationship. I note the difference in the two levels in our discussion of the findings.

The “odds ratio” column indicates the odds ratio that a school offers and advanced course. Odds ratios greater than 1.0 indicate the factor is positively associated with a school offering an advanced course. An odds ratio less than 1.0 indicates that the factor is negatively associated with a school offering an advanced course.

School Size

The first block of factors are indicators of the number of 11th and 12th grade students enrolled in the school. Note that the missing group is schools with between 301 to 500 students. The results for all of the other indicators are relative to the set of schools with between 301 and 500 students. The results show that the three sets of schools with smaller enrollments than 301 students were all statistically significantly less likely to offer an advanced course than schools with between 301 and 500 students for all five outcomes variables. This substantiates prior research on the relationship between school size and offering of advanced coursework as well as the descriptive statistics I presented above. There were no consistent results for larger schools across all five outcomes. However, schools with between 601 and 1,000 students had substantially greater odds of offering at least one advanced course across all four subject areas and of offering at least one advanced course in mathematics than schools with between 301 and 500 students.

Student Characteristics

With respect to student characteristics, neither the percentage of female students nor English Language Learner students were statistically significantly related to any of the five outcome variables.

Interestingly, the percentage of students living in poverty was negatively associated with the odds of a school offering advanced courses for three outcomes while schools with less than 40% of White and Asian students were negatively associated with offering advanced courses for the other two outcomes. Specifically, the greater the percentage of students living in poverty in a school, the lower the odds that a school offered (1) at least one advanced course in each of the four subject areas, (2) at least one advanced course in English language arts, and (3) at least one advanced course in social studies.

In both mathematics and science, schools with less than 40% White and Asian students had substantially lower odds of offering an advanced course. Thus, students in schools in which a majority of students were students of color were far less likely than other schools to offer advanced courses in both mathematics and science. This is a notable finding given the importance of that access to advanced STEM courses has on opening the doors to high-paying careers that drive innovation in the Commonwealth.

Also note that I found the percentage of students living in poverty and the percentage of students of color (African American, Hispanic, American Indian, and students of mixed race) to be fairly highly correlated. This means that schools serving a high proportion of students of color are very often also serving a high proportion of students living in poverty as well. When I removed the percentage of students living in poverty from the analysis, schools with less than 40% White and Asian students had statistically significantly lower odds of offering advanced courses for all five outcomes. Similarly, when I removed schools with less than 40% White and Asian students from the analysis, an increase in the percentage of students living in poverty was statistically significantly associated with a decrease in the odds of schools offering advanced courses across all five outcomes. Thus, the evidence suggests that student race, ethnicity, and socio-economic status are statistically significantly associated with the odds of offering advanced courses. Moreover, I found that as the percentages of students living in poverty and students of color increases, the odds of schools offering advanced courses decreases. In short, students in schools serving high proportions of students living in poverty and students of color have less access to advanced courses than other students.

School Type

 Brick and mortar charter schools had substantially lower odds of offering at least one advanced course in mathematics, science, and in at least one advanced course in each of the four subject areas. Again, given the importance of students having access to advanced courses in STEM, this is an important finding. Note, also, that brick and mortar charter schools also had lower odds of offering at least one advanced course in English language arts and social studies. Even though these two results were not statistically significant, the overall trend is that brick and mortar charter schools have lower odds of offering their students advanced coursework. These findings suggest that the belief that charter schools will lead to an increase of students well-prepared for rigorous post-secondary studies in STEM majors may be misplaced.

There was only one statistically significant finding for cyber charter schools. Specifically, cyber charter schools had statistically significantly lower odds of offering advanced course in mathematics. Cyber schools also had lower odds of offering advanced courses for the other four outcomes even though the results were not statistically significant.

Not surprisingly, magnet schools had greater odds of offering advanced courses in mathematics and for offering at least one advanced course in each of the four subject areas. Although not statistically significant, magnet schools also had greater odds of offering advanced courses for the other three subject areas as well.

Finally, across all five outcomes, career and technical schools had substantially lower odds of offering advanced courses. This is not particularly surprising given that career and technical schools are typically not designed to offer such courses.

Large School Districts

Schools in the Philadelphia School District had statistically significantly lower odds of offering advanced courses for mathematics, science, and for offering at least one advanced course in each of the four subject areas. These findings are disconcerting given the importance of students having access to advanced courses in STEM areas.

While there were no statistically significant results for schools in the Pittsburgh School District, note that the odds across all five outcomes were positive. Indeed, in examining the simple percentages of schools in large city school offering advanced courses, a relatively high percentage of Pittsburgh schools offered advanced courses.

Table 7: Logistic Regression Analysis Results for All Pennsylvania Schools
with 11th and 12th Grade Students and Information on Advanced Coursework Offerings
adv-course-access_table-7
Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Statistical Analysis of Access to Advanced Coursework for All Schools

In this analysis, I examine the results for only traditional public schools. Thus, I excluded all charter schools. I also excluded four schools that have large proportions of special education students that are designed to meet the unique needs of special need students. I focus on traditional public schools because I have access to both the actual instructional expenditures per weighted average daily membership as well as the percentage of residents 25 years or older in each school district while such data are not available for charter schools

For this analysis, I include the following factors that are potentially associated with the odds of a school offering advanced courses:

  • Indicators of the number of 11th and 12th grade students enrolled in the school;
  • Percentage of White and Asian students;
  • Percentage of students living in poverty;
  • Percentage of English Language Learner students;
  • Percentage of female students;
  • Percentage of gifted students;
  • Percentage of special education students;
  • Magnet school indicator;
  • Actual instructional expenditures per weighted average daily membership; and,
  • An indicator of schools located in large and mid-sized cities.

Student Enrollment

As shown in Table 8, the three groups of schools with the number of 11th and 12th grade students less than 351 had lower odds of offering advanced courses than schools enrolling between 351 and 450 11th and 12th grade students. There was only one statistically significant result for schools with more than 450 11th and 12th grade students. Specifically, schools with greater than 700 11th and 12th grade students had greater odds of offering advanced courses than schools enrolling between 351 and 450 11th and 12th grade students.

Student Characteristics

As in the prior analysis, I found schools with less than 40%White and Asian students had substantially lower odds of offering at least one advanced course in mathematics, science, and in each of the four subject areas combined. In short, students in schools serving high proportions of students of color have less access to advanced courses in STEM fields and are also less likely to have access to advanced courses in each of the four major subject areas.

As the percentage of students living in poverty in a school increases, the odds of the school offering at least one advanced course in English decreases. This was the only statistically significant relationship between the percentage of students living in poverty and the odds of offering an advanced course. When I removed the race/ethnicity variables, I found that the percentage of students living in poverty became statistically significantly associated with the odds of a school offering advanced courses across all five outcomes. Specifically, I found that as the percentage of students living in poverty increases, the odds of schools offering at least one advanced course decreases across all five outcomes.

I found one statistically significant relationship between the percentage of female students in a school and the odds of offering an advanced course. This result indicated a positive relationship between the percentage of female students and the odds of a school offering at least one advanced course in social studies.

Finally, I found that as the percentage of special education students increases, the odds of offering at least one advanced course decreased for all outcomes except social studies. If I had access to student-level data about the types of disabilities and achievement levels, I could determine if this result is simply in response to students not possessing the academic ability to be successful in advanced courses or stemmed from educators not advocating for such students to enroll in advanced courses.

School Type

            The only school type included in this analysis was magnet schools. With the other factors included in the analysis, I did not find any statistically significant relationships between magnet schools and the odds of a school offering advanced courses for any of the five outcomes.

Expenditures

            Unfortunately, PDE does not provide school-level expenditure data. Thus, I cannot make a direct connection between school-level expenditures and access to advanced courses. PDE does, however, report the actual instructional expenses (AIE) as well as the AIE per weighted average daily membership (WADM) for public school districts. According to PDE, the AIE is defined in the following manner:

Actual Instruction Expense Includes all general fund expenditures as reported on the annual financial report by the school districts except those expenditures for health services, transportation, debt service, capital outlay, homebound instruction, early intervention, community/junior college education programs and payments to area vocational-technical schools.  Deductions are also made for selected local, state and federal revenues and for refunds of prior year expenditures and receipts from other local education agencies.  It is calculated in accord with Section 2501 of the Pennsylvania Public School Code of 1949.(See KidsCount: http://www.datacenter.kidscount.org/data/tables/6700-school-funding–actual-instructional-expenses–total-and-per-weighted-adm#detailed/2/any/false/1460,1249,1120,1024,937/3005,3006/15171)

To arrive at the AIE per WADM, the district AIE is divided by the WADM which is defined by PDE as: “The assignment of weight by grade level to the average daily membership.  The current weighting is half-time kindergarten at 0.5, full-time kindergarten at 1.0, elementary (grades 1-6) at 1.0, and secondary (grades 7-12) at 1.36.” (See KidsCount: http://www.datacenter.kidscount.org/data/tables/6700-school-funding–actual-instructional-expenses–total-and-per-weighted-adm#detailed/2/any/false/1460,1249,1120,1024,937/3005,3006/15171)

I found a statistically significant relationship between the AIE per WADM and the odds of a school offering at least one advanced course for three of the five outcomes. Specifically, I found that the AIE per WADM was positively associated with the odds of a school offering at least one advanced course in mathematics, science, and in each of the four subject areas combined. In other words, the greater the instructional expenses, the greater the odds that a school would offer at least one advanced course in mathematics, science, and in each of the four subject areas combined. This suggests that, at least for three of the outcomes, money actually matter. To repeat—schools with greater actual instructional expenses had greater odds of offering advanced courses, particularly in the subject areas of mathematics and science. While some may argue this underscores that the way in which money is spent matters most—in this case, districts choosing to spend their money on recruiting or developing teachers with the capacity to teach such courses and on offering AP and IB courses which have associated costs. However, you can’t spend what you don’t have. Indeed, a wealth of research has shown that overall access to money matters as does the manner in which that money is spent.

Locale

In this analysis, I included a variable that identified if a school was in one of four districts: Philadelphia, Pittsburgh, Allentown, or Erie City. These are the four districts identified by the National Center for Education Statistics as being located in large or mid-size cities in Pennsylvania. Of the 64 schools included in the analysis, 48 were from Philadelphia. Thus, the results for this factor are more reflective of schools in Philadelphia than the other three districts. In fact, the other three districts have substantially higher percentages of schools offering advanced courses than Philadelphia schools. There was only one statistically significant finding for this variable—schools in large or mid-sized cities had substantially lower odds of offering at least one advanced courses in each of the four subject areas.

Table 8: Logistic Regression Analysis Results for All Pennsylvania Public Schools*
with 11th and 12th Grade Students and Information on Advanced Coursework Offerings
adv-course-access_table-8
Data Source: PDE School Enrollment data file, 2015;
PDE School Performance Profile data file

Conclusions

This analysis of publicly available data suggests schools enrolling greater percentages of students living in poverty and students of color are less likely to offer advanced courses. Moreover, a lower percentage of 11th and 12th grade students of color are enrolled in schools that offer advanced courses. Most disadvantaged in this regard are African American students. Indeed, only 58% of African American students enrolled in the 11th and 12th grades were enrolled in schools that offered at least one advanced course in English language arts, mathematics, science, and social studies. In comparison, 87% of White students are enrolled in schools that offer advanced courses in each of the four subject areas.

In addition, a lower percentage of rural schools and brick-and-mortar charter schools offer advanced courses. This is particularly true in mathematics and science. While smaller school sizes explain much of the result for rural schools, brick-and-mortar charter schools have lower odds of offering advanced courses in mathematics and science even after adjusting for differences in enrollment and student characteristics between brick-and-mortar charter schools and other schools.

Finally, and importantly, schools in districts with greater instructional expenditures have greater odds of offering advanced courses in mathematics and science after adjusting the results for student enrollment and student characteristics of schools.

 

 

 

Even MORE evidence that money actually matters to student achievement!

Despite repeated claims that “money does not matter”, solid research evidence continues to mount that money, in fact, does matter to student outcomes.  Yet, many state legislatures  have failed to return funding amounts to pre-recession levels and most certainly have not invested in education systems to meet the higher expectations for student outcomes adopted by most states in the past few years.

Unfortunately, Pennsylvania is one of these states. In fact, report after report continues to find that Pennsylvania has one of the least equitable school finance “systems” in the country (https://www.washingtonpost.com/local/education/pa-schools-are-the-nations-most-inequitable-the-new-governor-wants-to-fix-that/2015/04/22/3d2f4e3e-e441-11e4-81ea-0649268f729e_story.html) and does not have a particularly adequate system either. Indeed, the governor and legislature still cannot agree on last year’s budget that called for increases in the fiscal investments in the state’s K-12 education system.

New research (http://www.nber.org/papers/w22011?utm_campaign=ntw&utm_medium=email&utm_source=ntw) by Julien Lafortunewas, Diane Whitmore Schanzenbach, Jesse Rothstein was  recently released that examined the effects of increasing state expenditures in K-12 education and the degree to which funding was equalized between affluent and poor districts.

In short, the authors found the following:

“Using an event study design, we find that reform events–court orders and legislative reforms–lead to sharp, immediate, and sustained increases in absolute and relative spending in low-income school districts.”

Further, they found that the increases in spending–particularly in poor districts–improved student outcomes. Specifically, the authors note:

“Using representative samples from the National Assessment of Educational Progress, we also find that reforms cause gradual increases in the relative achievement of students in low-income school districts, consistent with the goal of improving educational opportunity for these students.”

In sum, the authors find that increasing K-12 education spending has a “large” effect on educational achievement.

The authors note that many critics of school funding reforms argue that voter behavior on tax referendums offset the influence of school finance reform, thus efforts to change school finance systems is not worth the effort. The authors of this study, however, found that this was not true. Indeed, the authors actually conclude that, “Courts and legislatures can evidently force improvements in school quality for students in low-income districts.

Moreover, the authors conduct a cost-effectiveness analysis of the increases in expenditures and find a benefit to cost ratio of almost 1.4 to 1. They also note that due to data limitations, these cost benefits are underestimated and the true benefits are actually much larger.

This new research adds to a large number of studies tat consistently find that increases investments in K-12 education improves student achievement and is cost-effective in the long-run.Further, the research consistently finds that reducing inequities across poor and wealthy districts also reduces the achievement gap between such districts by increasing achievement in poor districts at a faster rate.

Unfortunately, rather than taking a long-term view on achievement and a state’s economic future, many states have generally looked to quick-fixes that are cheap relatively to school finance reform (see http://nepc.colorado.edu/files/PB-ProductivityResearch%20%282%29.pdf). Such efforts not only waste money in the long-term, they miss opportunities to educate children so that they might have a brighter (and more productive) future.

Why Pennsylvania policymakers continue to fight over investing in K-12 education as a driver of future state economic growth remains bewildering. As this research shows, investments in K-12 education will result in economic benefits to the Commonwealth over the long run. It is finally time for Commonwealth leaders and courts to act!

Additional resources:

Does Money Matter in Education? by Bruce Baker (Rutgers University)
http://www.shankerinstitute.org/resource/does-money-matter

Jackson, C.K., Johnson, R.C., & Persico, C. (2016). The effects of school spending on
educational and economic outcomes: Evidence from school finance reforms.
Quarterly Journal of Economics, 131(1).
Previous version of the paper can be found for free at: http://www.nber.org/papers/w20847

Papke, L. (2005). The Effects of Spending on Test Pass Rates: Evidence from
Michigan. Journal of Public Economics 89(5), 821-839.
http://www.sciencedirect.com/science/article/pii/S0047272704000908

Abstract:This study uses data on standardized test scores from 1992 through 1998 at Michigan schools to determine the effects of spending on student performance. The years in the data set straddle 1994, when Michigan dramatically changed the way that K-12 schools are funded, and moved toward equalization of spending across schools. Focusing on pass rates for a fourth-grade math tests (the most complete and consistent data available for Michigan), I find that increases in spending have nontrivial, statistically significant effects on math test pass rates, and the effects are largest for schools with initially poor performance.

 

 

 

 

 

 

 

Black Student Achievement in PA: 4th Grade NAEP Scores

In this first in a series of blog posts about Black student achievement, equity, and opportunity in Pennsylvania, I examine the NAEP 4th grade mathematics and reading scores from 2015. You can read about the NAEP exams and scores at https://nces.ed.gov/nationsreportcard/

Importantly, I rely on scale scores rather than any of the proficiency groups because we lose a lot of information when we use the various performance groups instead of the scale score.

In the tables and links below, I present the results for all states for the three primary racial/ethnic groups (White, Black, Hispanic). I also disaggregate the racial/ethnic results by economically disadvantaged status defined by participation in the federal free- and reduced-price meals programs. Importantly, I rely on the NAEP statistical tool to determine if differences in scores are actually statistically significant. As many have pointed out, differences in scale scores may or may not indicate REAL differences between states.

So, how do Black students in PA perform relative to other Black students?

Grade 4 Mathematics

As shown in Table 1A, PA students from all three major racial/ethnic groups generally performed about the same as their peers across the nation. Two notable exceptions, however, stand out. In both 2003 and 2015, PA Black students had statistically significantly lower scores than their peers across the US. Interestingly, PA Black students had closed the gap between with their US peers between 2003 and 2005 and had actually started to slightly outperform their US peers by 2013, although the difference was not statistically significant. But, between 2013 and 2015, scores for PA Black students plummeted by 7 points which lead to PA Black students having a statistically significantly lower scale score than the average scale for Black students for the US. More on this later.

Table 1A: Average Scale Scores by Race/Ethnicity for the Nation and Pennsylvania
NAEP 4th grade math_PA and US

Table 1B shows the 2015 results for Pennsylvania relative to the performance of similar students in other states.. PA Black students did not outperform Black students in any state in 2015. PA Black students performed about the same as Black students in 31 states, but performed worse than Black students in 12 other states. In contrast, PA White students outperformed their peers in 19 states and underperformed their peers in only two states.

When looking at economically disadvantaged students, PA White students outperformed their peers in only one other state. PA Black (and Hispanic) students did not outperform their peers in any state. PA Black students performed worse than their peers in 13 states.

Finally, with respect to not economically disadvantaged students, PA Black students again did not outperform their peers in any states. However, PA Black students that were not economically disadvantaged only underperformed relative to their peers in 4 other states. Once again, White students outperformed their peers in 19 states.

Table 1B: Number of States with NAEP 4th Grade Mathematics Scale Scores Statistically Greater than, Equal to, or Less than Than PA Scale Scores
NAEP 4th grade math_ceepablog
Link to pdf with mathematics results for all states:
Fourth Grade NAEP Math 2015

As shown in Figure 1,not economically disadvantaged Whites outperformed all other sub-populations. Interestingly, not economically disadvantaged Blacks had about the same level of achievement as economically disadvantaged Whites until 2015. Between 2013 and 2015, something fairly drastic happened that negatively impacted the scores of Black students–particularly not economically Black students.

Figure 1: PA NAEP 4th grade Mathematics Scale Score by
Race/Ethnicity and Economically Disadvantaged Status, 2003-2015
NAEP 4th grade math x ecodis 2003 2015

Grade 4 Reading

As shown in Table 2A, there were only a few instances in which PA students scored better or worse relative to their peers across the US. PA White students outperformed their peers in 2007 and 2011, but performed the same in all other years. PA Black students performed substantially worse than their US peers in 2003, but performed the same across all other years–including 2015. Thus, the dramatic drop in mathematics scores did not occur in reading. Schools generally have a greater impact on mathematics scores than reading scores given that reading ability if more strongly correlated to student background characteristics and a student’s home life, particularly in the formative years prior to entering school.

Table 2A: Average Scale Scores by Race/Ethnicity for the Nation and Pennsylvania
NAEP 4th grade rdg_PA and US

Table 2B shows the results for states. Despite scoring the same as their national peers, PA Black students in all 3 groups of (all students, economically disadvantaged students, and not economically disadvantaged students) did NOT outperform their peers in any state. However, all PA Black students and economically disadvantaged Black students underperformed their peers in 11 and 13 states, respectively. PA not economically disadvantaged students performed equally to their peers in all other states. In contrast, PA White students again outperformed their peers in 20 states.

Table 2: Number of States with NAEP 4th Grade reading Scale Scores Statistically Greater than, Equal to, or Less than Than PA Scale Scores
NAEP 4th grade reading state comparison

Link to pdf with reading results for all states:
Fourth Grade NAEP Reading 2015

As shown in Figure 2, we see the same pattern as shown in Figure 1. However, the decrease in the scores for not economically disadvantaged students was even more pronounced. Indeed, their scores dropped 17 points–clearly more than one grade level and perhaps closer to two grade levels. Another way to think about the magnitude of this drop is that a student with a similar score profile dropped from the 85th percentile to the 66th percentile in the span of two years. This is a monumental drop in scores–especially within a two year time span–and completely eliminated the strong achievement progress shown from 2003 through 2013. Of course, this is NOT the same set of students. Each 4th grade score is for a completely different set of students. but to see such huge increases and decreases is quite rare.

Figure 1: PA NAEP 4th grade Reading Scale Score by
Race/Ethnicity and Economically Disadvantaged Status, 2003-2015
NAEP 4th grade reading x ecodis 2003 2015

Summary

While PA Black students perform on par with their peers across the nation, the fact that PA Black students do not outperform their peers in any other states and under perform their peers in around 10 other states is disheartening.

There are clear differences in student achievement between those that are eligible and not eligible for free- and reduced-price meals. Interestingly, Black students that were not economically disadvantaged scored about the same as White students that were economically disadvantaged through 2013. Then scores dropped precipitously in 2015 for some reason. I will explore these drops in another post.

Implications

Black students are a significant proportion of 4th grade students in PA–according to NAEP, about 13%. Further, the percentage of non-White students continues to increase in PA and across the US and this trend will likely accelerate rather than abate in the coming decades. PA must examine the underlying causes of the under performance of Black, Hispanic, and economically disadvantaged students if the Commonwealth wants to have a highly educated workforce that attracts businesses to the state. And, more importantly, we have a moral imperative to ensure EVERY child in the Commonwealth is well-educated. Failure to do so will cause long-term and irreparable issues in the future

Potential Causes?

Although we cannot attribute causes for the low performance of Black, Hispanic, and economically disadvantaged students, one very possible reason is the Commonwealth’s inequitable school finance system. Schools serving these students need MORE money, not less. Yet, the Commonwealth continues to adopt school finances systems that provide more revenue for wealthy White students than for other families. This must stop if we are to address the performance of our historically under-performing groups.

Other potential causes other than low-funding are: increased segregation, change in the type of schools attended (charter vs public), and change in curricula.