AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON SCHOOL ACCOUNTABILITY AND STUDENT ACHIEVEMENT IN HIGH-POVERY SCHOOLS by Sheri L. Miller-Williams, Dissertation Chair: William Allan Kritsonis, PhD

1. To: Dr. Collins; Dr. Gardiner; Dr. Glenn; Dr. Osho
From: Dr. Kritsonis
Proposal Meeting, March 31, 2:00PM, Delco 240
Re: Some Notes for Chapter 3 - Methodology
AN INVESTIGATION OF THE IMPACT OF ATYPICAL
PRINCIPAL PREPARATION PROGRAMS ON SCHOOL
ACCOUNTABILITY AND STUDENT ACHIEVEMENT IN
HIGH-POVERTY SCHOOLS
BY
Sheri L. Miller-Williams - Some Notes
1. A Quantitative causal-comparative design will
be used to determine the cause for or the consequences
of differences between the participants in the study.
(See page 37 bottom)
(This design involves selecting two or more
groups that differ on a particular variable of interest
and comparing them on another variable.
(Fraenkel & Wallen, 2009)
2. Within this quantitative casual-comparative
research design, the independent variable (X) for
both research questions is the type of principal
preparation program participants engaged in.
(See page 38).
X1 = atypical principal preparation
X2 = Traditional principal preparation

2. 3. The research study also includes two dependent variables.
(See page 38, Independent and Dependent Variables)
For the first research question, the dependent variable
will be the impact on school accountability ratings (Exemplary,
Recognized, Acceptable, and Unacceptable) of high –poverty
schools in Greater Houston area school districts as measure by
the AEIS reports.
For the second research question, the dependent
variable will be student achievement results of high-poverty
schools in Greater Houston area school districts as measured
by the Texas Assessment of Knowledge and Skills (TAKS)
mathematics and reading scores.
4. The target population for this study is all elementary,
middle and high school principals in five targeted
school districts in the Greater Houston area.
5. For this study the researcher will employ a two-fold sampling
strategy: criterion sampling and the snowballing
sampling technique.
A sample size of 100 principals will be selected
for the study. The sample population will consist of 20
principals selected from each of the five targeted districts.
Within this sample, a combination of 10 atypically trained
and 10 traditionally trained principals will be included for
each district represented in the study. The sample will
include 50 atypically trained and 50 traditionally
trained principals. (See page 39).

3. 6. Criterion sampling involves selecting cases that meet
some predetermined criterion of importance. This method of
sampling is very strong in quality assurance. It can be useful
for identifying and understanding cases that are information
rich. Criterion sampling can also provide an important
qualitative component to quantitative data.
(See page 39, bottom of page)
7. The researcher will also utilize a snowball sampling
technique within the study. Snowball sampling is a method
used to obtain research and knowledge, from extended
associations or through previous acquaintances. Snowball
sampling uses recommendations to find people with the
specific range of skills that has been determined as
being useful. Within this sampling process, an
individual or a group receives information from
different places through a mutual intermediary.
Snowball sampling is a useful tool for building
networks and increasing the number of participants.
The snowball sampling technique will be utilized
to locate people meeting specific criteria that the researcher
would not have been able to identify. The advantage of this
technique is the ability of the researcher to use those in the field
with the knowledge of others who meet the criteria identified
for participation in the study. (See page 40).
8. The process of collecting data is known as
instrumentation. (Fraenkel and Wallen, 2009). The
initial data collection process for this study will include the
use of a demographic survey to collect and identify the sample
population based on pre-identified criteria. (See page 41).

4. 9. The statistical analysis portion of the study will rely solely
on quantitative instruments. The instruments will include
Texas Assessment of Knowledge and Skills (TAKS)
data from the 2008-2009 and 2009-2010 school years gathered
from the Academic Excellence Indicator System (AEIS) report
published by the Texas Education Agency (TEA) each year.
According to the Texas Education Agency (TEA), the
Academic Excellence Indicator System (AEIS) pulls together a
wide range of information on the performance of students in
each school and district in Texas each year.
(See page 41, last paragraph)
10. Validity and Reliability - The researcher has elected to
use two instruments that have both validity and
reliability. (See page 43, bottom, and top of page 44).
The quantitative instrument or Academic
Excellence Indicator System (AEIS) report is an
instrument generated by the Texas Education Agency
(TEA) that documents school performance on the Texas
Assessment of Knowledge and Skills (TAKS) assessment each
year.
The Texas Education Agency (TEA) conducts
internal tests for validity and reliability each year prior
to releasing the reports for review by the general public.
“Test reliability” refers to the consistency of
inferences researchers make based on the data collected
over time, location, and circumstances (p. 463, Frankel
and Wallen) (See page 42 at bottom, and page 43).

5. The Kuder-Richardson Formula 20 (KR-20)
is the measure in which internal consistency is
measured. The Kuder-Richardson Formula 20 is a
mathematical expression of the classical
measurement definition of reliability that validates
that as error variance is reduced, reliability
increases. (Standard measurement is calculated using both
the standard deviation and the reliability of test scores and
represents the amount of variance in a score resulting from
factors other than achievement).
11.Data Analysis (Pages 46 & 47)
Demographic data will be analyzed based on the
School Leadership Demographic Survey Instrument.
The researcher seeks to identify differences that
exist between the independent variable which is the
type of principal preparation and to analyze the
quantitative data. The researcher will compare the means (sets of
scores) from two
independent or different groups.
The comparison groups will consist of those who
have participated in atypical or traditional
principal preparation programs.
The Independent Sample T-Test will be used to measure
differences in the comparison groups. There is one
independent variable with two levels (X1 = atypical
principal preparation, and X2 = traditional principal
preparation).

6. For each research question, the researcher has
one dependent variable: School
Accountability Ratings (Exemplary,
Recognized, Acceptable, Unacceptable) and
Texas Assessment of Knowledge and Skills
(TAKS), student achievement scores in
mathematics and reading.
The Statistical Package for the Social Sciences
(SPSS 13.) will be utilized to analyze the data.
Frequencies and percentages will be calculated
and represented graphically. The researcher will
construct frequency polygons and then calculate
the mean and standard deviation of each group
if the variable is quantitative.
Note:
According to Fraenkel and Wallen (2009, p.
370), the most commonly used test for causal-
comparative research is the t-test for
differences between means. (See pages 47 and
48).