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.