Chapter V

DISCUSSION

Study for Action

            In summary, when all 258 schools are included in the database, six factors appear to influence the eighth grade math ISAT passing percentage.  Five of the six are not controllable by the school and one (pupil-to-teacher ratio) is controllable by the school.  When the 16 outlier schools are removed from the database, the number of factors increases, as does the number of controllable factors.  With the outlier schools removed, seven factors appear to influence the eighth grade math ISAT passing percentage.  Four of the seven are non-controllable by the school and three are controllable.  If persons were to ignore the few outlier schools, they would see that school districts in this study have more influence over the eighth grade math ISAT passing percentage.  The controllable factors that exhibit an influence in this case are pupil-to-teacher ratio, average class size (8th grade) and average administrator salary.

The first two of these controllable factors would appear to follow conventional wisdom.  It seems reasonable that students would benefit from greater personal instruction in classrooms with fewer students and/or classes that have a fewer students per teacher.  However, the benefit of the last controllable factor (average administrator salary) may not be so obvious.  For some insight as to why higher administration salaries result in high student achievement, one should refer to the literature review in Chapter II, the section titled “Administrator Compensation and Student Achievement.”  In this section, three research cases are cited that link administrative pay to student achievement.  The citations are summarized below.

Rainey & Murova (2003) conducted a study of Arkansas Public Schools that showed a positive correlation between student achievement and the percentage of student expenditures used to attract highly qualified administrators and teachers.  A similar research study conducted by Strauss (2003) in Pennsylvania found that administrators who earned more as a result of specialty training beyond general education certifications were linked to higher performance of the students.  Examples of specialty training cited in the study included K-12 guidance counselor, assistant superintendent for instruction, and special education certifications.  A study conducted by Brewer (1993) is the final case cited in the literature review.  This research found a positive correlation between increased administrative pay and higher student performance.  The effects were amplified as the well-compensated administrators appointed well-compensated faculty.  The greater the percentage of faculty appointed by the administration, the more significant the student achievement gains.

Summarizing the effects of the outliers, when all 258 schools are used in the study, the resulting preliminary predictive model is dependent on five non-controllable factors and one controllable factor.  When 16 outlier schools (6% of the total schools) are removed from the database, the number of factors increases to seven.  Four of the seven are non-controllable factors and three are controllable factors.


Limitations of the Study

            One of the limitations identified by the researcher is the difference between school wide controllable and non-controllable factors and eighth grade specific controllable and non-controllable factors.  Since the Illinois State Board of Education requests that schools report their metrics in these specific ways, the researcher was limited to the data as provided on the ISBE website.  The researcher acknowledges that there may be an “apples and oranges” difference when comparing factors that are eighth grade specific to factors which are school wide.

            Another limitation identified by the researcher is the fact that the passing percentage changes every year.  As described in Chapter I, the Elementary and Secondary Education Act dictates the rules that govern high-stakes testing.  One of the provisions is that the passing percentage is a value that changes (increases) by a few percent every year.  So it would be difficult to perform a longitudinal study that compares controllable and non-controllable factors from year to year.


Actions and Recommendations

            In this study, the researcher used data from the Illinois State Board of Education (ISBE) to determine which factors influence the eighth grade math Illinois Standards Achievement Test (ISAT) passing percentage for 2006.  Each year, all public elementary and middle-junior high school must report a multitude of metrics to the ISBE.  These schools’ specific metrics, along with the results of the ISATs, are then published by the ISBE in annual school report cards.  The researcher collected this data for 258 schools offering eighth grade in the counties of Cook (excluding Chicago Public Schools), DuPage, Kane, Lake, McHenry and Will.  The researcher then analyzed nine factors called controllable factors, over which school districts exhibit control, and nine factors called non-controllable factors, which school districts cannot control.

The preliminary results support the research question of whether one or more controllable factors influence the eighth grade math ISAT passing percentage.  The preliminary results uncovered that the when all 258 schools are used in a multiple regression analysis, a single controllable factor registers a low enough P-value to influence passing percentage.  This controllable factor is the pupil-to-teacher ratio and it has a coefficient of –0.57.  This indicates that as the ratio of pupils-to-teacher increases, the eighth grade math ISAT passing percentage decreases.  Conversely, as the ratio of pupils-to-teacher decreases, the eighth grade math ISAT passing percentage increases.  The preliminary results suggest the eighth grade math ISAT passing percentage would increase eight percent for a classroom with 28 students and two teachers (co-teaching) compared to a classroom with 28 students and one teacher.

During data examination, 16 schools were identified as outlier schools.  If these schools were removed from the database and the multiple regression analysis were rerun, slightly different preliminary results would be achieved.  The multiple linear regression analysis of the 242 non-outlier schools results in three controllable factors with P-value a low enough to influence passing percentage.  These controllable factors include pupil-to-teacher ratio, average class size (8th grade) and average administrator salary.  The coefficients for these controllable factors are –0.61, 0.22, and 0.07 (per $1000 of salary), respectively.

The preliminary results of this study may be helpful in formulating action plans that can have a real impact on eighth grade math ISAT passing percentages.  First, the researcher would like to offer suggestions for non-controllable factors that influence eighth grade math ISAT passing percentages and then do the same for the controllable factor.

This study found that five non-controllable factors influenced the eighth grade math ISAT passing percentage, when taking all the middle and junior high schools into consideration.  These factors were the percentages of black, Hispanic and low-income students and the mobility and attendance rates.  Even though non-controllable factors are defined in this study as factors that are beyond the control of school districts, two of the factors may be potentially influenced by school districts that have community guidance programs.

Mobility rate and attendance rate are non-controllable factors that influence eighth grade math ISAT passing percentage.  These are factors that school districts cannot directly control.  For example, a school district cannot stop a family from relocating into or out of a district.  Similarly, a school district cannot force sick or injured students to attend school.  Acknowledging this, there is something school districts can do to try to minimize the effects these factors have on the eighth grade math ISAT passing percentage.

Using the preliminary findings of this study, school districts can provide informational guidance to families in the community.  School districts can educate parents on how attendance and a stable educational environment impact their students’ success.  Increasing time in school and decreasing time out of school due to relocation should be the goal of this parental education program.

Attendance rate is a factor that is particularly suited for an intervention program.  For example, a school district could establish specific absentee amounts that lead to specific interventions on the part of the school district.  Suggested interventions might be similar to the following:

 

Number of

Student Absences

District Intervention

5

Phone call from school principal and follow up letter home to remind parents of the impact on a student’s performance for missing classes

8

Meeting between school principal and parents

10

Meeting between district representative (curriculum director or superintendent) and parents

Figure 14: Interventions for Student Absences

 

One suggestion for exiting families is to require parents to attend an out-processing meeting with a school councilor or district administrator where they can be reminded of the importance of getting their students re-enrolled in their new school as quickly as possible.  Perhaps release of the students’ school records can be contingent on parents attending such a meeting to ensure they get the necessary reminder.

Finally, this researcher would like to examine the preliminary results of this study as they apply to the controllable factors influencing the eighth grade math ISAT passing percentage and action plans schools can take to increase their passing percentages.

From this preliminary research, the singular factor of the controllable factors that exhibited influence on the eighth grade math ISAT passing percentage was the pupil-to-teacher ratio.  Pupil-to-teacher ratio should not to be confused with average class size.  Average class size is simply the average number of students that share a classroom.  In this study, the average class size ranges from a low of 11 to a high of 34.  By contrast, the pupil-to-teacher is the number of students in a class compared to the number of education professionals.  For example, if a classroom has 24 students and one teacher, its pupil-to-teacher ratio is 24:1.  If that same classroom received a co-teacher, teacher’s aide or other para-educator, the pupil-to-teacher ratio would drop to 12:1.

This researcher shared the preliminary findings of this study with the administrative staff of his school district, specifically the findings regarding pupil-to-teacher ratio.  The administrators were asked to share their suggestions for decreasing the pupil-to-teacher ratio.  The following is a summary of the suggestions given by the administration.

One, no-cost option to a school district would be to develop a collaborative program with local chapters of Future Teachers of America (FTA) and Future Educators of America (FEA).  FTA/FEA chapters are sometimes established in high schools that offer career guidance in educational fields.  High schools with FTA/FEA chapters also integrate a structured curriculum with classroom-based activities to prepare high school students for college teacher preparation programs.  High school members of FTA/FEA could spend several hours a week in a primary, elementary or middle school classroom after they had achieved the requisite structured curriculum at their high school.

Another, no-cost option a school district might consider is a collaborative program with a local college or university.  With this option, school districts could receive near fully trained education majors seeking to fulfill student teaching requirements, internships or practical hours.  Since many of these type of para-educators would be available for full semesters, their consistent and continued presence in a classroom would be of significant benefit.

Several suggestions were made that fall into the category of low-cost options.  Each of theses ideas involved hiring para-educators on a part-time basis and paying them slightly more than minimum wage.  From the experience one administrator had with this option, she felt most of these para-educators participated in her program for the sense of making a difference and not so much for the compensation.  The para-education participants in this program typically were college graduates who were professionals of one kind or another.  Some para-educators in this group had experience working as educators.

The three most often accessed sources of para-educators for this program were: 1) members of retired teachers’ organizations, 2) stay-at-home or part-time working parents involved in the PTA or PTO who had the desire to help in their children’s schools, and 3) non-education retiree professionals who worked in complementary career fields.

Accessing members of the community to assist classroom teachers proved to be beneficial on several levels.  One administrator, who managed this program for her previous school district, said the participants from the community felt a sense of ownership in the school district after they came to work at it.  Many of the para-educators in the program told how the experience opened their eyes to the challenges inherent in today’s education system.  Many also were excited by the opportunities these challenges presented.  The para-education participants in this program felt a tremendous sense of pride in the children they helped, the schools they served, and the contributions they made.  When at a later date the school district sought community support for an education referendum, many of these community para-educators became the strongest and most vocal proponents of the referendum. 

The last category of suggestions for reducing the pupil-to-teacher ratio contained the most formal and most costly ideas.  Three primary ideas made up this group.

 The most effective and most expensive idea was to hire full-time co-teachers to support each math teacher for every class period taught.  This would effectively cut the pupil-to-teacher ratio in half for all the math classes.  For example, a grade level with 150 students and six sections of math would have a pupil-to-teacher ratio of 25:1.  With co-teachers in every section of every math class, the pupil-to-teacher ratio would drop to 12.5:1.  From the preliminary research of this study, the 12.5 student pupil-to-teacher reduction would translate into a 7% to 8% higher passing percentage.  Of course this would require the school district to invest heavily in new math teachers.

A less effective and less costly suggestion was the idea of diluting the pupil-to-teacher ratio by adding more sections of math classes.  Using the same example above, a grade with 150 students and six sections of math would have a pupil-to-teacher ratio of 25:1.  If one more section could be added, the pupil-to-teacher ratio would drop to 21:1.  If two more sections could be added, the pupil-to-teacher ratio would fall to 19:1.  For a middle school with three grades, each with approximately 150 students or less, one additional full-time teacher could be employed to add two sections to each grade and reduce the pupil-to-teacher ratio by 24%.  From the preliminary research of this study, a reduction of six students in the pupil-to-teacher ratio would translate into a 3% to 4% higher passing percentage.

The least effective and least costly suggestion involved flexibly scheduling for an extended school day to add one additional math class.  Using the same example numbers in the previously mentioned options, one additional section would reduce the pupil-to-teacher ratio by about 14%.  From the preliminary research of this study, a reduction of three students in the pupil-to-teacher ratio would translate into a 1% to 2% higher passing percentage.  If this were achieved with the current staff of math teachers, the grade employing this suggestion would require compensating the math teacher for teaching an overload class.  Students in this class would be required to take this class during “zero hour,” before the start of the traditional school day.

These were the suggestions for action that the researcher was able to gain from conversations with his school district’s administrative staff.  They represent creative ways of bringing more help into the math class in an effort to reduce the pupil-to-teacher ratio which is the sole controllable factor cited by this preliminary research to increase the eighth grade math ISAT passing percentage.

The data amassed annually by the ISBE is comprehensive and complexly interrelated.  Finding relationships in the data that lend themselves to practical applications is a difficult process.  Data mining is a relatively new analysis tool that has gained widespread acceptance in commercial and scientific application in the past few decades.  Data mining software can analyze huge amounts of seemingly unrelated data and discover hidden relationships that would be imperceptible to most researchers.  A future investigation might employ data mining to uncover more sophisticated combinations of controllable and non-controllable factors that could optimize the school environment to meet the needs of specific groups of students and, thus, maximize their learning potential.