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Volume 14, Number 1                            ISSN 1099-839X 
 

 
An Analysis of High School Transformation  

Effort from an Outcome Perspective 

Hea-Jin Lee 

Ohio State University at Lima 

S. Aslı Özgün-Koca 

Wayne State University 

Dean Cristol 

Ohio State University at Lima 

 
 
Citation 

Lee, H., Özgün-Koca, S., & Cristol, D. (2011). An Analysis of High School Transformation 
Effort from an Outcome Perspective. Current Issues in Education, 14(1). Retrieved from  

 http://cie.asu.edu/ojs/index.php/cieatasu/article/view/ 
 

Abstract 

This study investigates the effectiveness of the Ohio High School Transformation Initiative using 

several years of state data on attendance, graduation, dropout rates, and performance index 

scores. Results indicate differences between small schools or small learning communities, and 

traditional schools that have similar school profiles to small schools in: graduation rates by year; 

attendance rates among the traditional schools over the years; and the performance index scores.  



Current Issues in Education Vol. 14 No. 1 2 
 
Small schools’ performance index scores gradually increased, but traditional schools with similar 

school profiles outperformed small schools. There was no difference in the dropout rates.  

Creating a sense of community, rather than simply transforming the school structure, seems to be 

the key to improving high school education. 

 
Keywords: secondary education; Small Schools; OHSTI; attendance rates; graduation rates; 

dropout rates; performance index scores 
 
 
 
 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  3 
 
About the Author(s) 

Author: Hea-Jin Lee 

Affiliation: Ohio State University at Lima 

Address: College of Education and Human Ecology, Ohio State University, Lima, OH, 45804 

Email: lee.1129@osu.edu 

Biographical information:  Dr. Hea-Jin Lee is an Associate Professor of Mathematics Education 

at the Ohio State University-Lima.  Her research interests include improving reflective thinking 

and practice, assessing professional growth, designing teacher-needs based professional 

development programs, and teaching mathematics to children at various levels. 

 

Author: S. Aslı Özgün-Koca 

Affiliation: Wayne State University 

Address: College of Education, Wayne State University, Detroit, MI, 48202 

Email: aokoca@wayne.edu 

Biographical information:  Dr. S. Aslı Özgün-Koca is currently an Assistant Professor in the 

Mathematics Education Program area under the Teacher Education Department at Wayne State 

University. She teaches mathematics and secondary mathematics education courses. Her main 

research interest is the use of technology in mathematics education. Her research with preservice 

teachers earned an Outstanding Paper Award in Mathematics Education from the International 

Conference of the Society for Information Technology and Teacher Education in 2008. 

 

 

 



Current Issues in Education Vol. 14 No. 1 4 
 
Author: Dean Cristol 

Affiliation: Ohio State University at Lima 

Address: College of Education and Human Ecology, Ohio State University, Lima, OH, 45804 

Email: cristol.2@osu.edu 

Biographical information:  Dr. Dean Cristol is an Associate Professor at the Ohio State 

University-Lima Campus. His research areas are university-school partnerships, professional 

development and utilizing instructional technology in PK-12 classrooms.  He recently secured a 

National Science Foundation grant focusing on STEM careers for high school students in Ohio 

and North Carolina. 

 

 

 

 

 

 

 

 

 

 

 

 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  5 
 

An Analysis of High School Transformation Effort from an Outcome Perspective 

In 2003, the KnowledgeWorks Foundation, along with the Bill & Melinda Gates 

Foundation, the Ohio and U.S. Departments of Education, the Ford Foundation, the Kellogg 

Foundation, and local community-based foundations established the Ohio High School 

Transformation Initiative (OHSTI). This school improvement effort focused on transforming 

Ohio’s ineffective large urban high school model into a model that promoted smaller learning 

communities by diminishing school size and by addressing “rising high school dropout rates, 

declining scores on the state student achievement exams, and increased problems with school 

violence and truancy” (KnowledgeWorks Foundation, 2009, p. 3). The Ohio State Board of 

Education (ODE, 2004) proposed that a key measure for educational success would be an 

increase in the graduation rates for all students, in all demographic groups, and an increase in the 

percentage of students who advance with their cohort group from eighth grade to graduation. 

The Western Interstate Commission for Higher Education (2008) reported that the U.S. 

was heading toward an overall decline in the number of high school graduates. The report 

predicted that the number of graduates in the Midwest would continue to increase until 2007-08 

then face a dramatic decline that will ultimately see the region’s number of graduates fall by 

eight percent by 2014-15. The report concluded that Ohio can expect large decreases in 

graduation rates by 2021-22 (relative to 2004-05), which will result in almost 16,000 fewer 

public high school graduates. 

In this study, we investigate the effectiveness of the small schools concept from an 

outcome perspective. Because the concept became a transformative model for many urban high 

schools in Ohio, we were curious about the initiative’s effect on school characteristics: 

graduation rates, attendance rates, performance index scores, and dropout rates. The purpose of 



Current Issues in Education Vol. 14 No. 1 6 
 
the study is to analyze the Ohio Department of Education’s data to see if the initiative had an 

effect in these areas, when compared to similar high schools that remained large.  The research 

questions for this study are: 

1.  Did the transformation of a school from a large urban school to small learning 

communities have an effect on graduation rates, attendance rates, dropout rates, and 

performance rates? 

2. Did the transformation of a school from a large urban school to small learning 

communities have an effect on graduation rates, attendance rates, dropout rates, and 

performance rates when compared to similar schools that remained traditional? 

 
School Characteristics that Measure Success 

School Size 

Several studies report that small schools attain: higher achievement (Lee, 2000; Lee & 

Smith, 1997; Wasley, Fine, Gladden, Holland, King, Mosak, & Powell, 2000; Wyse, Keesler & 

Schneider, 2008), lower dropout rates (Kahne, Sporte, de la Torre, & Easton, 2008; Toch, 2003), 

higher graduation rates (Wasley et al., 2000), and even a higher likelihood of student enrollment 

in higher education (Schneider, Wyse, & Keesler, 2007). High school students, especially those 

who are considered at greater risk, fare much better in small schools: “the effect of increasing the 

size of high schools, it seems as though there is reduced individual participation in school 

activities, decreased attendance, and less expressed satisfaction with school” (Pittman & 

Haughwout, 1987, p. 338). Students attending small schools are reported to be doing better, 

because the learning experience that is offered is more authentic and relevant to the student. 

Many small learning communities focus on the continued success of each student, especially 

those learners who seem neglected by the typical large school environment. In a small learning 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  7 
 
community, every student is a significant member of the school; in the large schools, many 

disadvantaged students sense that teachers and staff lack concern for their well-being and 

learning (Ark, 2002; Crane, 2002; House, 2007). The small school concept stresses a supportive 

community where students receive individualized help and attention from their teachers. By 

making schools smaller, the goal is to create a better teaching and learning environment, as well 

as a caring community within the schools. Soon after a district has changed to small schools, a 

common manifestation is that achievement gaps among all students appear to be bridged (Ark, 

2002; Crane, 2002; House, 2007; Keller, 2001; Raywid, 1998, 2002). 

Smaller school environments allow for improved safety and increased support for 

students and staff (Association for Supervision and Curriculum Development, 2000). Small 

learning environments commonly create the possibility of closer collaboration among teachers, 

which contributes to a collaborative school community (Duke & Trautvetter, 2001; Strull, 2002). 

“Teachers could develop better connections between home and school, better understand 

students’ strengths and weaknesses, provide better support for both, and learn more from each 

other, creating a more exciting and vibrant career” (Wasley et al., 2000, p. 10). Perhaps it is not 

only due to the size of a small school and its classes, but rather to the greater involvement of 

students, teachers, staff and parents, that yields a more pronounced sense of community where 

all affected groups work together in the interest of their learning community. Students tend to 

feel more connected to their teachers and peers when they are in a small school. Overall, 

attending a small school at any grade level appears to reap greater rewards for students than the 

larger schools, regardless of social class or minority status (Driscoll, 2003; Metzger, 2006; 

Sackney, Leonard, & Leonard, 2001). 



Current Issues in Education Vol. 14 No. 1 8 
 

It has been shown that converting a large school into a small school has some 

disadvantages. With a limited number of faculty, a small school may not be able to offer an 

extensive selection of courses. Also, as more large high schools become small schools, some 

schools become small only physically, but retain the same philosophy of teaching and learning 

found in the large school. They do not adopt the small school principles described earlier in the 

paper (Gregory, 2000; Myatt, 2005). 

In summary, school size seems to have an impact on some school related issues, such as 

performance, dropout rates, attendance, and behavioral issues. Students feel that their needs and 

accomplishments are better recognized, which leads them to higher achievement. Although there 

may be more opportunities for extracurricular activities in larger schools, more students are 

involved and participate in more activities in small schools. Small schools seem to benefit 

students in numerous ways, from greater engagement in learning and activities to a higher level 

of parent involvement (Iatarola, Schwartz, Stiefel, & Chellman, 2008). 

Dropout and Graduation Rates 

The reporting of dropout rates for high schools varies greatly within the research 

literature.  The variation in dropout rate data is due to differences in the ways data is collected 

and reported. For example, some researchers count students who move back and forth between 

multiple school systems, while other researchers use the rate of enrollment, instead of the actual 

number of students attending the school (Bracey, 2009; Mishel & Roy, 2006; Stanard, 2003). 

The graduation rates in many school districts have been steadily improving for several decades, 

especially among minority groups. Some discrepancies arise from overgeneralization of 

categories, which yields rates that are higher than actual, especially in inner city schools. A cause 

of high dropout rates, one that could be more easily focused on, if not rectified, is the lack of 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  9 
 
community involvement in the schools. Some students drop out because their families do not 

value education. Others leave school early, because the available school options are just too 

limited. Some researchers maintain that if these issues were more seriously addressed, the 

graduation rate would improve (Alliance for Excellent Education, 2008a). 

Attendance Rates 

Students in larger schools are more likely to commit truancy and miss more days than 

students who attend small schools. Research shows that the small schools have a greater impact 

on student engagement, parent involvement, and attendance (Roby, 2004, The National Forum, 

2004). A deficiency with the research that examines attendance rates is that they do not account 

for excused absences, which yields inaccurate data (Greene & Winters, 2002). Some research 

shows that the more students miss school, the more they do not want to be there at all, 

“Excessive absenteeism influences the student’s desire to return to school” (News Briefs, 2006, 

p. 6). 

Performance Index Scores 

Some schools require a high school exit exam, while others require that students pass 

standards-based exams at a tenth grade level or higher. The number of schools with this 

requirement has greatly increased in the past few years. Emphasis is also being placed on factors 

considered by college admissions offices, such as grade point average, Scholastic Aptitude Tests 

scores, American College Testing scores, class rankings, and classes taken, so that students will 

be considered “college ready” at graduation. Some advanced courses are required to get into 

certain colleges, while some colleges consider how many years of each subject a student has 

taken during their high school academic career (Alliance for Excellent Education, 2008b; Greene 

& Forster, 2003; Louvouezo, 2008). 



Current Issues in Education Vol. 14 No. 1 10 
 

The importance of what content should be addressed in high school is an issue that is 

constantly changing and discussed among policy leaders and educators. This leads us to believe 

that some form of action must be taken regarding how and what students are being taught, if it is 

leading them to perform poorly on tests related to the content that students are struggling to 

master (Cavanagh, 2009; Manzo, 2009). 

Students who do not perform well academically tend to give up and eventually drop out 

of school. Some research demonstrates that students who are alienated in school often feel their 

absence goes unnoticed. Many students who dropped out said that they felt school did not relate 

to real-life situations and was therefore irrelevant. If they had been more interested in what they 

were learning and had felt it was relevant, they might have remained in school and possibly 

achieved at higher rates. Engaging the students is the key to academic motivation and success 

(National Academy of Sciences, 2003). 

Potentially, socioeconomic segregation could also be a factor in the large achievement 

gap between minority and white students. Much of the research demonstrates that a student’s 

family background and socioeconomic status (SES) play a much more significant role in 

achievement levels than does anything directly related to the school itself (Konstantopoulos, 

2006, Mickelson & Borman, 2007; Rumberger & Palardy, 2005). 

Method 

The study focused on the effects of small schools in Ohio on graduation rates, attendance 

rates, dropout rates and performance index rating scores. The data from the small schools were 

compared to traditional schools that are identified as similar to the small schools by the Ohio 

Department of Education.  Graduation rates, attendance rates, and dropout rates are based on the 

data reported by each school to the state, and performance index rating scores are based on the 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  11 
 
state standardized tests scores.  The data used in this study are produced by the state, and our 

research team was unable to collect descriptive information how each school calculated their 

graduation rates, attendance rates, and dropout rates. 

Data Collection 

Data were collected from more than 230 Ohio schools, from 2003 – 2007: between 30 – 

35 schools from 14 districts were identified as small school by KnowledgeWorks; and 

approximately 200 schools were identified as similar to small schools by the Ohio Department of 

Education (ODE). Our reason for collecting data from these schools during these school years 

was to align with the data included in the report on the effectiveness of the small schools 

released in January 2009 by the KnowledgeWorks Foundation. 

The KnowledgeWorks Foundation collaborated with the Bill & Melinda Gates 

Foundation and other partners, to create the Ohio High School Transformation Initiative 

(OHSTI), a model to transform large urban low performing high schools to small learning 

communities. The OHSTI model defined a large school as at or above 800 students, while small 

schools or small learning communities are approximately 100 students per grade level, or 400 

students within the learning community (KnowledgeWorks Foundation, 2009). The OHSTI 

model was designed according to the following criteria developed by the KnowledgeWorks 

Foundation (2009): 

• existing campuses have been divided into independent schools of no more than 400 

students;  

• each school has its own area of focus such as business or creative arts, or a curriculum 

model; 



Current Issues in Education Vol. 14 No. 1 12 
 

• each school has its own shared leadership model consisting of administrators and 

teachers; 

• a standards-based curriculum is combined with new teaching methods, such as real-world 

connections, longer class periods, project-based learning and cross-curricular study; and 

• close working relationships between teachers and students, such as teachers working as 

student advisers (Ohio Education Matters, 2009). 

The ODE website allows researchers to extract data that pertains to specific schools in 

Ohio. The site allows the data to be compared to similar schools through a process designed by 

ODE. The similar school district comparison methodology data evaluates performance data for a 

school district. When a school is identified, the site finds up to 20 districts that are most similar 

according to certain criteria. Statistically, the comparable districts are considered the nearest 

neighbors of the selected district. ODE maintains that a “consistent and objective method of 

determining similar districts has been established, and within that framework, comparison 

groupings have been tailored to each individual district. Each district’s characteristics drive the 

creation of the comparison groupings, and each district’s set of "peers" is developed with only 

that district’s characteristics in mind. Every district thus has its own unique set of peers” (ODE, 

2010, http://webapp2.ode.state.oh.us/similar_districts/). 

ODE produced a set of 11 descriptors to differentiate districts; four stand alone, and 

seven are included in two composite measures. Composite measures were used for dimensions 

where there is no valid data element used to describe the dimension. “Tests for relationships 

between data elements were conducted with each variable prior to the analysis of dimensions. 

Data representing each dimension were normalized prior to the analysis, with means equal to 

zero and standard deviations of 1. This process standardized the metric used for comparative 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  13 
 
purposes so that each district can be fairly compared with any other district. The data used for 

each dimension represent a set of descriptive background characteristics that distinguish one 

district from another. These single or composite variables create the six dimensions used to 

determine a district’s comparison grouping: district size, poverty, socioeconomic status, 

rural/urban composite, race/ethnicity, and non-agricultural” (ODE, 2010, 

http://webapp2.ode.state.oh.us/similar_districts/). 

The similar school process works by identifying a district which is compared to 609 other 

districts by performing a collective comparison across all dimensions. The formula for each 

district-to-district comparison can be found at http://webapp2.ode.state.oh.us/similar_districts/. 

The comparison groupings are those districts that are most similar to the initial district. For most 

districts, there are 20 similar districts, but some large urban and unique districts have a minimal 

number of comparatively similar districts. ODE recognized that there are limitations to this 

methodology: (1) no geographical dimension; (2) arbitrarily setting a minimum of 6 and 

maximum of 20 comparison districts; (3) comparison groupings can produce counter-intuitive 

results for inter-grouping comparison cases; (4) the poverty measure includes all children ages 5-

17 residing in a school district, living in a family reported by the Ohio Department of Jobs and 

Family Services; and (5) the rural-urban scale for school district population (2000 Census) and 

whether the school district contains a large (>40,000) or very large (>100,000) city. 

Data Analysis 

Analyses were conducted with SPSS for Windows, Version 16.0. In order to examine 

differences in small and similar schools over the four years, we performed the Wilcoxon, the 

Mann-Whitney, and Friedman nonparametric statistical tests. The Mann-Whitney test is a non-

parametric analog of the independent samples t-test and can be used when the dependent variable 



Current Issues in Education Vol. 14 No. 1 14 
 
is a normally distributed interval variable. We used this test to determine if there is a difference 

in small and similar schools. A Friedman test is used when there is one within-subjects 

independent variable with two or more levels and a dependent variable that is not interval and 

normally distributed (but at least ordinal). Finally, we used the Wilcoxon test to compare the 

differences for two years for each group separately. 

Results 

Graduation Rates 

Table 1 is a summary of the descriptive statistics for graduation rates with Mann-Whitney 

results for group comparisons, from 03-04 to 06-07. This test compares graduation rates by year 

between small schools and similar schools.  Z scores in Table 1 suggest that there is a 

statistically significant difference between small schools and similar schools in graduation rates 

by year with similar schools having greater graduation rates. 

Table 1. 

Graduation Rates Between Small and Similar Schools 

 Type N Mean Std. Dev. Z Score 
Graduation Rates 03-04 Small school 30 66.387 18.299 -3.872* 

 Similar school 207 79.514 20.496  
Graduation Rates 04-05 Small school 31 69.500 18.638 -3.944* 

 Similar school 212 82.994 16.949  
Graduation Rates 05-06 Small school 33 72.091 21.482 -3.480* 

 Similar school 218 83.742 18.317  
Graduation Rates 06-07 Small school 35 77.214 18.809 -2.122* 

 Similar school 215 84.451 15.498  
Note. *p<.05 

Table 2 is a summary of a Friedman test for graduation rates in 2003, 2004, 2005 and 

2006. This test compares differences in graduation rates over the four years for the whole group, 

small schools, and similar schools separately. According to the Chi-Square scores shown in 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  15 
 
Table 2, there are statistically significant differences in the whole group and also small and 

similar schools separately in their graduation rates over the four years. 

Table 2. 

Graduation Rates Over the Four Years 

Friedman Test Whole Group Small School Similar School 
N 224 27 197 

Chi-Square 39.978* 21.067* 31.833* 
Df 3 3 3 

Note. *p<.05 

In order to compare changes of each group’s graduation rates in two consecutive years, a 

Wilcoxon test (two-by-two comparisons) is performed (see Table 3). We compared the whole 

group, small schools, and similar schools separately. Both the whole group and similar schools 

show statistically significant differences in graduation rates in the years 03-04 & 04-05, 04-05 & 

05-06, and 05-06 & 06-07. No yearly differences were observed from small schools. However, 

all three groups showed statistically significant differences in their graduation rates when we 

compared 03-04 and 06-07. 

Table 3. 

Graduation Rates Comparison Between Two Years 

Wilcoxon Test Grad 03-04 
Grad 04-05 

Grad 04-05 
Grad 05-06 

Grad 05-06 
Grad 06-07 

Grad 03-04 
Grad 06-07 

Whole Group Z -4.845* -4.121* -2.105* -5.996* 
Small School Z -1.635 -1.470 -1.674 -3.460* 

Similar School Z -4.662* -3.894* -3.012* -4.912* 
Note. *p<.05 

According to the KnowledgeWorks report (2009): 

• High school graduation rates increased from 62.8 percent in 2002 to 82.4 percent in 2007. 

• The graduation gap between OHSTI high schools and all Ohio high schools closed 

dramatically, by nearly 75 percent, from 19.9 percentage points in 2002 to 4.5 percentage 

points in 2007. 



Current Issues in Education Vol. 14 No. 1 16 
 

• 91 percent of OHSTI campuses experienced an increase in graduation rates since 2002. 

• The growth in graduation rates for white, black, and Hispanic OHSTI students exceeded 

the state growth rate for these groups between 2002 and 2007 (pp. 11-12). 

Unlike the KnowledgeWorks’ claim, our findings can only conclude that the differences 

between small and similar schools lie in their graduation rates every year. A steady yearly 

difference in graduation rates is not observed in small schools, but is found in similar schools. As 

seen in Table 2 and the last column in Table 3, the graduation rates changed over the four years, 

which suggests that OHSTI school graduation rates increased from 2003 - 2004 to 2006 - 2007. 

However, we also observed a significant difference in graduation rates for similar schools from 

2003-2004 to 2006-2007. 

Attendance Rates 

Table 4 shows the descriptive statistics for attendance rates with Mann-Whitney results for 

group comparisons. 

Table 4. 

Attendance Rates Between Small and Similar Schools 

 Type N Mean Std. Dev. Z Score 
Attendance Rates 03-

04 Small school 34 93.056 4.012 -0.939 

 Similar school 221 92.857 3.433  
Attendance Rates 04-

05 Small school 35 92.960 3.415 -0.996 

 Similar school 226 92.142 4.598  
Attendance Rates 05-

06 Small school 34 91.271 4.551 -1.405 

 Similar school 221 92.524 4.037  
Attendance Rates 06-

07 Small school 35 91.457 4.093 -1.365 

 Similar school 217 91.989 4.324  
Attendance Rates 07-

08 Small school 32 90.688 4.386 -2.176* 

 Similar school 213 92.376 4.251  
Note. *p<.05 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  17 
 
This test compares attendance rates between the two groups, small and similar schools, by year. 

As can be seen from the Z scores in Table 4, 2007-2008 is the only year showing a statistically 

significant difference in attendance rates between small schools and similar schools, with similar 

schools having higher attendance rates. 

Table 5 is a summary of a Friedman test for attendance rates in 2003, 2004, 2005, 2006, 

and 2007. It shows that there is a statistically significant difference in attendance rates for the 

similar schools over the 5 years. However, there was no statistically significant difference 

observed in the attendance rates of either the whole group or small schools. 

Table 5. 

Attendance Rates Over the Five Years 

Friedman Test Whole Group Small School Similar School 
N 235 28 207 

Chi-Square 9.398 6.105 12.564* 
Df 4 4 4 

Note. *p<.05 

A Wilcoxon test was performed to make two-by-two comparisons for the whole group, 

the small schools, and similar schools separately (see Table 6). Both the whole group and similar 

schools show statistically significant differences in attendance rates between 04-05 and 05-06 

and between 05-06 and 06-07. The only differences in attendance rates observed in small schools 

occurred between the years 05-06 and 06-07 and between 03-04 and 07-08. 

Table 6. 

Attendance Rates Comparison Between Two Years 

Wilcoxon Test Att. 03-04 
Att. 04-05 

Att. 04-05 
Att. 05-06 

Att. 05-06 
Att. 06-07 

Att. 06-07 
Att. 07-08 

Att. 03-04 
Att. 07-08 

Whole Group Z -1.493 -3.196* -2.077* -1.178 -0.429 
Small School Z -0.858 -1.309 -2.588* -1.171 -2.403* 

Similar School Z -1.246 -4.112* -3.314* -1.711 -0.598 
Note. *p<.05 



Current Issues in Education Vol. 14 No. 1 18 
 

According to the results shown in Table 4, the only statistical differences in attendance 

rates between small and similar schools were observed in 07-08. However, only similar schools’ 

attendance rates show differences over the 5 years, specifically from 04-05 through 06-07 (see 

Table 5).  A statistically significant difference in attendance rates between 03-04 and 07-08 was 

observed only in small schools (see Table 6). This finding supports the KnowledgeWorks report 

(2009) on OHSTI campus growth in attendance in total, but cannot support their claim on the 

growth in attendance rate for annualized data. 

Performance Index Scores 

Table 7 shows the descriptive statistics for performance index scores for both small and 

similar schools. There are Mann-Whitney results for group comparisons, comparing performance 

index scores between small schools and similar schools by year. The Z scores in Table 7 suggest 

that there is a statistically significant difference between small schools and similar schools in 

performance index scores by year, with similar schools performing better. 

Table 7. 

Performance Index Scores Between Small and Similar Schools 

 Type N Mean Std. Dev. Z Score 
Performance 04-05 Small school 34 76.256 17.737 -3.660* 

 Similar school 226 87.997 13.264  
Performance 05-06 Small school 35 78.143 17.717 -4.239* 

 Similar school 221 90.989 10.809  
Performance 06-07 Small school 35 82.989 11.912 -3.848* 

 Similar school 217 91.037 9.660  
Performance 07-08 Small school 32 83.728 12.270 -3.111* 

 Similar school 213 90.320 10.327  
Note. *p<.05 

Table 8 is a summary of a Friedman test for performance index scores for 2004, 2005, 

2006 and 2007. This test compares differences in performance index scores over the four years 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  19 
 
for the whole group, small schools, and similar schools. According to the Chi-Square scores 

shown in Table 8, there are statistically significant differences in all three groups, the whole 

group, small schools, and similar schools in their performance index rates over the four years. 

Table 8. 

Performance Index Scores Over the Four Years 

Friedman Test Whole Group Small School Similar School 
N 241 29 212 

Chi-Square 39.991* 13.138* 34.622* 
Df 3 3 3 

Note. *p<.05 

A Wilcoxon test was performed to do two-by-two comparisons for the whole group, the 

small schools, and similar schools separately (see Table 9).  All three groups, the whole group, 

small schools, and similar schools, show statistically significant differences in performance 

index scores between 04-05 and 05-06, between 05-06 and 06-07, and between 04-05 and 07-08. 

Table 9. 

Performance Index Scores Comparison Between Two Years 

Wilcoxon Test Per. 04-05 
Per. 05-06 

Per. 05-06 
Per. 06-07 

Per. 06-07 
Per. 07-08 

Per. 04-05 
Per. 07-08 

Whole Group Z -7.175* -2.683* -1.148 -3.712* 
Small School Z -3.291* -2.097* -1.197 -3.125* 

Similar School Z -6.433* -3.844* -0.731 -2.752* 
Note. *p<.05 

According to the results from these Mann-Whitney, Friedman, and Wilcoxon tests, there 

was a statistical difference in performance index scores between small and similar schools every 

year. Also, the differences in performance index scores were observed across four years within 

each group. However, only statistical differences between two consecutive years were observed 

from 04-05 through 06-07 in all three groups. The findings in the last column in Table 9 show 

that all three groups have a significant difference in the performance index scores, comparing 04-



Current Issues in Education Vol. 14 No. 1 20 
 
05 data to 07-08. According to mean scores in Table 7, the performance index scores of small 

schools gradually increased every year. However, we cannot compare our findings on 

performance index scores to the KnowledgeWorks report (2009), because their report does not 

include overall performance growth, but rather the improvement on both the mathematics and 

reading pass rates on the Ohio Graduation Test. 

Dropout Rates 

The state dropout data are presented using frequency data. Our team re-coded the data as 

Less than 10, Between 10 and 19, Between 20 and 29, Between 30 and 39, Between 40 and 49, 

and More than 50.  Figure 1 shows the frequencies of the middle grades. Dropouts for Grades 6 – 

8, middle school students, do not seem high enough to be a matter of concern.  Figure 2 shows 

the frequencies for the dropout rates for Grades 9 – 12 in small and similar schools. As can be 

seen in Figures 1 and 2, the dropout rates of high school students are much higher than those of 

middle school students. 

 

 

 

 

 

 

 

 

 

 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  21 
 

 

 

 
Figure 1. Dropouts in middle schools 

 
 
 

 
Figure 2. Dropouts in high schools 

 

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Small

School



Similar

School



Small

School



Similar

School



Small

School



Similar

School



Small

School



Similar

School



Small

School



Similar

School



2003
 2004
 2005
 2006
 2007


High
School
Dropout


Less
than
10
 10‐19
 20‐29
 30‐39
 40‐49
 Above
50




Current Issues in Education Vol. 14 No. 1 22 
 

 

Figure 2 and Table 10 compare dropout rates of re-coded data categories (from Less than 10 to 

More than 50) for 5 years for small and similar high schools. No increasing or decreasing pattern 

was found in the total number of students dropping out of school in either small schools or 

similar schools. For every year, a higher ratio of students appears in the More than 50 group in 

small schools than in similar schools. Both small and similar school dropout rates mostly appear 

in the Less than 10 students range. Less than 5 percent of dropout rates of similar schools occur 

in the ≥ 30 range; whereas approximately 20 percent of dropouts in small schools occur in the ≥ 

30 range each year. Considering the size of the small school, the respective ratios of (1) dropout 

rates in the range of 30 - 39, (2) 40 - 49, and (3) More than 50 to the total in small schools are 

much higher for similar schools. 

Table 10. 

Dropout Ratios for Small and Similar High Schools 

  2003 2004 2005 2006 2007 
Less than 10 65 59 69 67 54 

10-19 30 24 19 11 33 
20-29 10 14 14 14 11 
30-39 6 10 12 9 13 
40-49 4 6 7 8 4 

Small Schools 

More than 50 7 4 8 14 9 
Less than 10 509 560 474 432 473 

10-19 158 118 164 211 169 
20-29 54 31 49 66 57 
30-39 9 9 18 29 15 
40-49 2 7 11 5 4 

Similar Schools 

More than 50 9 7  8  
 

The Mann-Whitney results for group comparisons (small schools versus similar schools 

by grade) show significant differences in the high school grades: the ninth grade dropout rates 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  23 
 
show a statistically significant difference between small and similar schools in 2005 and 2007; 

and 10th, 11th, and 12th grade dropout rates show statistically significant differences in 2003, 

2004, 2005, and 2007. 

Implications 

In order to investigate the effectiveness of the OHSTI model, four variables are used to 

measure the success of small schools and traditional schools that have similar school profiles 

according to the state criteria.  KnowledgeWorks also released a report on the effectiveness of 

the small schools in 2009.  We attempted to compare our findings and the results reported by 

KnowledgeWorks to provide readers with a broader view of school transformation.  The 

KnowledgeWorks report and our findings cannot be compared item by item, because the two 

studies used different sets of data and the detailed research methods used by KnowledgeWorks 

cannot be confirmed.  Some findings of these two studies support each other to some degree, 

while others do not. 

With regard to the graduation rates, KnowledgeWorks reported that small schools’ 

graduation rates in 2007 increased by 20 percent compared to those of 2002, and that the 

graduation gap between OHSTI high schools (small schools) and all Ohio high schools closed 

dramatically in 2007 compared to 2002. Unlike KnowledgeWorks, our findings conclude that the 

differences between small and similar schools lie in their graduation rates by year.  A steady 

yearly difference in graduation rates is not observed in small schools, but is found in similar 

schools.  Similar schools had higher graduation rates than small schools.  However, both small 

and similar schools showed statistically significant differences in their graduation rates when we 

compared 03-04 and 06-07. 



Current Issues in Education Vol. 14 No. 1 24 
 

According to the descriptive statistics for attendance rates, 2007-2008 was the only year 

showing a statistically significant difference between small schools and similar schools, with 

similar schools having higher attendance rates.  There was a statistically significant difference in 

attendance rates for the similar schools over the 5 years.  There was no yearly difference in small 

schools but a difference in small schools occurred between 03-04 and 07-08. Our findings 

support the KnowledgeWorks report (2009) on the growth in attendance rate not for annualized 

data but in total. 

Even though the performance index scores of small schools gradually increased by year, 

there was a statistically significant difference between small schools and similar schools in 

performance index scores by year, with similar schools performing better.  Since 

KnowledgeWorks did not report on an overall performance growth, no comparison on 

performance index scores between the two studies was conducted.  Based on our data, there was 

no pattern in the total number of students dropping out of school in either small schools or 

similar schools. There was no dropout data reported by KnowledgeWorks. 

This study exclusively analyzed the standardized test results available from the Ohio 

Department of Education. The authors did not use individual class or individual student data, 

since that data was not made available by ODE. The results of the study are therefore limited by 

the information available from the state standardized tests: limitation of standardized tests in 

assessing students/schools growth; limited data or analysis offered by KnowledgeWorks or small 

school organizations; and relatively new data with a short history of the school system. Another 

limitation of similar studies is in the variation among the states of the definition of graduation 

and requirements to obtain a high school diploma. This also needs to be taken into consideration 

when reviewing the collected data (Gewertz, 2007). 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  25 
 

Issues to be considered regarding the variation in reported dropout rates is that some 

research does not account for students who move/transfer schools or who are held back for a year 

and so graduate a year later than expected. Many studies also do not account for those students 

who enter or are expelled in the course of the year. All of these things cause significant 

discrepancies in the data collected and the rates reported. Several of the researchers seem to be in 

agreement that the best way to get the most accurate data on who is graduating and what the 

dropout rates are is to collect this type of data by following individual students through their high 

school years. This would be the best way to ensure more precise data is being reported (Greene 

& Winters, 2002; Ramirez, 2008). Some believe that having more accurate data on dropout rates, 

which ties directly to performance issues and why students are not performing well in schools, 

would be very beneficial in evaluating student performance and the effects for school reform 

issues (ODE, 2004). One teacher stated the importance of the “need for a cultural shift—at the 

federal, state, and school levels—from using data for compliance to using data for improving 

student performance in each classroom” (Marshall, 2009, p. 1). 

Both KnowledgeWorks and our studies observed some progress in the small schools.  

However, it was not clear if the progress occurred due to a change in the school system.  Small 

schools programs alone are not the answer to improve education. In addition to restructuring a 

school system, a sense of community needs to be created within small schools.  Learning must be 

made a relevant hands-on endeavor by supporting teachers to become more caring, helping 

administrators become more effective leaders, and increasing parental involvement. In addition, 

it has been suggested to extend the school day and year for the students who need and want 

additional instruction (Driscoll, 2003; House, 2007). “The key to solving the distribution 

problem at the high school level is to act comprehensively, by significantly increasing the supply 



Current Issues in Education Vol. 14 No. 1 26 
 
of teacher candidates where shortages exist, improving the recruitment and hiring process, and 

retaining effective teachers in low-performing high schools” (Alliance for Excellent Education, 

2008b, p. 1). 

 

 

 

 

 

 

 

 

 

 
 
 
 
 
 
 



AN ANALYSIS OF HIGH SCHOOL TRANSFORMATION EFFORT  27 
 
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