Can Charter Schools close the Achievement Gap?
Dwight Payne
John Near Scholar
Ms. Horan, Mentor
April 9, 2012
A Review of the Literature
Students of lower socioeconomic status often struggle disproportionally in the race to academic success. Researchers are searching for ways to unlock an equitable education system that rewards perseverance and creativity rather than the boon of a zip code or a certain shade of skin. They often perform correlational studies of cities or collections of districts with low-income, minority students who struggle to break free of poverty’s vacuum. Charter schools are only one new example of the effort to reform our broken education system and improve equity.
Still a young movement, the charter school effort began in 1991 (Zimmer & Buddin, 2005). A charter school is a publicly funded, independently run school that operates under the guidelines of a contract, or a “charter.” When a student enrolls at a traditional public school, that school receives a certain amount of money, the per-pupil expenditure, from the state and federal governments. When the student decides to enroll in his or her nearby charter school, the same funding goes almost entirely to the charter school instead. In 2005, over 40 states had passed laws allowing charter schools to operate. They accounted for over 3,400 schools nationwide, educating almost 1 million students (Zimmer & Buddin 2005). The number of charter-enrolled students hit nearly 1.5 million in 2008 and the movement’s remarkable growth continues.
Proponents argue that charter schools’ freedom from districts allows for greater innovation and creativity. They also claim that the ability of families to choose a charter school services low-income, minority students in particular who often suffer from the lowest performing public schools. They claim that choice also creates competition
between the traditional public schools and charter schools for students and funding (Zimmer & Buddin, 2005). The effect of which, contend supporters, is innovation and improvement spurned by free market exchange. The argument for a parent’s right to choose his or her child’s school, and the claim that higher achievement will come as a result, falls under the category of a more conservative position called market-based accountability (Haris & Harington, 2006). On the other end of the political spectrum lie those who would rather see districts more directly control their schools and thus criticize the charter school movement. Opponents argue that charter schools as a whole show no substantial improvement in achievement, that they often increase racial segregation in schools, and that they deprive school districts of funding (Zimmer & Buddin, 2005).
In a review of the literature surrounding charter schools and the achievement gap between students of different socioeconomic status, studies from across the country were reviewed. All sought correlations between charter school enrollment and changes in student achievement in areas with low-income, minority students. A study from New York City (Dobbie & Fryer, 2011) not only assessed the link between charter schools and academic improvement, but also systematically identified which specific educational methods and school cultures best-cultivated student success on standardized tests. This literature review combines evaluations of charter schools’ impact on the achievement gap with data on which specific educational and organizational methods are most integral to the success of effective charter schools. These complementary perspectives of student achievement construct a picture of the effectiveness or failure of charter schools in serving the socioeconomically disadvantaged.
Charter Schools in Los Angeles and San Diego
Zimmer and Buddin (2005) conducted a study of the effectiveness of Los Angeles Unified and San Diego Unified charter schools in closing the achievement gap. They examined the achievement of those schools’ students overall and the achievement of clusters grouped by their English proficiency and ethnicity categories. The study assessed five school years’ worth of data, from 1997-1998 to 2001-2002.The sample size provided by the two districts is substantial as it encompasses the 49 charter schools with over 25,000 students in the Los Angeles Unified School District (LAUSD) and the 21 charter schools with over 9,000 students in San Diego Unified School District (SDUSD).
In a longitudinal study, researchers tracked the progress of individual students in order to isolate the individual differences between different students and schools. By tracking only the changes in students’ test results, researchers controlled for base-level achievement and environmental factors such as parental involvement, to name one. The authors explained the confounding variable of “selection bias” and its importance in all studies regarding charter school attendance and achievement. The dilemma lies in the possibility that those students who elect to leave their traditional public schools in favor of a charter option differ from their classmates who remain in public school. Parental involvement in those students’ educations is likely to be significantly different and other factors including individual motivation and baseline achievement levels may also skew any comparison between the two groups of students.
In LAUSD, four percent of high school students were in charter schools and two percent of elementary students were in charter schools. In SDUSD, those numbers were eight and 2 percent, respectively. The Hispanic student population in LAUSD charter
Charter Schools 5 schools was significantly underrepresented in comparison to the percentage of Hispanic students in the district’s traditional public schools. In contrast, African American students of all grades were significantly overrepresented in LA charter schools. The district’s charter schools also educated a portion of Limited English Proficiency (LEP) students that was roughly 20 percent lower than that educated in LA public schools. Enrollment in SDUSD schools showed that Hispanics were underrepresented in elementary charter schools and overrepresented in secondary charter schools, although both differences in ethnic representation were less drastic than those displayed in Los Angeles charter schools. Although the gap was minor in its secondary schools, African Americans were overrepresented in San Diego charter schools as well.
In LAUSD, students did not improve at a significantly different rate in charter schools than they did in public schools. In SDUSD, charter school students scored between one and two percent worse in reading and one and five percent worse in math than those in public schools. These differences were statistically significant. Overall, the study showed that students in Los Angeles charter schools perform similarly to their LAUSD counterparts but that charter school students in San Diego lag behind students in SDUSD.
The paper’s introduction recognized the study's greatest limitation as its inability to assign cause to any findings. In other words, while the study provided valuable conclusions on the ability or inability of charter schools to close the achievement gap, it did not delve into the “nuances of school characteristics.” Such detailed understanding of differences between individual charter schools would be remarkably difficult on such a large scale. While the sheer magnitude of the study (over 34,000 students) lends it
Schools 6 statistical merit, the massive number of schools examined made distinguishing between educational approaches nearly impossible. In other words, Zimmer and Buddin (2005) were unable to explain why differences in achievement in San Diego occurred. Smaller case studies that focus on specific methods of unique charter schools could be invaluable in understanding why certain charter schools do or do not help close the achievement gap.
Charter School Effectiveness in Chicago
With a goal similar to that of Zimmer and Buddin (2005), to assign correlation between charter schools and closing the achievement gap, but with a significantly smaller sample size, Hoxby and Rockoff (2005) conducted a study of three charter schools in Chicago. They attempted to determine whether charter school students received a more effective education than students in public schools and whether students that elected to attend charter schools received better educations than they would if they had chosen to stay in their local public schools. Researchers examined three schools run by the The Chicago Charter School Foundation (CCSF): a for-profit Charter Management Organization. Edison Schools runs one school and a non-profit group known as American Quality Schools runs the other two charters. The three schools approach education similarly with a "structured school day and curriculum" and a significant effort to increase parent-involvement. This general characterization of a particular type of charter school falls into the category of a “No Excuses” school. The students of these schools are over representative of the socioeconomically disadvantaged student population in the Chicago Public School System. They are, however, representative of their local neighborhoods and public schools. It is also worth noting that the per-pupil expenditure
that charter schools received in Chicago in the 2003-2004 school year was 75 percent of the funding that the Chicago public schools received for each student.
Each of the three charter schools received more applications for admission than available spots and thus held lotteries for admission by grade. The study consisted of 2,448 students, all of who elected to attempt to move to a charter school and participated in each school’s respective lottery. Hoxby and Rockoff (2005) took advantage of the lottery-based system in an attempt to control for selection bias. In the study, the researchers’ control group was comprised of those who were not "lotteried in," in other words they applied to the charter school but did not win the lottery and instead returned to their local public schools. The experimental group was those who "lotteried in," those who won the lottery and attended one of the charter schools. Researchers affirmed the theory that the lottery system allows researchers to examine a representative sample size (those who won the lottery) of those who participated in the lottery. The winners were similar in measurable demographics such as income and ethnicity. It is then reasonable to conclude that these students are also representative in other non-measurable factors (Hoxby & Rockoff, 2005).
The study looked at lotteries held for the school years of 2000-2002. The students who “lotteried in” were matched with their public school achievement reports from past years to establish a baseline of achievement before the switch in schools. Achievement levels were measured using the Iowa Tests of Basic Skills (ITBS). For those who were unsuccessful in the lotteries and went back to public schools, this preceding data and later achievement data were both collected. When researchers analyzed the achievement from past years’ data, they found that students who attended charter schools had scored slightly
lower than other students in their respective public schools while they too were at public schools. While the small disparity in achievement between those who elected to attend charter schools and those in traditional public schools was not significant, in this case the fact that students who attempted to leave their public schools were not higher achieving when they decided to leave disputes the common argument that charter schools "skim" the highest achieving students from public schools.
The results showed a five to six percentile point advantage in reading and a fivepercentile point advantage in math for those students who attended a charter school. This significant advantage was interpreted as a two and a half to three percent yearly gain in achievement on top of what that child would expect to gain in a public school. The five to six point differences represented roughly half the difference in achievement between the average nonminority, middle class student and the minority, economically disadvantaged student. In presenting their findings, the authors stressed that the advantage of attending a charter school applies specifically and exclusively for students who enter between kindergarten and fifth grade. They claimed that studies that look primarily at students who enter charter schools later in middle school or in high school are flawed. They also point out that as the charter school movement ages and expands, enrollment in earlier grades will become more regular. Thus, the benefits of charter schools will become even more pronounced as entries at later grade levels become less common. The study indicates a significant advantage in attending a charter school.
The study by Zimmer and Buddin (2005) is effective in its fairly resounding conclusion. Its main limitation, however, lies in its relatively miniscule sample size. The findings are less likely to carry over to the charter school movement as a whole because
the accomplishments of three charter schools in Chicago do not necessarily reflect the thousands of charter schools across the country. Additionally, the study does not delve deeply into the specific characteristics of the charter schools it features. Despite its small size, particularly in comparison with the larger study by Zimmer and Buddin (2005), the study details little more than a classification of the high expectations and structured curriculum of the three schools. A study that assesses the specific characteristics of unique charter schools would help explain why certain patterns in the correlation between achievement and charter schools emerge.
School Inputs and Charter School Effectiveness in NYC
Dobbie and Fryer (2011) of Harvard University and the National Bureau of Economic Research conducted a study of 35 New York City charter schools (13 middle schools and 22 elementary schools) to determine which “school inputs” correlated with improvements in student achievement. In other words, the researchers sought to identify which teaching methods and school cultures were most effective in improving test scores. In the process, they also determined the efficacy of the charter schools themselves.
The inputs they evaluated through interviews with principals included teacher development, student instructional time, data driven instruction (the degree to which teachers adjusted their curricula to student performance), and parent involvement in the schools. Through teacher interviews and surveys, they evaluated professional development, school policies, school culture, and student assessment. They evaluated the school environment, school disciplinary policy, and the students’ future aspirations through random student interviews and surveys, and used teachers’ lesson plans to
determine the rigor of curriculum. To understand and quantify the degree to which students were focused on their lessons throughout the school day, researchers observed videotaped classes. In addition to the school input information they collected, the researchers gathered student demographic data from the New York Department of Education that included ethnicity, Free and Reduced Lunch eligibility to indicate economic status, and student testing data. The testing data came from the results of New York State standardized tests of math and English Language Arts and was collected for every student that was included in the assessment of the 35 schools.
In evaluating the impact of attending a New York City charter school on a student, the researchers recognized and accounted for selection bias. As similarly performed in the study in Chicago by Hoxby and Rockoff (2005), Dobbie and Fryer (2011) used the NYC charter schools’ lottery system to eliminate the potential confounding variable of a difference in motivation and circumstances between those students who chose to attend charter schools and those who chose to remain in traditional public schools. This method, however, was only possible for 22 of the 35 total charter schools because 13 schools did not require a lottery. To account for selection bias among those students, the researchers identified control students from traditional public schools with similar demographics (Free and Reduced Lunch status, LEP status, ethnicity, and gender) against which to compare the students in the study. Through “matching and regression analysis,” they controlled for variations between the students in the study and their respective similar students in traditional public schools. Thus, the researchers accounted for a substantial portion of the selection bias in those 13 charter schools. They also confirmed that, in the 22 schools that used a lottery-based entrance system, the
researchers’ use of the lottery data to control for selection bias was entirely successful, thus eliminating that particular confounding variable for those 22 schools.
The student population of the 35 charter schools was disproportionately African American in comparison with the NYC public school system. There was, however, an underrepresentation of Limited English Proficiency (LEP) students and special needs students in the charter schools. The rates of eligibility for Free and Reduced Lunch, widely regarded as an indicator of economic disparity, were equal among charter school and public school students in NYC. The charter school students tested lower in math and English Language Arts (ELA) than their counterparts in the city’s public schools. This lower level of baseline achievement, along with an overrepresentation of African American students, strongly indicates the presence of an achievement gap in NYC schools. In this case, however, the gap is between students of different ethnicities and not, as the equal representation of Free and Reduced lunch students shows, between those of different economic status.
Researchers tracked the academic improvements of those students who attended one of the 22 charter schools that performed lotteries for admission alongside the progress of the students who lost in the lotteries and thus returned to their respective public schools. Just as Zimmer and Buddin (2005) did, Dobbie and Fryer (2011) used the lottery losers as a control group against which they measured those who attended one of the 22 charter schools that used a lottery. For the 22 lottery schools, they found improvements in the achievement of the lottery winners after a year in the charter schools in both ELA and math. The researchers calculated that for every year that they attend a charter school, the students would score a small but significant .05 standard deviations
Charter Schools 12 higher than the lottery losers (who were in traditional public schools) in elementary school math and ELA as well as middle school math. The gains in middle school ELA were a virtually insignificant .013 standard deviations in higher scores each year. In the other 13 charter schools examined, those that did not hold lotteries, the advantage of attending a charter school was similarly distributed, although the gains were smaller than those displayed by the students in the lottery-based study. The consensus of the study was that attending a charter school allowed students to improve more each year in math and ELA than he or she would in a traditional public school.
Recall that researchers attempted to identify certain “school inputs” through interviews with principals, teachers, and students, along with analysis of teachers’ lesson plans and observation of videotaped classes. They quantified each input with a specific operational definition that they used in observing each school. For example, one of the inputs assessed was whether or not a school provided high-dosage tutoring. To be classified as providing this level of tutoring, a school must offer small-group tutoring and frequent tutoring, which the researchers defined as tutoring groups of six or fewer and consistent sessions at least four times a week. When they determined that a specific school fell above the median in its use of a certain input, researchers correlated that input with the particular school’s student achievement, thus isolating the effect of a single input through repeating this process.
The most commonly manipulated school inputs at the district, state, and federal level include class size, per pupil expenditure, the portion of teachers with no teaching certification, and the portion of teachers with a master’s degree. Through the described method, researchers determined that varying any of those four inputs either did not
Schools
correlate with a change in student achievement or correlated with a negative impact on achievement. Varying the four variables accounted for between 13.6 and 20.4 percent of the variation in student achievement. This variation, however, was in the negative direction. Five inputs that are more common in educational literature include the use of teacher feedback, the use of data to guide instruction, tutoring, instructional time, and a culture of high expectations. Once again, the researchers quantified each variable with specific operational definitions. After correlating the inputs with student achievement, the researchers found that variation in the five variables correlated with a 50 percent variation in student achievement, and in the expected positive direction. While the study details the correlation between each input and achievement, the researchers also calculated that increasing an index of all five of the variables by one standard deviation correlated with a .056 standard deviations increase in yearly math improvement and .039 increase in yearly ELA improvement.
Dobbie and Fryer (2011) recognized a limitation of their work as the inability to assign cause to the correlations between the school inputs and achievement. While they discovered significant relationships, it was possible, they noted, that other less observable factors such as principal talent or parent engagement caused the correlations. Where Dobbie and Fryer (2011) shine, however, is in their quantification of seemingly objective educational methods and school philosophies. In addition to controlling for selection bias, they systematically isolated the correlation between individual school inputs and achievement. They present quantified data that suggests not only that the charter schools they studied were effective in improving the gains of their disadvantaged students, but also that specific methods were largely responsible for the successes.
Comparative Analysis
Zimmer and Buddin (2005), Hoxby and Rockoff (2005), and Dobbie and Fryer (2011) tackled the effectiveness of charter schools in areas with low-income, minority students. All three studies recognized and addressed the confounding variable of selection bias that arises in comparisons between charter schools and traditional public schools. However, Zimmer and Buddin (2005) went about neutralizing the bias differently than the other two groups of researchers, both of which took advantage of lottery-based enrollment to create a control group to account for the bias. Zimmer and Buddin (2005) longitudinally tracked individual student progress over five years in order to evaluate only the change in achievement and account for selection bias. While there is no explicit evidence that favors the accuracy of one method over the other, the longitudinal, individual-progress method of Zimmer and Buddin (2005) leaves room for the possibility that an individual student could not only be different from other students in his or her baseline achievement, but in the ability to improve as well. Although Dobbie and Fryer (2011) were only able to use the lottery-based method of controlling for selection bias for 22 of their 35 charter schools, they recognized and accounted for their less-precise estimations for the remaining schools. Future research that compares charter school students to traditional public school students would be wise to utilize a lottery-based admission system in the charter schools to account for selection bias if possible. If not, Dobbie and Fryer’s (2011) secondary method of finding controls with similar demographics or Zimmer and Buddin’s (2005) method of individual, longitudinal analysis could serve as reasonable alternatives.
Hoxby and Rockoff (2005) used only three Chicago charter schools for evidence and found that they had a significant, consistently positive impact on achievement. The low socioeconomic status of a large percentage of the students in these charter schools indicates that these charter schools do indeed make gains in closing the achievement gap. The consistency of this minority representation with the minority population in neighboring public schools is unique to the study and suggests that, given roughly the same percentage of minority students, the charter schools make greater gains in achievement than do traditional public schools.
On the other hand, the study in Southern California by Zimmer and Buddin (2005) depicts a different version of the charter school movement. The researchers examined thousands of charter schools in SDUSD and LAUSD to incur a massive sample size (over 34,000 students) to which the study in Chicago pales in comparison. The representation of minority students in charters does not align with the group’s representation in the districts’ public schools. The larger minority population in those districts, the Hispanic population, is underrepresented in LAUSD charter schools and SDUSD charter schools while African Americans were overrepresented. The study found that the achievement gains made by the charter schools are not markedly different from those made by public schools. Thus, in stark contrast with the study by Hoxby and Rockoff (2005) in Chicago, Zimmer and Buddin (2005) found that the examined charter schools do not close the achievement gap any more effectively than the traditional public schools in the same districts. In fact, the underrepresentation of a large minority group suggested that they do not explicitly address the achievement gap. While Zimmer and Buddin (2005) were not able to deal with the issue of selection bias as handily as the
other two studies, their advantage in the size of their study bolsters the argument that charter schools are no more effective in closing the achievement gap than their traditional public school counterparts. While the disproportionately minority students who enrolled in NYC charter schools scored lower than their public school counterparts, indicating an achievement gap, their improvement gains were greater in the charter schools. With a sample size of 35 charter schools, markedly smaller than that of the study in LAUSD and SDUSD but larger than the sample of the study in Chicago, Dobbie and Fryer (2011) found a significant, exponentially improving impact of charter schools on student achievement. The sample matched the public school system in the percentage of economically disadvantaged students and held an overrepresentation of African American students.
The three studies depict conflicting realities of the charter school movement’s effort to close the achievement gap. The study by Zimmer and Buddin (2005), the large sample size of which indicates that it is the most replicable, suggests a gloomy picture for charter schools, claiming they are not any more effective than public schools. To determine whether any of the studies outlined here are inaccurate or if the charter schools in Chicago and New York City are simply more effective in out-gaining their districts’ public schools requires future research. Such research would ideally be on a large enough scale to suggest trends in the charter school movement as a whole. Future studies must also account for the contention of Hoxby and Rockoff (2005) that students who enter charter schools after early elementary years receive less benefit per year than those who entered earlier. Neither the study by Zimmer and Buddin (2005) nor the study by Dobbie and Fryer (2011) acknowledged this potential confounding variable.
Dobbie and Fryer (2011) presented a potentially significant step forward in the charter school movement by identifying which school inputs are most effective in improving student achievement in a district with poor, disproportionately minority students. This accomplishment reveals that the most effective charter schools, in this review the three in Chicago and those in NYC, may differ from their public school counterparts in their manipulation of “key inputs.” The study identified teacher feedback, data-driven instruction, more instructional time, high-dosage tutoring, and a concentration on academic progress as the most significant. Just as importantly, the study identifies many traditionally manipulated inputs that have either no correlation or a negative one with changes in student achievement. While the literature as a whole presents conflicting findings regarding the ability of charter schools to close the achievement gap, it also reveals openings for further research. Investigating the effects of the school inputs identified by Dobbie and Fryer (2011) on other charter school samples is worthy of further research.
Charter School Case Studies
To pursue a more in depth understanding of the relationship between the five school inputs identified by Dobbie and Fryer (2011) and charter school achievement, the author interviewed three charter school leaders in the Bay Area of Northern California. In addition to general commentary on charter school advantages and disadvantages, all three were asked to describe how their respective charter schools or Charter Management Organizations utilize the five inputs from Dobbie and Fryer (2011): frequent teacher feedback, the use of data to guide instruction, high-dosage tutoring, increased instructional time, and a culture of high expectations. Alongside detailed interview
Charter Schools 18 information that characterized the respective charter schools’ based on the five school inputs, state testing and school ranking data was collected. Using the California Department of Education’s testing database known as DataQuest, each school’s 2010 or 2011 California Standardized Testing results (CST) were gathered based on which year provided the most complete data. The schools’ respective API ratings for 2010-2011 and their 2010 Similar Schools Ranking were also collected.
The California Department of Education (CDE) provides a Similar Schools Rank that places each school among 100 others that are most similar in terms of the student demographic that includes student socioeconomic status and 12 other characteristics. The 100 schools are split into ten groups of ten based on API score where 10 is the highest and one is the lowest. In other words, the top ten schools in API performance all receive a rank of 10 on the Similar Schools Rank, the next ten receive a rank of nine, and so forth.
In assigning numerical value to the average level of parent education, schools are ranked on a five-point scale. On the scale, one represents “not a high school graduate” and five represents “graduate school” (California Department of Education, 2011).
One of the three school leaders was Mrs. Paige Cisewski, the Principal of the Charter School of Morgan Hill (CSMH). CSMH is a K-8 (kindergarten through eighth grade) school that opened in 2001 and focuses on project-based learning (PBL) and community involvement to educate its students for future success. When asked to describe the school’s culture, the principal cited the school’s signature practices of teaching outside the core subjects, including foreign language, art, physical education, science, and social studies (P. Cisewski, personal communication, March 21, 2012). She also described the importance of mutual respect within the community and educating
Schools 19 responsible individuals with the help of a YMCA initiative called Project Cornerstone.
Providing a context of the makeup of the students, 3.8% of the student body was classified as economically disadvantaged in the 2010-2011 school year and slightly fewer than 25 percent were Hispanic or African American. With one representing “not a high school graduate” and five representing “graduate school”, the school’s average parent education level was 4.10. (CDE, 2011)
The Principal of CSMH was asked to describe both informal and formal feedback that the school’s teachers receive throughout the year. The formal feedback includes oneon-one meetings between each teacher and the principal three times per year and a monthly collaboration of the entire staff to critique the teachers of each grade level at least once a year in their PBL implementation. Informal feedback is more frequent and includes the principal spending at least one day a week visiting classrooms to provide instant feedback, multiple venues for teachers to collaborate with each other and with teachers from other schools, and discussion of student interviews and a yearly parent survey (P. Cisewski, personal communication, March 21, 2012).
The principal was also asked to describe the school’s use of data to guide instruction and the degree to which tutoring occurs. In addition to all state standardized tests, CSMH implements its own tests that partially aim to identify “target” students who are behind grade level. Such tests include a diagnostic reading assessment for grades K-4 and multiple benchmark tests in math within the school and through collaboration with the Silicon Valley Math Institute. Teachers of the same subject meet twice a week to discuss discrepancies in student achievement and adjust teaching methods accordingly. Intervention for “target” students reflects the bulk of the tutoring that CSMH students
Charter Schools 20 receive. Such attention includes one-on-one weekly tutoring with trained community volunteers during the year and a two-week intervention before the school year for some “target” students to receive help in small groups in reading and math. Although it is not classified as tutoring, students do individualized work with online math programs for about an hour a week at home (P. Cisewski, personal communication, March 21, 2012). Additionally, the school’s total instructional time in minutes for the 2010-2011 school year far exceeded the California Department of Education’s requirement.
The 2011 California Standardized Test (STAR) classified the following percentages of CSMH students in grades two through eight as proficient or advanced (at least proficient) in the given subjects: 81.79% in English Language Arts (ELA), 75.33% in Math, 91.26% in Science, and 71.17% in History (CDE, 2011). CSMH received a score of 901 on California’s Academic Performance Index (API) in 2011, an increase of 14 points from its 2010 score of 887 (CDE, 2010-2011). CSMH received a rank of 4 on the 2010 Similar Schools Rank (CDE, 2010-2011).
Another school leader who provided information about a local charter school was Ms. Kia Darling-Hammond. She tracks program assessment and effectiveness as the Associate Director of Special Programs at Stanford New Schools’ East Palo Alto Academy-High School. Stanford New Schools, a Charter Management Organization that works in conjunction with the Stanford School of Education, began operating the high school in the 2010-2011 school year. It also, however, operated a kindergarten-througheighth-grade school between 2006 and 2010 known as East Palo Alto Middle School. The middle school’s charter with the Ravenswood school district was not renewed in 2010 and Stanford New Schools now exclusively runs the high school (Stanford New Schools,
2010). Over 86% of East Palo Alto Academy high school students learned a language other than English first and 64% were classified as English Language learners in 2011 with the differing 22% having been “re-designated” in past years as at least English proficient (K. Darling-Hammond, personal communication, April 2, 2012) (CDE, 2011).
According to CDE’s CST demographics, 89% of the school’s students were either Hispanic or African American when the standardized tests were implemented in 2011.
The same source classified 99% of the school’s students as economically disadvantaged (CDE, 2011). The school also has one of the highest incidences of low-education-levels in its parent population. (K. Darling-Hammond, personal communication, April 2, 2012)
The school’s average parent education level was 1.77 on the one-through-five scale (CDE, 2011).
Regarding the culture of Stanford New Schools, Ms. Darling-Hammond cited the five habits that the school works to instill in its students: personal responsibility, social responsibility, application of knowledge, critical and creative thinking, and communication. The school uses an advisory system with a 15:1 ratio and the same students and teacher through all four years that meet four times a week to implement its basic cultural expectations of students. Ms. Darling-Hammond cited student interviews in which students credit advisories for academic improvements and state that teachers believe in them and expect them to do well (K. Darling-Hammond, personal communication, April 2, 2012).
Teacher feedback at Stanford New schools includes two cycles of observation, each with two meetings between a teacher and the principal or vice principal. Informal observations and subsequent feedback by the principal or vice principal occur every few
Charter Schools 22 weeks. Additionally, an informal teacher mentorship program is in place in which experienced teachers pair with newer ones to critique and assist them. The school conducts a yearly survey of parents, students, teachers, and staff and reviews the results with the entire school staff (K. Darling-Hammond, personal communication, April 2, 2012).
Teachers at Stanford New Schools use the California Standardized testing data (STAR) of their students’ previous year to shape their curriculum for the coming school year. The school administers English proficiency tests for its English Learner students and the teachers use that data as well in the middle of the school year to adjust their lesson plans. Stanford New Schools implements strategies of SDAIE (Specifically Designed Academic Instruction in English) to integrate English language learning into all other subjects. The school tests some of its students up to three times a year with the NWEA’s Measure of Academic Progress (MAP) that produces similar results to a standardized test before the students take California’s standardized tests. However, the test is administered at the discretion of individual teachers and is not a school standard.
The school contracts with Tutorpedia, an outside tutoring company that works one-onone with some struggling students during the day and after school. The school offers optional extended learning four days a week after school for students who want extra help on school material. In addition, the normal school day at East Palo Alto Academy is from 8:00 AM to 3:15 PM with weekly minimum days (K. Darling-Hammond, personal communication, April 2, 2012). With roughly 180 school days in the year (standard number in the state), East Palo Alto Academy exceeds California’s requirement for total instructional time.
The 2010 California Standardized Test (STAR) classified the following percentages of Stanford New Schools students in grades nine through twelve as proficient or advanced (at least proficient) in the given subjects: 23.4% in English Language Arts and 22.2% in Math. 10th graders were tested in Science and 17.2% were proficient or advanced, but that number dropped to 4.8% for the end-of-course test. 11th graders were tested in History and 8.1% were proficient or advanced (CDE, 2011). Stanford New Schools received a score of 603 on the 2011 API, a decrease of 17 points from its score of 620 in 2010 (CDE, 2010-2011). Where 10 is the highest and 1 is the lowest, it received a rank of 6 in the 2010 Similar School Rank (CDE, 2010-2011).
The third school leader who participated in interviews was Preston Smith, the Cofounder and Chief Achievement Officer of Rocketship Education. Rocketship Education is a Charter Management Organization that was founded in 2006 and has since opened five charter schools in and around San Jose, California. It holds charter agreements for over 30 new schools in California and other states as it plans to aggressively expand over the next several years. The non-profit organization strives to close the achievement gap by serving students in predominantly high-poverty neighborhoods (Rocketship Education, 2012). Of the five currently operating schools, two are old enough to have a record of results and have full testing data displayed on the CST database. In 2011, Rocketship Mateo Sheedy Elementary had a student body of which 93% were economically disadvantaged and 93% were Hispanic (1% African American). Using the same 1-5 scale for parental education, the average education level of Mateo Sheedy parents was 2.15. At Rocketship Si Se Puede Academy, 89% of students were economically disadvantaged and 86% were Hispanic (0% African American). The
Charter Schools 24 average parental education level at Si Se Puede was 2.22 (CDE, 2011).
When asked to describe the culture of expectations at Rocketship Schools, Mr. Smith cited standardized discipline and rules that are consistent throughout every school. Disciplinary action within every classroom uses the same color chart to create even expectations. The students wear uniforms (they “dress for success”) and keep their shirts tucked in at all times. They are constantly reminded of four basic expectations of how to behave during class: listen attentively, sit upright, track the teacher visually, and maintain respectful posture. Overall, students learn to display respect for peers and teachers in a fashion that will carry them past elementary and middle school (P. Smith, personal communication, April 6, 2012).
Teachers at Rocketship schools undergo a weekly “intensive coaching experience” in which the school dean or principal observes a class and gives real-time feedback to the teacher via an earpiece in addition to feedback after the session.
Struggling teachers may receive this feedback multiple times in a week. Through their use of a rotational block schedule in which there are always roughly one fourth of the students of a grade in the computer “learning lab,” Rocketship schools cut the number of credentialed teachers they would employ based on their number of students and low student to teacher ratio by roughly one fourth. The resulting freedom in funding allows them to higher a full-time dean for each school who focuses primarily on teacher feedback and development. The schools undergo eight-week cycles in which teachers and administrators set student achievement goals in certain focus areas where students are struggling, implement new strategies if needed, measure student progress, and assess the results. All students receive individualized skill development with online programs such
as Dreambox Learning and Ten Marks in math during daily “learning lab” periods.
Because Rocketship uses the Response to Intervention (RTI) model that stresses frequent testing, and providing frequent assistance to students who struggle in specific areas, about 25% of the students receive daily tutoring in specific areas where they struggle and 75% receive no tutoring. Additionally, Rocketship schools observe roughly 180 school days that, with the exception of kindergarteners, last from 8:00 AM to 4:00 PM. As the state observes Rocketship instructional time, they are slightly over California’s requirement. However, this calculation does not include daily “learning lab” time that, if factored in, would push total instructional time at Rocketship schools far above the requirement of instructional time (P. Smith, personal communication, April 6, 2012).
The 2010 California Standardized Test (STAR) classified the following percentages of Rocketship Si Se Puede Academy’s students as proficient or advanced (at least proficient) in English Language Arts: 69% in grade two, 45% in grade three, 60% in grade four. For Math: 87% in grade two, 76% in grades three and four. No data was available in History or Science. The following percentages of students at Rocketship Mateo Sheedy Elementary were proficient or advanced in English Language Arts: 83% in grade two, 72% in grade three, 75% in grade four, 85% in grade five. In Math: 90% in grade two, 93% in grade three, 93% in grade four, 92% in grade five. 69% of fifth graders were proficient or above in Science and no data was available for other grades or in History (CDE, 2011). Rocketship Si Se Puede Academy received an API rating of 886 in 2010 and 859 in 2011, a decline of 27 points between the two years (CDE, 20102011). The school’s 2010 Similar Schools Rank was 10, the highest ranking possible (CDE, 2010-2011). Rocketship Mateo Sheedy received an API rating of 925 in 2010 and
892 in 2011, a 33-point decrease (CDE, 2010-2011). Mateo Sheedy’s 2010 Similar Schools Rank was also 10 (CDE, 2010-2011).
Case Study Analysis and Conclusion
The aim of the data collection was to examine the connection between the level of implementation of the five key school inputs and CST results, API rating, and Similar Schools Ranking. In interviews in which school leaders were asked to describe if and how their school(s) implements each of the five inputs, all three described steps that their respective schools take in regard to the five inputs. The three differed greatly in their specific methods of, for example, formal and informal teacher feedback, the use of data to guide instruction, and tutoring. All, however, described ways that their schools address those inputs. Nevertheless, among different student demographics and student grade levels, testing results varied hugely between the schools. Thus, it was impossible to perfectly isolate the five inputs and determine their direct relation to achievement.
The drastic variation in CST scores between the three organizations (four schools) speaks to a multitude of factors. The most obvious difference between the schools was the makeup of their student bodies in terms of economic status, minority status, and parental education levels. There was a relationship between high incidences of economically disadvantaged students, minority students, and low parental education and lower test performance. Additionally, Stanford New Schools’ East Palo Alto Academy is a high school while CSMH and Rocketship schools are elementary and middle schools.
While the data on student achievement as it correlates with the charter school movement is not conclusive, the emergence of specific educational methods from charter
schools that could revolutionize all types of schools bodes well for the future of the movement as it works to create educational excellence and equity. While the case study of CSMH, Stanford New Schools, and Rocketship Education did not conclusively validate the claims by Dobby and Fryer (2011), it reveals opportunity for future research. Such investigations should focus more on comparing students and schools of similar demographics rather than exclusively on universal testing results. The 2010 Similar Schools Ranking, for example, provided helpful insight into the success of each charter school in educating the demographic that makes up their school. That both Rocketship schools received the top rating on the 2010 Similar Schools Ranking implies that Rocketship Education is taking a step toward a replicable model of successfully educating the most socioeconomically disadvantaged students. The relatively lower scores of CSMH and Stanford New Schools on the 2010 Similar School Ranking suggest that the two have more room for growth and improvement of tests scores within their respective student demographics. Further research should seek to identify which schools perform the best in their respective student demographics. Continuing with the model of the study by Dobbie and Fryer (2011) and perhaps using the five “key inputs” they identified, such research should then attempt to understand what specific educational methods of the most successful schools allow them to defy any seemingly disadvantageous demographic.
Further research could help fulfill a common contention of charter school advocates who claim that charter schools can act as incubators for new educational methods that can then be applied in all types of schools, including traditional public schools. Most importantly, researchers should investigate how to replicate the most
effective charter schools and their methods are on a larger scale. While Rocketship Education is an example of a remarkably successful Charter Management Organization with many socioeconomically disadvantaged students, its five charter schools are not yet conclusive evidence that it can be consistently replicated. Rocketship Education’s plans to open eight new schools within five years and increasingly more after that will test their ability to duplicate past success. Such aggressive expansion of successful methods, in addition to further research into effective schools, will determine whether educators can implement innovations that charter schools develop. Such research will contribute evidence to the debate of whether charter schools incubate innovation that carries beyond the schools themselves.
References
Dobbie, W., & Fryer, R. G., Jr. (2011, November). Getting beneath the veil of effective schools: Evidence from New York City. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w17632
Herington, C. D., & Harris, D. N. (2006). Accountability, standards, and the growing achievement gap: lessons from the past half-century . American Journal of Education, 112(2), 209-238. Retrieved from http://scholar.google.com/scholar_url?hl=en&q=http://eps.education.wisc.edu/ Faculty%2520papers/Harris/
Harris%2520Herrington%2520Ach%2520Gap%2520AJE.doc&sa=X&scisig=AAGBf m0m8IbaKEnr3KN
NYZznBTwPkpEACw&oi=scholar
Hoxby, C., & Rockoff, J. (2005, Fall). Findings from the city of big shoulders. Education Next, 52-58. Retrieved from http://educationnext.org/files/ ednext20054_52.pdf
Zimmer, R., & Buddin, R. (2005, July). Charter school performance in urban districts: Are they closing the achievement gap? RAND Education. Retrieved from http://www.ncspe.org/publications_files/OP118.pdf
About us. (n.d.). Retrieved from Charter School of Morgan Hill website:
Charter Schools 30 http://www.csmh.org/about/index.html
About Stanford New Schools. (n.d.). Retrieved from Stanford New Schools website: http://www.stanfordnewschools.org/stanford-new-schools/sns
Our story. (n.d.). Retrieved from Rocketship Education website: http://rsed.org/ index.php?page=our-story
2010 STAR Test Results. Retrieved from California Department of Education website: http://star.cde.ca.gov/star2010/Index.asp
2010-2011 Accountability Progress Reporting. Retrieved from California Department of Education website: http://www.cde.ca.gov/ta/ac/ap/apireports.asp