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RUNNING HEAD: A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 1
THE NATIVE AMERICAN STUDENT DROP-OUT RATE AT 50%
(26% HIGHER THAN FOR WHITE STUDENTS):
A PERSISTNG PROBLEM IN SEARCH OF A SOLUTION
By
Aaron A. Payment
Northern Michigan University
SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
MASTERS IN EDUCATION ADMINISTRATION &
EDUCATIONAL SPECIALIST DEGREE AT
NORTHERN MICHIGAN UNIVERSITY
December 19, 2011
APPROVED BY: Derek L. Anderson, Ed.D.
DATE: December 20, 2011
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 2
ABSTRACT
Background
Researchers have studied the Native American (Natives) high school drop-out crisis at
least since the enactment of the Indian Education and Self-Determination Act of 1974. Today,
this crisis persists with one of every two Natives who enter high school dropping out. Only four
of every ten who enter college will graduate. Natives have the worst high school graduation rate
of all racial ethnic population (National Center for Educational Statistics, 2010). Michigan
statistics mirror national data (EPE Research Center, 2009). One study of Michigan Natives
(Cornell, Parish, Schweitzer, 2001) shows a Native drop-out rate of 47% with Natives tracked to
non-college curriculum at a rate of three times that of their non-Native counterparts.
Research Focus & Methods
The broad purpose of this research is to identify, understand and explain influences on
educational outcomes for Natives borrowing from research by Sixkiller-Clarke (1994) to
examine the extent to which school, personal, family and cultural factors influence or predict
educational outcomes for Michigan Natives using non-experimental quantitative retrospective
research methods. The target population is Michigan Natives who earned their college degree as
differentiated by entering college with a high school diploma or General Education Diploma
(GED). Given the small n problem in studying Natives, convenience and snowball sampling
techniques were used. A sample size of n=300 was achieved representing several Michigan
tribes. Correlations, t-tests, ANOVAs, and multiple and logical regression were used to answer
six related research questions that address two main areas of inquiry: whether individual
characteristics and pre-college education factors influence high school GPAs and if MI Natives
graduate with a high school diploma versus a GED; and if there is a significant difference in
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 3
college graduating GPAs between the two populations and if individuals characteristics (pre-
college and college level) influence college GPAs.
Findings
Significant differences were found between the two groups on family income, expectation
to graduate, family member substance abuse, connection to school, connection to class cohort,
use of financial aid, the Michigan Indian Tuition Waiver, the Native American Office and Multi-
Cultural Affairs offices. Additionally, while there was a significant difference in high school
GPAs (on a 4.0 scale) between GED recipients (2.51) and high school graduates (3.09), the
college graduating GPAs between these two groups were not significantly different with GED
recipients edging out high school graduates (3.37 versus 3.35 respectively). Significant factors at
the pre-college level influencing high school GPA include: knowing what students wanted to be
when they grow up, connection to school, connection to class cohort, change in this connection,
class subject grades, and school type. Also, both parental expectations to graduate and
connection to class significantly influence whether an individual graduated or earned a GED.
Those items which influenced college GPA include: class subject liked in high school,
connection to culture, academic GPA in high school, whether or not the student graduated or
earned a GED and the use of multicultural affairs in college.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 4
TABLE OF CONTENTS
Chapter I: Introduction………………………………………………………………….... 6
Problem Statement…………………………………………………………...…………. 7
Research Purpose and Questions …………………………..…………………………... 8
Definitions………………………….………………………………………………….... 9
Chapter II: Literature Review ……………………………………………………………. 11
Data Related to Native American High School Graduation…………………………….
Native Entry and College Graduation………………………………….………………..
Visualizing the Crisis……………………………………………………………………
American Indian Education Shortcomings………………………………………………
11
13
13
16
Approaches: Deficit, Organizational/ Systems, Socio-Anthropological, Cultural………
Operationalizing Native American Retention Study…………………………………….
18
20
Related Studies
Quantitative…………………………………………………………………………
Qualitative…………………………………………………………………………..
22
25
Chapter III: Methodology
Research Design……………………………………………………………...………….
Quantitative Purpose and Research Question………………………………………
Conceptual Framework: Quantitative………………………………………….
Quantitative Research Design…………………………………………………
Population………………….……………………………..……...…….............
Small n problem in Native Populations………………………………………..
Sample Size……….. …...……………………………………..……...……….
29
29
29
30
31
32
32
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 5
Data Collection………………………………………………………………...
Variables……………………………………………………………………….
Reliability Assessment……………………………………………………
Limits on Variables in Data Collection…………………………………...
Quantitative Analytical Method……………..…………………………........…
Potential Researcher Subjectivity (Bias)……………………………………………
33
34
36
37
38
42
Chapter IV: Results
Quantitative Findings……………………………………………………………….
Descriptives (frequencies, correlations matrix)…...………...…………………
ANOVAS, t-tests……………………………………………………….…
Correlations……………………………………………………………...
Regression Analyses
RQ1……………………………………………………………………….
RQ2……………………………………………………………………….
RQ3……………………………………………………………………….
RQ4……………………………………………………………………….
RQ5……………………………………………………………………….
RQ6……………………………………………………………………….
RQ7……………………………………………………………………….
44
44
45
51
54
55
56
57
59
59
60
Chapter V: Recommendations and Conclusions
Conclusions………………………………………….………………..……………
Areas of Further Research: What Was Missed.………………………………….…
Limitations of Study……………………………………………………………….
62
64
65
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 6
References……………………………………………………………………………………
Appendices (A through G)…………………………………………………………………...
67
71
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 7
LIST OF TABLES
Table 1 Model of Hypothetical Differences in Outcomes for Natives versus Caucasian
Students from entry into high school through to college graduation………………..
14
Table 2
Applying Model of Differences in Outcomes for Natives versus Caucasian
Students from entry into high school through to college graduation (Nationally
and Michigan)………………………………………………………………………………
15
Table 3 Model of Hypothetical Differences in Outcomes for Natives (n=35) versus
Caucasian Students (n=65) from entry into high school through to college
graduation…………………………………………………………………………………...
16
Table 4 Proposed Factors, Independent and Dependent Variables for RQ1 through RQ4.. 35
Table 5 Descriptive Statistics for all Variables………………………………………………….. 44
Table 6 Mean Differences of Family Income While Growing Up (IV2) Between
Respondent Groups…………………………………………………………………………
47
Table 7 Mean Differences of School Connection (IV6) Between Respondent Groups……... 48
Table 8 Mean Differences of Connection to Class Cohort (IV7) Between Respondent
Groups………………………………………………………………………………………..
49
Table 9 Mean Differences of Class Subjects Liked (IV12) Between Respondent Groups….. 50
Table 10 RQ2 Coefficients for Final Model……………………………………………………….. 56
Table 11 RQ3 Coefficients for Final Model……………………………………………………….. 57
Table 12 RQ4 Coefficients for Final Model……………………………………………………….. 58
Table 13 RQ6 Coefficients for Final Model……………………………………………………….. 60
Table 14 RQ7 Coefficients for Final Model……………………………………………………….. 61
LIST OF FIGURES
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 8
Figure 1 Cumulative Promotion Index (CPI) formula developed by Christopher B.
Swanson, for the Urban Institute Education Policy Center………………………
21
Figure 2 Conceptual Framework for Intergenerational Historical Trauma for Native
Americans…………………………………………………………………………………..
26
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 9
CHAPTER I: INTRODUCTION
The disparity between Native American (Natives) student success versus that of the
general population and other racial-ethnic minorities is alarming. The attrition or narrowing of
academic success due to fractionating at each stage in education: those who enter high school;
those who graduate high school; those who enroll in college; those who graduate college,
underscores the importance of identifying factors that positively or negatively affect academic
success at each stage. Not all Natives who fail to graduate high school cease their educational
endeavors, but with a 50 percent drop-out rate for Natives (NCES, 2010), the alternative
educational path of a general education development (GED) certificate – appears to be the
Native tract to college for many Natives. There appears to be some factor, condition, or
phenomena for some Native students that make them less likely to graduate through the
conventional route. The fact that some Natives enter and graduate college through the GED
route, suggests there exists some set of characteristics that may predict success or failure.
Chapter I of this research will provide an orientation to the Native education experience
and focus the issue to the main problem statement. The purpose of this study will be identified
followed by the delineation of the main research question and subsidiary research questions and
methods to be tested through data collection and analysis. The significance of this study will
become apparent through the review of relevant statistics and analyses. An orientation to
commonly used terms in studying Natives and academic success will follow. Chapter II will
provide a more in-depth orientation to literature addressing both qualitative and quantitative
studies, as well as, address previous works related to Natives at various academic levels.
Chapter III will operationalize this two phased sequential mixed-methods study and describe the
methodology used to answer the main and subsidiary research question(s) including the analytics
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 10
applied. The results in Chapter IV will dually report the relevant statistical analytics which
describe the relationships of variables and a qualitative analysis to understand and describe the
phenomena associated with the Native drop-out crisis. Chapter V will conclude with some
recommendations for increasing the likelihood of Native American student graduation; identify
limitations of this study; and pose additional areas of both quantitative and qualitative
exploration to pursue a solution to the Native American drop-out crisis.
Problem Statement
Statistics show an enduring crisis of an alarmingly low high school graduation rate for
Native students. In 2006, the national high school graduation rate for Natives was 50 percent
versus 76 percent for Caucasian Americans (EPE Research Center, 2009). Compared to 2005
(NCES as cited by Faircloth and Tippeconnic, 2010), Natives experienced a three percent
improvement but the gap appears to be widening as the graduation rates for each population in
2005 were 47 percent and 70 percent respectively. Nationally, Natives continue to have the
lowest high school graduation rate of any racial-ethnic population at 1.2 percent lower than
African Americans; 29 percent lower than Asian/ Pacific Americans; and 5 percent lower than
Hispanic Americans. Michigan statistics for 2006, are consistent with national data with a
Native graduation rate of 49 percent versus 77 percent for Caucasian students representing a 28
percent gap (EPE Research Center, 2009). At the collegiate level, the experience for Natives is
also bleak. According to the National Center for Educational Statistics:
Sixty seven percent of Asians [graduate] compared with 60 percent of Whites; 48% of
Hispanics, 42 % of Blacks, and 40 % of Natives graduated with a bachelor's degree or its
equivalent within 6 years. Nonetheless, Natives consistently had the lowest graduation
rates of the five racial/ethnic groups (NCES, 2010).
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 11
While there is a great deal of descriptive statistical reporting of the incidence of Native
graduation rates and an abundance of literature steeped in qualitative socio-anthropological
theory to explain why Natives drop-out, there appears to be little research that comprehensively
studies the problem – namely through quasi-experimental research and rich phenomenological
explanations drawn from the same participants. More pointedly to the Michigan Native
population, broad studies on the Native drop-out crisis in Michigan appear non-existent.
Michigan Tribal leaders are reticent to facilitate implementation of intervention strategies
gleaned from communities outside of their own experience. With some Natives persisting
through to graduation in college after having dropped out of high school, there may exist some
discoverable characteristics for Native student success.
Research Purpose and Questions
The broad purpose of this research is to identify, understand and explain what influence
educational outcomes for Natives at both the high school and college level. This study will
explore the extent to which school, personal, family, and cultural factors influence educational
outcomes and seek to understand the experience of Michigan Natives in educational institutions.
Differences that exist between Natives who earned their college degree by way of earning a high
school diploma versus those who attained their general education development (GED) certificate
will be analyzed. This positivistic-oriented study will examine what factors explain and predict
the probability that some Natives may succeed. A second phase (not reported in this research)
will have a broader purpose of exploring phenomenological and ethnographic components to
inductively discover common or divergent cultural experiences of Michigan Natives and seek to
describe and understand the experiences of Michigan Native Americans in educational
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 12
institutions. The second phase will explore, describe, and explain these educational experiences
with the hope that related grounded theory will emerge for further study and problem solving.
The broad purpose of the current research is distilled to two main research areas:
1) Do individual characteristics and previous education factors influence whether or not
MI Natives graduate with a high school diploma versus a GED?; and
2) Is there a significant difference in college graduating grade point averages (GPAs)
between MI Natives who entered college with a high school diploma versus those who
attained their GEDs?
The following subsidiary research questions will be explored to contextualize the answer to the
initial areas of inquiry. Is there a difference between college graduating GPAs for the two
subsets of the population studied – high school graduates versus those who earned their GEDs?
Do various pre-college and select college variables predict college graduating GPA? Do select
college variables and whether an individual earned a high school diploma or GED predict college
graduating GPA? What is the effect of all pre-college and all college variables on college
graduating GPA? Is any difference between high school GPA of those who graduate high school
versus those who earned their GED? What predictive values does all pre-college variables have
on high school GPA? Finally, how well do these pre-college variables predict whether or not
someone will graduate with a high school diploma versus a GED? You will note that these
questions becoming increasing more complex with variations of additional factors added to the
design. The initial research question and subsidiary questions, method of analysis, and decision
factors are fully explored in Chapter Three.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 13
Definition of Terms
Attrition and matriculation are used as inverse properties that extend the annual drop-out
rate beyond one year and explain those who do not continue and those who do (respectively).
Graduation rate and drop-out rate are used as inverse properties even though it is
understood that some students may eventually elect to re-enter education in at a later date.
Native American(s), Native(s), Native student(s) refer to those individual(s) who are
members of federally recognized American Indian tribes. This is different from those who self-
identify as American Indian but cannot prove this through legal documentation of blood lineage
and enrollment in a federally recognized tribe.
Persistence, persist and ‘did not persist’ are emerging as the standard as these terms do
not carry with it the negative connotations that the term drop-out does.
Racial Terms - though datasets and studies generally use the terms Whites, Blacks,
Asians, Hispanics, the more appropriate terms of Caucasian, African American, Asian Pacific
Americans, and Hispanic Americans are used. Even more appropriate but cumbersome terms of
Latino/a, Chicano/a, Cuban, Puerto Rican, Dominican, and other populations clustered into the
conglomerate Hispanic nomenclature are noted. Several additional terms are used throughout
and are sufficiently explained both in their context and often with brief descriptive asides.
Retention is simply the state of continuing to be enrolled and usually refers to a year to
year statistic. Typically, the retention rate is the number of students who enter one academic
year over those who were enrolled the previous year. Use as a static statistic is often confused
with a longitudinal retention rate which is the combined rate of retention year to year through to
graduation.
Succeed (academically). At this stage, the phrase “succeed along a conventional route”
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 14
will be generally defined as those from the target population who earn a high school diploma
within a four year time frame and those who earn their college degrees within the six years.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 15
Chapter II: Literature Review
Chapter One sought to provide compelling statistics to demonstrate the serious need for
the issue of Native American high school and college retention to be studied further such that
practicable solutions are found. Chapter two gets into more specifics and describes how the
issue of Native student retention has been studied including qualitative explanations of the issue
and quantitative studies to begin to understand the relationships and effects of predictor variables
on outcomes. Review of the literature will elaborate the Native American drop-out crisis;
highlight the work that has been done to date with regard to the Native drop-out crisis at both the
high school and college levels; and provide an overview of the essential studies conducted since
Indian Education became a studied topic in and around the enactment of the 1974 Indian
Education and Self-Determination Act. Enduring conceptual frameworks will be described like
those developed by Reyhner (1991) in writing the seminal Indian Nations At Risk, to provide the
theoretical basis for what the literature describes as factors influencing Native retention. Finally,
the application of these factors through three quantitative research studies, two at the secondary
level and one at the post secondary level will be summarized for their value related to the
variables but also to demonstrate three different levels of statistical analyses (independent t-test,
ANOVA, and multiple regression) as relevant to the current study. Qualitative explorations will
draw liberally from the literature to help frame what we may find in the data.
Data Related to Native American high school graduation
The National Center for Education Statistics (NCES) reported in 1989 that Native
Americans (Natives) had a high school graduation rate of 35.5 percent which represented the
highest drop-out rate of any racial/ ethnic group (Reyhner, 1991). Though there are variances in
reported data, clearly Natives persist in having the worse high school completion rate of any
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 16
racial-ethnic group. According to Swanson (2003) for the high school class of 1999-2000, the
graduation rate for Natives was 38.1 percent. In reviewing more closely 2005 data from the
National Center for Education Statistics for the twelve states that have the largest proportion of
the total student population who are Natives, the graduation rate for Natives ranged from 30
percent (South Dakota) to 64 percent (Oklahoma). Even more striking is the 45 percent lower
graduation rate for Natives in South Dakota versus the general population. The average
graduation rate for these states for Native Americans was 47 percent versus Caucasians at 70
percent (a disparity of 23 percent). Again Natives have the lowest graduation rate of any racial-
ethnic group at 8 percent lower than African Americans; 31 percent lower than Asian/ Pacific
Americans; and 4 percent lower than Hispanic Americans. Finally, using the same dataset, there
appears to be a gender difference - 42 percent for male Natives versus 51 percent for female
Natives - with Native males graduating at a lower rate in all but one of these states (Faircloth and
Tippeconnic, 2010). In an historical archival study of a school district located in a small town in
the upper peninsula of Michigan of the 1990’s, Cornell (2001) reported a Native high school
drop-out rate of 47 percent. Thus, in Michigan and nationally, one out of two Native Americans
who enter high school do not graduate. By all measures, this data demonstrates a crisis.
Of course, though graduation is the ultimate measure of academic success it is by no
means the only measure. Twenty nine percent of Native students have had to repeat at least one
grade which is the highest percentage of any racial/ethnic group. Less than 10 percent of Native
students are in the upper quartile on achievement test scores in history, mathematics, reading and
science while 40 percent are in the lowest quartile (Reyhner, 1991). Looking at SAT and ACT
scores from 1987 to 1997, Natives lagged behind the rest of the nation and ranked below the
national average in completion of core curriculum for high school graduation (Gilbert, 2000).
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 17
According to Reyhner (1991) there is evidence of the ‘unequal’ practice of tracking Native
students into non-college preparation. In the study in Michigan noted previously, it was also
demonstrated that Native students were 3 times more likely to be tracked to non-college prep
over their non-Native counterparts (Cornell, 2001).
Native Entry and College Graduation
Literature for post secondary graduation rates of Native Americans is noticeably scarce.
Available statistics, however, show a persisting Native dropout crisis at the collegiate level as
well. The problem of retention does not begin with college enrollment as Native Americans are
the least likely to enroll in four-year public institutions of higher education and the least likely to
graduate in those institutions (Larimore and McClellan, 2005). According to Neisler (1992 as
cited in Larimore and McClellan, 2005) 60 percent of all students who graduated high school in
1989 immediately enrolled in college while Tierney (1992) cites several studies indicating that
only 40 percent of the Native students who graduate high school will enroll in college. Once in
college Native students are less likely to graduate. Tierney adds that a retention rate for Native
Americans may be as low as 15 percent overall. According to Brown and Robinson Kurpius
(1997 as cited in Larimore and McClellan, 2005) estimates of drop-out rates for Native students
in higher education range from between 75 to 93 percent . One incredulous statistic cited by
Gilbert (2000) for those who were enrolled in college (1994-95) one percent of Natives received
bachelor’s degrees compared to 79 percent of students from the dominant culture.
Visualizing the crisis
The critical nature of the crisis of the Native drop-out rate is perhaps better appreciated
when using numbers of students rather than percentages and tracking a hypothetical group of
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 18
students from entry into high school through to college graduation. From data presented earlier,
if 49 percent of Native students graduate high school, and 40 percent of this subset actually
enroll in college (versus 77 percent and 60 percent respectively for Caucasians) for a
hypothetical population of n= 100 for both populations, we see 28 of the Caucasian students who
start high school eventually finish college versus just eight for Natives (See Table 1). Note how
this model fractionates the total number for both populations at each juncture.
Table 1
Model of Hypothetical Differences in Outcomes for Natives versus Caucasian Students from
entry into high school through to college graduation.
A B C D E F G
n
%
Graduate
HS (A*B)
% of those
who
Graduate
HS who
Enroll in
College
# who
enroll in
College
(C*D)
% who
graduate
college
# who
graduate
college
(E*F)
Whites 100 77% 77 60% 46 60% 28
Natives 100 49% 49 40% 20 40% 8
Taking this a step further, using NCES (2010) data for high school graduates rates in
2006-07 for the Nation, a projected 3,913,871 (2,892,351 graduated / a rate of 73.9 percent who
entered high school four years earlier) students entered high school during the 2002-03 school
year. The comparable data in Michigan is 145,244 (111,838 who graduated/ a rate of 77 percent
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 19
who entered high school four years earlier) students who entered high school in 2002-03.
Inserting each of these figures into the model from Table 1 - Natives at a factor of 1.5 percent
nationally and .05 percent for Michigan (My Online Maps, 2011) of the total population at each
level (see Table 2), we see the following results in Table 2:
Table 2
Applying Model of Differences in Outcomes for Natives versus Caucasian Students from entry
into high school through to college graduation (Nationally and Michigan)
A B C D E F G
n
%
Graduate
HS (A*B)
% of those
who
Graduate
HS who
Enroll in
College
# who
enroll in
College
(C*D)
% who
graduate
college
# who
graduate
college
(E*F)
Nation
White 3,913,871 77% 3,013,681 60% 1,808,208 60% 1,084,925
NA 58,708 49% 29,354 40% 11,742 40% 4,697
MI
White 145,244 77% 111,838 60% 67,103 60% 40,262
NA 726 49% 356 40% 142 40% 57
Extrapolating the relative success rates noted above at each juncture, varying the n for
both Caucasian and Native students, for the nation we see that of the 3,913,871Caucasian
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 20
students who enter high school, hypothetically 1,084,925 (28%) will graduate college while the
comparable number for Natives is just 4,697 (8%). For Michigan, of the 145,244 Caucasian
students who enter high school, 40,262 will graduate college while just 57 of the 726 Natives
who enter high school will matriculate on through to college graduation.
Taking this hypothetical one step further to represent the proportion of a total population
of students Natives represent by using a 35% and setting the total population at 100, we see that
eighteen of the original sixty five Caucasian students will matriculate through to college
graduation while just three Natives out of the original thirty five Native Americans who enter
high school will graduated college. In this final hypothetical model, where Natives represent
35% of the total population who enter high school, they represent a mere 16% of the total
population who will graduate college.
If the extrapolations from this hypothetical model hold true, there exists a ready challenge
for educational leaders to not only endeavor to fix the high Native drop-out problem, but also
work to understand what factors influence the likelihood of Natives matriculating at each
juncture as these factors may ultimately relate to their academic success or failure beyond high
school. Once Natives enter college, it is also important to understand the factors (before and
during college) that influence the likelihood of Natives not only matriculating through to college
graduation but to also of success with measures of achievement like grade point average.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 21
Table 3
Model of Hypothetical Differences in Outcomes for Natives (n=35) versus Caucasian Students
(n=65) from entry into high school through to college graduation.
A B C D E F G
n
%
Graduate
HS (A*B)
% of those
who
Graduate
HS who
Enroll in
College
# who
enroll in
College
(C*D)
% who
graduate
college
# who
graduate
college
(E*F)
Whites 65 77% 50 60% 30 60% 18
Natives 35 49% 17 40% 7 40% 3
American Indian education short comings
The apparent unrelenting crisis of a low Native American high school graduation rate and
inversely - the drop-out rate, warrants a comprehensive, valid and reliable study that
operationalizes, and triangulates methods in order to identify factors that influence Natives to
dropout in order to find solutions. In discharging it’s federal fiduciary responsibility to honor the
‘prepaid treaty right’ of education for American Indians, the federal government has had mixed
results with mostly adverse effects of Indian boarding schools designed to assimilate Natives by
stripping them of their cultural identity and worldview to nominal funding through the Johnson
O’Malley (JOM) tribal education funding program established under the Indian Reorganization
Act of 1934 and the Indian Education and Self-Determination Act of 1974 which provided equity
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 22
funding for federal Title initiatives like Indian Education (currently Title VII) to public schools
who have verifiable Native student counts from federally recognized tribes. Over the years, a
number of Congressional reports have been commissioned (NCLB Indian Education Workgroup,
National Advisory Council on Indian Education (NACIE) Annual Reports). Though positive in
some respects with shining a light on the crisis that is American Indian Education, these
retrospective historical archival studies, have generally failed to comprehensively quantify the
problem in a valid and reliable way; have not studied the issue in a longitudinal manner; and
have not systematically ascertained explanations that have any practicable use. Additionally,
irrespective of past efforts, Natives persist in having the highest rate of high school dropout of
any racial/ethical population. Past Indian education research has focused primarily on regional,
reservation or Bureau of Indian Affairs/ Education (BIA/BIE) funded residential or day schools
with none on Michigan Natives. Thus, these studies have limited generalizability to Michigan.
Survey research through a quantitative survey and historical document approach
(Creswell, 2009) is necessary for examining variables that effect Native student retention, but it
is by no means sufficient for solving the problem. To the extent that characteristics that
positively influence Native retention can be identified and replicated while mitigating negative
influences, successful intervention strategies may be discovered and developed. Of preeminent
interest is identifying access factors that have a positive impact while minimizing variables that
adversely influence a Native student’s likelihood of succeeding academically. Involving a
partnership between individual tribes, tribal nation groups, the National Congress of American
Indians, the Bureau of Indian Education and the tribal education departments may facilitate a
comprehensive and applied examination of the issue in order to make systemic and lasting
change. Putting federal bureau (administrative), Congressional, and tribal governance territorial
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 23
differences aside, the opportunity for partnerships exist for a meaningful and applied approach to
finding solutions with potential alignment of Title VII, JOM and other tribal resources to address
this crisis. If it takes a village to educate a child, it certainly takes more than an isolated
approach to ensure a Native child’s academic success. Fully understanding the phenomena of
the Native dropout problem is the first step.
Approaches and Theoretical Frameworks
Approaches to the study of Native student retention have varied depending on the
researchers’ theoretical and conceptual frameworks. Deficit theory posits that students who
come from broken homes need individual attention and enrichment for skill mastery (St.
Germaine, 1995). In the U.S. Department of Education commissioned study entitled, Indian
Nations at Risk, Reyhner (1991) noted that a survey of research demonstrated that studies
focused on so-called deficits of the student who drops out, such as intelligence, school
attendance, and parental income. Instead, he suggests a shift in focus to systemic institutional
and support issues endemic to schools like: large factory-like schools, uncaring teachers, passive
teaching methods, irrelevant curriculum, inappropriate testing, tracked classes, and lack of
parental involvement (Reyner, 1992, 2006). This systems focus has endured in Native
educational research. Organizational theorists postulate that ‘school-structures’ need to change
to retain students. A sociologist/ anthropologist focus on economic and political structures that
are endemic to society and “give voice to some and deny it to others” suggests, ‘that winners and
losers are inevitable” (McLaughlin, p. 53 as cited in St. Germaine 1995, p. 2). These critical
theorists call for "teachers as coaches, pedagogy as problem solving and curriculum that
addresses important themes connected to the lives of students” (St. Germaine, 1995, p. 2).
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 24
The conceptual model of cultural discontinuity focuses on student social adjustment to
the dominant culture (St. Germaine, 1995) and falls into the broad category of cultural theorists
which is borne out of the work of sociolinguists. According to St. Germaine (1995), “Cultural
difference theorists believe solutions lie in teachers becoming knowledgeable about the culture
and language of their students and adapting curriculum and teaching methods to students’ needs”
(p. 3). Cultural discontinuity theory suggests that minority children,
…having been initially raised in a distinctive culture of their own, are often thrust into a
school system that promotes the values of the majority culture - not those of their own.
If the resulting clash of cultures continues, the minority child may feel forced to choose
one culture at the expense of the other. Success (in school becomes failure (in the
community)…failure in school is a tacit cultural goal that must be achieved”
(McDermott, 1987; Spindler, 1987 as cited in St. Germaine, 1995, p. 3).
While St. Germaine cited that though cultural discontinuity plays a major role in Native
American student failure, some researchers caution that this construct is too narrow as it ignores
“macrostructural variables” when there is “overwhelming evidence that economic and social
issues…not culturally specific to being Indian” are significant to Natives dropping out (1995, p.
4). Certainly, the notion of cultural discontinuity is consistent with Reyhner’s findings in the
Indian Nation’s at Risk study where he noted the impact of “inappropriate” curriculum in
teaching methods where the curriculum does not reflect the Indian child’s unique cultural
background. He elaborates that, “textbooks are not written for Indian students…they enlarge the
cultural gap between home and school” (Reyhner, 1992, p. 5). With images of American Indians
in movies and television as uncivilized and blood thirsty savages, Indian sports mascots as the
savage warrior or with a goofy grin reminiscent of the Black Sambo, and little or no authentic
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 25
competing history taught in school to counter the objectification of American Indians, it’s no
wonder Natives flee school systems. Irrespective of the level at which a Native American
student has assimilated to the dominant culture or the extent to which an Native student is not
identifiably Indian (in visual appearance), the persistence of negative or incomplete cultural
stereotypes serves to perpetuate a lowered sense of self. This notion is reinforced through a
resolution enacted by the American Psychological Association which reads:
…the continued use of American Indian mascots…appears to have a negative impact on
the self-esteem of American Indian children…is a detrimental [to]…the cultural identity
of American Indian people through negative displays and/ or interpretations of spiritual
and traditional practices (American Psychological Association, 2005).
Though possibly well intended, sociological/ ethnographic studies provide a limited view
and application of Natives that is often one-dimensional. In the past, oversimplified
generalizations of Natives, as “good with their hands”, “good workers at heights” or “good with
arts and crafts” probably contributed to tracking Natives into non-college preparation programs.
Indian boarding schools were designed to assimilate Natives. One method was to train them to
become textile workers or seamstresses (St. Germaine, 1995). Federal funding for many Native
dropout studies originates from the Bureau of Indian Education and have limited application as
these studies follow one conceptual framework or another focusing on reservation-based Indians,
residential or Indian day-schools, geographically or to individual tribes. This leaves the
impression that Natives are a homogenous population and that there is one way to study Natives.
Operationalizing Native American Retention Study: Getting on the Same Page
One challenge in studying the Native American drop-out crisis is the lack of agreement of
which retention statistic to look at. According to Reyhner,
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 26
Studies by some school districts…only [report] the dropout rate for one year…such
studies ignore students who will drop out in subsequent years before graduating or who
have dropped out in previous years. Longitudinal studies are those that follow students
through high school… (1991, p. 3).
Some researchers (Swisher, 1992) have tried to establish a standard for defining Native student
dropouts and conversely retention rates by conducting a survey of methods. Pavel (1992) cites
several other studies to define reliable indicators including state equity scores or enrollment
(ESEs) created by dividing the proportion of Natives in a state’s population by the proportion of
Native enrollment in the state’s education institutions. Pavel prescribes the use of state equity
scores for graduation (ESGs) which can be computed by dividing the proportion of Natives in an
entering class by the proportion of Natives who graduate. Comparing these indices to the
general population provides a relative statistic of how Natives are doing compared to others.
Nonetheless, Pavel (1992) cited the lack of unanimity on the subject.
In reviewing more recent general literature on high school graduation, it appears as
though at least some states are now using the National Governor’s Association (NGA) Compact
Formula for calculating graduation rates which is calculated by, “taking the total number of
Native American students who graduated from high school within 4 years and dividing by the
total number of freshman Native American students entering high school four years earlier, then
multiplying by 100” (Zwiebel, 2010, p. 77). Another recent study used the National Center for
Education Statistics data, and the Cumulative Promotion Index (CPI) developed by Swanson
(2003 as cited in Faircloth and Tippeconnic, 2010) which collects and analyzes simulated
longitudinal data to allow researchers to track student progress toward graduation. Thus, the
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 27
statistic is the combined probability for each static statistic for each class to simulate the
probability of graduating. Figure 1 shows this calculation,
Figure 1. Cumulative Promotion Index (CPI) formula developed by Christopher B. Swanson, for
the Urban Institute Education Policy Center.
Related Studies
Quantitative Studies
The following quantitative studies represent two at the high school level and one at the
collegiate level examining the Native student drop out crisis from varying perspectives. These
studies were selected for their similarities to the quantitative portion of the current study. The
first, uses an independent t-test to study the effect of an intervention treatment at the Nizhoni
Academy which teaches Native students (Gilbert, 2000). The second, is a study using an ANOVA
test to examine cultural, school and family factor (Sixkiller-Clarke, 1994) differences between
Native high school drop-outs and those who graduated high school. The third, uses a multiple
regression study at the University of Oklahoma to make predictions on whether or not the fall
class of Native American students would matriculate to their sophomore year while examining a
number of pre-college and during-college independent variables on the outcome of persist or not
(Healy, 2000).
First, we start with a quantitative study of high school interventions by Gilbert (2000)
which used a ‘pre-experimental’ research design with a treatment afforded to a group of Native
high students who attended a five week summer academic program (Nizhoni Academy). The
purpose statement focused on the outcomes of an intervention or treatment on Native high school
sophomores and juniors in a five week summer program which provided direct instruction and
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 28
academic support for educationally disadvantaged students from rural high schools in the ‘four-
corners’ Southwest area. The program goals were to acquaint students to the rigor of college
life, and to prepare them for college and continued academic success after high school (Gilbert,
2000). The Nizhoni Academy philosophy focused on five aspects of learning including: meta-
cognition, concentrated learning, cooperative learning, a process approach, and critical thinking
skills. Each aspect emphasized structured learning opportunities that promoted culturally
oriented individual and communal learning. Three research questions asked how student
academic achievement was affected as evidenced by post-test scores in three subject areas. The
research design was ‘pre-experimental’ quantitative as no control group was used. Pre-test and
post-test scores were examined. The researcher set up a non-directional null hypothesis for
analyzing mathematics, English, and career development pre-test, post-test differences. A
convenience sample was used which represents a potential internal validity concern. Changes to
the curriculum (systems theory) were implemented including method of delivery, supplemental
instructional experiences and reinforcement of learning through collaborative activities, building
trust with the instructors, and creating social cohesion. The mean scores on pre-tests/post-tests
were examined to prove or disprove the null, thereby rejecting or accepting the alternative
hypothesis. The post-test scores were significantly higher (using a two tailed t- test) for math
pretest-posttest (M = 2.54, SD = 1.40 < M = 4.46, SD 1.69, p < .001); (M = 3.80, SD = 1.40 < M
= 5.82, SD = 1.50, p < .001); (M = 84.60, SD = 11.20 < M = 89.81, SD = 7.63, p < .001). Even
when factoring for the effects of gender, grade-level, and public/ private school, students showed
significant improvements thereby rejecting each null hypothesis (Gilbert, 2000).
Next, a study by Sixkiller-Clarke (1994) used an ANOVA test to: Identify the factors
that keep Native American students in school (graduation); and identify the factors that result in
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 29
their leaving school prematurely (i.e. dropping out). The participants were Native high school
students (n =156, 116 high school graduates, 40 drop-outs) living on reservations in1989, 1990,
or 1991 in the Montana, North Dakota and South Dakota regions. Selected variables were
grouped in areas of person problems, school factors, family factors and cultural issues.
Significant differences were found in skipping school between those who graduated high school
(M = 2.71) versus those who dropped out (M = 1.92) F = 19.30(1, 154), p < .001); retention at
grade level (failing a class) graduates (M = .18) versus those who dropped out (M = .43) F =
11.10(1, 154), p < .001); and for playing sports with graduates (M = 1.64%) versus those who
dropped out (M = 2.35%) F = 11.27(1,159), p < .05). Further, for differences in skipping school,
retention at grade level and sports, the r statistics were .11, .07, and .07 respectively. No other
variables examined under cultural, school and family factors were found to be significant.
The third and more complex level of study at the university level (Healy, 2000)
examined the entire 270 new enrolling freshmen Natives at the University of Oklahoma in the
fall of 1994 to predict retention to the second semester along a number of pre-college and during-
college variables. The Native student population represented 10 percent of the new freshmen
whereas the Caucasian population represented 79 percent. The purpose was to determine to what
extent they could predict retention as measured by successive enrollment in the fall semester
1995. This multivariate study using a multiple regression analysis explored family, tribal and
community experiences as factors broken down into: pre-college (mother’s and father’s
education level, state of residence, high school size, high school GPA, seven different ACT sorts,
and population of hometown); during-college variables (intended science related major as yes or
no, status of campus living, and first semester GPA). In the descriptives, it was reported that
89% of the Native students matriculated while 11% did not. The significant relationships
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 30
between various predictors and retention were: type of housing, semester GPA (p < .001,
respectively) and English ACT and Reading ACT (p < .05, respectively). Overall, the
combinations of these variables account for an R2 predictive value of .581 which Healy (2000)
reports means these three variables account for 34% of the variation in retention.
Qualitative Studies:
Collectively, the literature on Native American retention demonstrates a crisis with the
highest drop-out rate of any racial ethnic group. In addition to the survey of study types noted
previously, several qualitative studies have provided great insights into the problem with at least
a few studies demonstrating the consistency of the combination of personal, family, school, and
cultural factors that influence the Native drop-out phenomena. More specific regional studies
and comparisons to national databases like NCES might shed additional light to better appreciate
the situation. Building a body of literature that pinpoints the effect of variables and taking the
next (qualitative) step to prescribe how to enhance those positive conditions and minimize the
negative factors might lead to the development of effective intervention strategies.
Historical Trauma
Grounded theory seeks to remain open to emergent themes or patterns which then
may formulate a theory to describe some social phenomena (Patton 2002, Creswell, 2009).
Natives are in large part a heterogeneous population with a diversity of experience including
cultural identities, visual appearance, urban versus rural versus reservation, socioeconomic
status, and legacy Indian board school experiences. There are a few working theories or
conceptual frameworks regarding American Indians from which to borrow from academic
disciplines of psychology, sociology, cultural anthropology and ethnic studies which may
explain the common educational experience and facilitate data collection in the current research.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 31
The prescience of these conceptual frameworks exist through an historical trauma
working hypothesis or conceptual framework. Social indicators like high rates of suicide,
alcoholism, transience, and normlessness in common Native experiences rings familiar with
Durkheim’s theory of social anomie (Young, 1991). Immigrant theory (Bender and Kagiwada,
1968) challenges the melting pot notions of cultural assimilation, acculturation with associated
cultural identity, and ethnic pride. Again, related cultural discontinuity and deficit theory are
often cited to explain the Native experience in general (St. Germain, 1995). Figure Two
provides a visualization of the American Indian educational experience, and the dynamics and
intergenerational effects of historical trauma.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 32
Figure 2. Conceptual Framework for Intergenerational Historical Trauma
for Native Americans.
According to Newbreast (2011) and Yellow Horse Braveheart (2000, 2001, 2004),
historical trauma is the persisting condition of cultural shock for Natives including the
missionary and boarding school experiences, negative self-identify and learned helplessness, and
prescribed efforts to heal irrespective of a heterogeneous Native population and diversity of
experience. Policies of self-governance and self-determination likely play a role with tribes
having the opportunity to shape the educational destinies of their citizens. The conceptual
framework noted in Figure Two is directional and longitudinally modeled moving from top to
bottom with cultural and historical influences persisting from generation-to-generation with an
anticipated level of dilution over time. Theories of anomie, immigrant theory, historical trauma,
and U.S. Policies of Educational Self-Determination may be observable or articulated throughout
this study. The red circles labeled Z1 through Z4 refer to possible zones of cultural adaptation,
adherence or even resistance which may be observed. The last zone Z5 is undetermined as
increasing tribes have the financial wherewithal to set the direction of education and social
adaptation of their tribal citizens. This represents substantive opportunities for scholarship of an
advocacy or participatory action research nature.
Tribes are likely to be more critical consumers of research and will undoubtedly push for
substantive studies which are not ideologically one-dimensional. A burgeoning field that may
provide a scientific explanation to intergenerational trauma is that of epigenetics. Though
epigenetic study is biomedical and focuses on disease, the nature versus nurture argument
become inextricably intertwined as genetic precursors and social conditions explain behavior.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 33
An obvious overlap between neuroscience and education for example is Autism (Hopkins, 2011).
More pointedly, epigenetics seeks to isolate the conditions at which certain outcomes are
triggered. This might explain why some Native Americans succeed academically and others do
not. If Natives have a predisposition to say learning disabilities, and if certain environmental
conditions or events trigger manifestations of this predisposition, then discovering what these
triggers are becomes critical. Clearly not within the scope of this study or the literature search
conducted for this study, if there exists a common combination of factors to explain why Native
Americans have the highest drop-out rates, then irrespective of how offensive as it may seem,
keeping an open mind to epigenetics is a good idea as it may not only add credence to the notion
of historical trauma, but explain this seemingly perpetual state in Native America.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 34
CHAPTER III: METHODOLOGY
Quantitative Purpose and Research Questions
Again, the broad purpose of this research is to identify what factors influence educational
outcomes for Native Americans at both the high school and college level. More pointedly, for
Michigan Native Americans, this research will explore the extent to which school, personal,
family, and cultural factors influence high school graduation or general education development
(GED) attainment, high school graduating grade point average (GPA), and college graduating
grade point average. Further, differences that exist between Native Americans who earned their
college degree by way of earning a high school diploma versus those who attained their general
education development (GED) will be analyzed.
Conceptual framework: Quantitative
The conceptual framework used for the quantitative portion of this research borrows
largely from the comprehensive correlational / multiple regression study (noted in the literature
review section of this research, Sixkiller-Clarke, 1994) which collected over 140 variables that
fall fit into five broad categories. These are: personal factors (substance abuse, peer pressure,
trouble with the law, low self-esteem, teen pregnancy, motivation toward school, career plans);
family background (family composition, SES, welfare access and generation use, parental and
other family education levels, birth order and family dropout/graduation/college attendance and
graduation status, substance abuse, family education expectations); school factors (academic
achievement, teacher attitudes and expectations, school attendance, sports and extra-curricular
participation, abuse by school employee, engagement with high school guidance counselor,
integration with cohort or school); cultural factors (tribal identification, discrimination/racism
and from whom, bilingualism, per-capita dividend) and access factors (proximity to a tribal or
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 35
other community college, college, or university and any outreach, availability and participation
in Title VII Indian Education public schools or Johnson O’ Malley tribal programs. Given
concerns with sampling error with such a large variable population and the problem of small n in
studying Native Americans, the current study will minimize the number of independent variables
but borrow from the broad categories (personal, family, school, and culture).
Quantitative Research Design
This study will employ a quantitative non-experimental or quasi-experimental research
design (Creswell, 2009) utilizing primary research. Statistical tools allows for the manipulation
of variables, constructs and factors after the fact to: identify their relationships between
variables; determine what predictor/independent variables are associated with particular
outcomes (dependent variables); and later to discover and develop inferential models that explain
and predict educational outcomes for Native Americans. Given the unique challenges of the
problem of a small sample size (small n) (Bufferfield, 2003 as cited in Faircloth and
Tippeconnic, III, 2010) with studying American Indian populations, it is anticipated that use of
archival data like NCES datasets in later studies would allow for a review of the reliability of
various combinations of variables, constructs, or factors collected in historical archival data to be
compared against those planned for use in survey research. Operationalizing future studies to be
consistent with comprehensive data collected in national databases like the National Center for
Educational Statistics (NCES) on high school retention with the ability to sort by Native
American populations would allow for a level of reliability for comparisons in answering the
seven research questions between existing data collected over time versus data collected in this
primary research of Michigan Native Americans. If primary survey research instruments can be
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 36
articulated to match historical datasets, a simulated longitudinal effect may be gained for greater
insights into trends in Native American high school and college persistence rates and factors.
As a quasi-experimental or non-experimental design, research questions are used as
opposed to null and alternative hypothesis statements. The research questions (RQ) for this
study follow.
RQ1: Is there a difference between college graduating GPAs for the two subsets of the
population studied – high school graduates versus those who earned their GEDs?
RQ2: Do various pre-college and select college variables predict college graduating
GPA?
RQ3: Do select college variables and whether an individual earned a high school
diploma or GED predict college graduating GPA?
RQ4: What is the effect of all pre-college and all college variables on college
graduating GPA?
RQ5: Is any difference between high school GPA of those who graduate high school
versus those who earned their GED?
RQ6: What predictive values does all pre-college variables have on high school GPA?
RQ7: How well do these pre-college variables predict whether or not someone will
graduate with a high school diploma versus a GED?
Population
The population for whom this research intends to draw inferences is Native American
students at both the high school and college levels. More specifically, given there appears to be
no comprehensive primary educational research studies of MI Natives, the population of interest
is MI Native Americans who possess college degrees. Of particular interest is Natives who are
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 37
members of federally recognized tribes whose reservations are situated in Michigan. There are
twelve such tribes in Michigan from which to draw participants.
Small n problem in studying the Native American populations
A serious challenge to studying Native students is the problem of small n and with a
geographically dispersed population which results in many researchers not studying or reporting
Native statistics due to the statistical insignificance of the results (Butterfield, 2003 as cited in
Faircloth and Tippeconnic, 2010). In 2008, there were about 644,000 American Indian and
Alaska Native students in kindergarten through twelfth grade. About 92 percent attended regular
public schools with just 8 percent attending federal Bureau of Indian Education (BIE) or
individual tribal schools. In Michigan, there exists two BIE Tribal/ State of Michigan Public
School Academy Charter Schools. Native students are 46 percent more likely than their non-
Native counterparts to attend rural schools. Though Indian education is mostly a public school
issue, one-third of Native students attend school where at least 50 percent of the population is
Native (Faircloth and Tippeconnic, 2010).
Sample Size
The problem of the small n necessitates operationalizing several paths this research may
take. Inevitably, the sample population is a convenience sample that took on a snow ball effect
in data collection in order to ensure a sufficient sample size. The targeted sample size was set
based on RQ3 which has the largest number of variables to be collected at 18. In order to
minimize sampling error, using a multiplier of 20 respondents per variable, the number of survey
returns needed for RQ3 is an n = 360. In a conventional hard copy survey, using a projected
response rate of 30 percent, this would necessitate the production of 1,200 surveys. The second
highest number of variables is for RQ1 (15 variables) for a targeted number of returns at 300
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 38
necessitating the projection of 1,000 surveys. Depending on reliability analyses, these variables
are expected to be combined into no more than seven factors or constructs which allows us to set
the maximum responses as a target but not a steadfast rule. See Appendix A for calculations.
Given the retrospective nature of this research, it is important to note that typically
research may limit the elapsed time since earning their diploma or GED to five years. This is
noted as a serious challenge to the reliability of the results and is recognized as an area of
improvement for future studies. Additionally, the potential threat of sampling bias exists in the
manner in which surveys were collected. Given there is no known available repository of
available names of MI Native high school graduates or those who earned their GED, several
innovative techniques will need to be employed to get surveys to potential respondents. Suffice
it to say that the trade off of convenience sampling to ensure a sufficient sample size, is a
potential sampling bias through convenience sampling in a snow ball manner.
Data Collection
Data was collected using an instrument created for this purpose (see Appendix B) and
implemented using several distribution methods. A mailing was done and follow-up phone
calls and/or visits to MI tribal administrations for distribution in the twelve federally recognized
tribal offices which typically have a high traffic flow of their tribal members. Tribal
governments in Michigan were asked to promote completion of the survey through their
respective tribal newspapers, web pages, and through mass emails to their members. Tribal
education directors generally have the most reliable lists of members who are in college or have
earned college degrees given they administer tribally based scholarships. The survey was made
accessible through hard copy or through an electronic version using the on-line data collector
Survey Monkey (Survey Monkey, 2011). For those who completed a hard copy of the survey, the
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 39
results were individually inputted into Survey Monkey. Respondents were asked to forward the
Survey Monkey link to an electronic on-line version of the survey to other MI Natives who
earned their college degrees within the last ten years.
The anonymous survey collected general demographic information for all research
questions including gender, tribal membership, year of birth, year high school diploma was
earned or GED attained, and year of college graduation. The closest previous research found to
match the current research identified four major correlates to the incidence of Native American
persistence in high school (Sixkiller-Clarke, 1994). The following variables for the current
study were paired with the variables used by Sixkiller-Clarke: personal factors (substance
abuse, peer pressure, trouble with the law, low self-esteem, teen pregnancy); family factors
(family composition, socioeconomic status, parental education levels, older siblings – drop-out
or graduate, substance abuse); school factors (academic achievement, teacher attitudes, teacher
expectations, school attendance, abuse by school employee); cultural factors (tribal self-
identify/pride, discrimination/racism, bilingualism) Sixkiller-Clarke (1994, p. 72).
Variables
Table 4 lists factors, constructs, and variables for both the predictor/ independent and
independent and outcome/dependent variables. For each research question, Table 4 also denotes
whether each variable is categorical (discrete) or continuous and the level of measurement.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 40
Table 4
Proposed Factors, Independent and Dependent Variables for RQ1 through RQ4
Factor Value Label DV/ IV Measure
RQ 1 College GPA DV234 Scale
School High School Graduation or GED (used as IV) DV1 Nominal
RQ 2 College GPA DV 234 Ratio
ALL RQ7 Independent Variables plus…. IV1 thru IV15 Mixed
School High School Graduation or GED (used as IV) DV1 Nominal
School English, Math, Science, History, Social Studies GPA IV17 Scale
School College Admissions Status IV18 Nominal
RQ 3 College GPA DV234 Scale
School High School Graduation or GED (used as IV) DV1 Nominal
School English, Math, Science, History, Social Studies IV17 Scale
School College Admissions Status IV18 Nominal
Family College Financial aid IV19 Nominal
Family Loans IV20 Nominal
Cultural Michigan Indian Tuition Waiver IV21 Nominal
Cultural Tribal Scholarships IV22 Nominal
Cultural Natives Services IV23 Nominal
Cultural Multi-Cultural Office IV24 Nominal
RQ 4 College GPA DV234 Scale
All Pre-College IV (RQ7) + All College IV (IV17-IV24) Various Various
RQ 5 High School GPA IV17 Scale
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 41
High School Graduation or GED DV1 Nominal
RQ 6 High School GPA IV17 Scale
All Pre-College IV (RQ7) Various Various
RQ 7 High School Graduation or GED DV1 Nominal
Personal Be When You Grow Up IV1 Nominal
Family Family Income While Growing Up IV2 Ordinal
Family Highest Level of Education of Family IV3 Scale
Family Parental Expectations to Graduate IV4 Nominal
Family Family Substance Abuse IV5 Nominal
School Connection at Elementary, Middle and High School IV6 Ordinal
School Connection to Class Cohort IV7 Ordinal
School Change of Connection with Class Cohort IV8 Nominal
School Participated in Extra Curricular Activities IV9 Nominal
School School Intervention Available? IV10 Nominal
School Participate in School Intervention? IV11 Nominal
School Class Subjects Liked IV12 Ordinal
School Class Subjects Grades IV13 Scale
School School Type IV14 Nominal
Cultural Connection to Culture IV15 Ordinal
[Variable names and values for each variable appear in Appendix C]
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 42
Reliability assessment
The reliability of possible constructs or the combinations of variables that make up these
possible constructs was examined using PASW Statistics 18, Release Version 18.0.0 (PASW,
2009) reliability test feature. Given instrument construction and questions are very similar to
data collected by NCES (on a much smaller scale), the reliability of proposed constructs may be
compared against NCES datasets and reliability test results using PASW reliability test feature of
similar questions asked on NCES instrument. Though, no reliability statistic - alpha was
reported in the Sixkiller-Clarke study (1994), the results did not rule out any variables. For the
current research, the combinations of three or more variables in suspected combinations were
analyzed using the PASW Scale feature, selecting the reliability and scale item if deleted option
which shows the reliability of these questions taken together and how they could be improved
upon by omission of select variables.
The suggested constructs or combinations of variables at this stage included: personal
engagement at school (feeling of connection in school at the elementary, middle school and high
school level, feeling of connect with class cohort, and participation in school activities); school
engagement (interventions, attendance, like of class subjects, and grades per class subject); and
financial support (college financial aid, loans, Michigan Indian Tuition Waiver use, tribal
scholarship use). Additionally, any number of variables for each research question may
constitute a construct and the factors identified may result in broad constructs. Once the data
was collected, an analysis of all combinations of variables that make a factor was performed
using the PASW Scale feature noted previously.
Some of the constructs in the previous study which overlap with the current study have
some notable established reliability. For the variables - feeling of connection in school, class
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 43
cohort, and participation in school activities - combined as a construct, a reliable result was
found (= .81, M = 3.08, SD = .41). For the variables – college financial aid, loans, Michigan
Indian Tuition Waiver, and Tribal scholarships – combined as a construct found a reliable result
as well (= .70, M = 1.71, SD = .21). However, the variables – interventions, class subjects like,
class subject grades – combined found a close but less than reliable result (= .66, M = 13.33,
SD = 9) which doesn’t quite meet the (> .70) threshold to be combined as a construct. In
examining further the value of both the ratings of class subject like and class subject grades for
individual classes combined as constructs, these were found to be reliable with class subject like
(= .74, M =1.62 , SD = .06); and class subject grades (= .79, M = 3.19, SD = .20). The
reliability for ‘interventions’ could not be determined due the existence of just two variables.
The conclusion is that the variable interventions in high school does not fit with the other two
variables of class like and grades.
Limitations on Variables and Data Collected
The possible limitations of the data and method of collection include: collecting a
sufficient sample size; the ability of the respondent to recall information with a level of precision
given the retrospective nature of the data; and whether or not respondents answer questions
truthfully which is always a potential threat to any survey. To the extent this can be ameliorated,
a cover letter stressed the importance of answering all questions truthfully and with the greatest
level of recall possible. In order to ensure that a sufficient sample size was drawn from the
respective high school graduation and GED attainment populations, the length of time for
retrospective data collection was extended beyond a standard five year period. It is understood
and noted that longer than this period represents a threat to the validity and reliability of the data
recollected.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 44
Quantitative Analytical method
Preparatory work moving from data collection to analysis
Survey responses were collected via Survey Monkey with data downloaded into Microsoft
Excel 7.0 (2007) then uploaded into PASW for descriptive and inferential statistical data
analyses. The data collection period predated a recent Survey Monkey feature which
automatically encodes data from the on-line survey into SPSS. For this research, this was done
manually and painstakingly for approximately 200 data points. When downloading from Survey
Monkey to Excel 7.0, the variable names are preserved in column headings. Once uploaded into
PASW, the column headings serve as variable names. For each variable, value labels were added
for ease of use and for displaying results. Variables were encoded as either numeric or string
variables; level of measurement; and values assigned to selection of options within each variable.
Appendix C displays this information for all variables used in this research.
As part of the preparatory work for running analyses, the distribution of variables was
examined for the relative normality of each distribution using the PASW frequencies command.
In doing so, the distribution of the data for each variable was checked against the normal
distribution using the means, standard deviations, standard errors, kurtosis and skew, and
z-scores to detect if there are any outliers that necessitated making alternative arrangements like
setting the outlier value to the lowest or highest within + or - three standard deviations from the
mean value. This is an important step in order to gauge whether or not corrections need to be
made for non-normally distributed data. The results from frequency tables runs serves as the
basis for reporting ‘descriptives’ in the results to aid the reader in visualizing the data.
Additional general data runs were conducted to better understand the data and possible
relationships among variables using: the PASW Correlations – bivariate function selecting
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 45
flagging significant correlations among all variables; an analysis of variance between the
outcome/dependent variables and predictor/independent variable for each research question
using PASW Compare Means – ANOVA function selecting posthoc, tukey table to test for
significance of variances, homogeneity of variance test, and means plots to better understand
how the means differ.
Deciding on appropriate statistical tests
The most important aspect of moving from data collection to data analyses is interpreting
which statistical test to use. Table 4 listed the nature of the data for each variable used in this
research as either categorical (discrete) or continuous. This information is necessary to
determine the statistical test to use. According to Field (2009) and Mertler and Vannatta (2010),
answering a few simple questions reveals the appropriate test to use. These questions ask how
many outcome/dependent or dependent variables are used in each research question. Whether or
not the outcome/dependent or dependent variable is continuous or categorical and how many
predictor/independent variables there are at either one or two (or more) is asked. Next, what type
of predictor/independent variable(s) is(are) used and how many categories does each
predictor/independent variable fit into is decided? Finally, answering whether or not each
predictor/independent variable has the same or different participants and whether the data meets
parametric assumptions, determines which analytics to use. The following includes the
responses to each of these questions Field (2009) poses and therefore which statistical tests were
selected for use for RQ1 through RQ7.
RQ1: The number of dependent variables is one. The nature of the dependent variable is
continuous as college graduating GPA is any number between 0.00 and 4.00 depending
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 46
on the grade point average system at their respective college. There is one predictor/
independent variable that is categorical with two categories that also differentiate the
different populations (high school graduation versus GED attainment) and the data meets
the parametric assumptions so the statistical test to use is an independent t-test.
RQ2: The number of dependent variables is one. The nature of the dependent variable,
college graduating GPA, is continuous. There are eighteen predictor/independent
variables that are both continuous and categorical with different populations
(differentiated by high school graduation or GED attainment) and the data meets the
parametric assumptions so the statistical test to use is multiple regression.
RQ3: The number of dependent variables is one. The nature of the dependent variable,
college graduating GPA, is continuous. There are nine predictor/independent variables
that are both continuous and categorical and the data meets the parametric assumptions so
the statistical test to use is multiple regression.
RQ4: The number of dependent variables is one. The nature of the dependent variable,
college graduating GPA, is continuous. There are twenty four predictor/independent
variables that are both continuous and categorical and the data meets the parametric
assumptions so the statistical test to use is multiple regression.
RQ5: The number of dependent variables is one. The nature of the dependent variable is
continuous as high school GPA is any number between 0.00 and 4.00 depending on the
grade point average system at their respective college. There is one predictor/
independent variable that is categorical with two categories that also differentiate the
different populations (high school graduation versus GED attainment) and the data meets
the parametric assumptions so the statistical test to use is an independent t-test.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 47
RQ6: The number of dependent variables is one. The nature of the dependent variable,
high school GPA, is continuous. There are fifteen predictor/independent variables that
are both continuous and categorical and the data meets the parametric assumptions so the
statistical test to use is multiple regression.
RQ7: The number of dependent variables is one. The nature of the dependent variable is
categorical as either possessing a high school diploma or GED. There are 15 predictor/
independent variables that are both continuous and categorical with different populations
(differentiated by high school graduation or GED attainment) so the statistical test to use
is logistical regression.
Decision factors for research questions
RQ1 and RQ5 are likely the most straight forward statistical test to conduct and interpret.
The independent t-test, should show whether or not the two groups are different with respect to
their mean high school and college graduating GPAs. The null hypothesis is stated that there is
no difference (to minimize Type I error) or that the means are equal. If the associated
significance value is (p < .05) for a 95 percent confidence interval for the t statistic, then we
reject the null and conclude that mean graduating college GPAs are different for those who
graduated high school with a diploma versus a GED. Conversely, typically, if the p value is not
significant (p > .05), then we fail to reject the null and conclude that the high school or college
graduating GPAs for the respondents is not significantly different for those graduated with a high
school diploma versus a GED.
RQ 2, RQ 3, RQ 4, and RQ6 were analyzed using a multiple regression analysis.
Multiple regression is simply the selection of several independent variables used as
regressors (using PASW regression feature and select linear regression) to find the
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 48
regression equation that best explains the role of the predictor/independent variables and
the extent of their effect per predictor/ independent variable unit change in the
outcome/dependent variable (Field, 2009). For RQ 2, RQ 3, RQ 4, and RQ6, the relative
effect of various predictor variables for personal, family, school and cultural factors have
on MI Native American college graduating GPAs will be explained.
For RQ 7, a logistical regression was the statistical test selected. Using PASW, select the
regression feature and choose the binary logistical regression option and display at each step
among other options. For linear regression equations like:
Y = + 1X1 + 2X2 + 3X3 + …k Xk +
the value of the beta coefficient or represents the change and significance in the
outcome/dependent or dependent variable resulting from a unit change in the
predictor/independent variable. The value reported in logistical regression is similar but
represents the change in the logit of the outcome/dependent variable associated with a one unit
change in the predictor/independent variable (Field, 2009). The sequential process in a logistical
regression begins with the constant at step zero and examines the value of including each
additional predictor/independent variable for increasing the overall predictability of the
regression model. In other words, the results indicate whether or not the model including the
predictor/independent variables is significantly better than without those predictor/independent
variables. For RQ7, the decision factor will be in determining at what step each of the 15
predictor/independent variables holds some value on predicting the outcome/dependent or
dependent variable. The response to RQ7, will take the form of the results for individual
predictor/independent variables, as well as, the overall model that best fits an explanation of the
outcome which is either obtaining a high school diploma or a GED.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 49
Quantitative Methodological limitations
Again with the population of American Indians at about 1.5 percent of the total United
States population means that the problem if the small n is always in play. Fractioning this
population further through various sorts decreases the likelihood of a sufficient sample size.
Natives are generally a transitory population which makes studying this population difficult.
Swisher & Hoisch (1992) and St. Germaine (1995) note the incidence of Native American
student transfers confounding the calculation of Native student retention. This is not to suggest
that transferring is detrimental, but that continuity of data collection is interrupted. Finally, one
of the limitations of the quantitative paradigm, is though we can establish accurate baseline data
to begin to project hypotheses to explain relationships among variables, the small n and the
heterogeneity of the population of Native Americans resists simple or convenient classifications.
Potential Researcher Subjectivity (Bias)
Any researcher carries a bias in the manner in which they interpret what they see.
Disclosing inherent biases and how these will be managed, promotes transparency in order to
rely on the objectivity of the researcher. For this study, the researcher has a clear advocacy/
participatory (Creswell, 2009) motivation for studying the Native high school dropout crisis. As
a Native who dropped out of high school but went on to earn a graduate education, the researcher
has a firmly held belief that given the right academic opportunity, most all students can achieve
academic success. Borrowing from the literature, an organizational/systems view suggests
deficiencies exist in public education that continue to fail Natives. The researcher agrees with
both constructivist (social historical) and sociological/anthropological theories that explain how
Natives enter the school system (lower SES, high rates of poverty, poor nutrition, poor cognitive
preparation, undiagnosed special education needs, etc.) effects their propensity to succeed.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 50
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 51
CHAPTER IV: RESULTS
Quantitative Findings
What follows is a comprehensive listing of the results and various analytics to address
each research question posed. First, descriptive will be shared to give a general birds-eye view
of the data with respect to their distributions. Next, both frequencies distributions and an
interpretation of this data using t-tests and ANOVA where appropriate are used to appreciate the
differences between the two populations research – namely high school graduates versus GED
recipients. Finally, the results of each research question are presents with the appropriate
statistical test ranging from t-tests, to multiple regression, and logistical regression where
appropriate.
Descriptive statistics and frequencies
What follows in Table 5 is a summary descriptive statistics to give a glimpse of the
nature of the data including the dispersion and frequencies.
Table 5
Descriptive Statistics for all Variables
N Min. Max. Mean Std. Deviation
High School Graduation or GED 300 1 2 1.12 .326
College GPA 265 2.00 4.00 3.35 .477
Be When You Growing Up 300 1 3 1.61 .514
Family Income While Growing Up 300 1 5 2.39 .856
Recoded for Family Education 296 1 22 13.49 4.140
Parental Expectation to Graduate 300 1 3 1.20 .499
Family Substance Abuse 300 1 3 1.65 .562
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 52
Connection (K-12) 300 1 5 2.52 .901
Connection to Class Cohort 281 1 5 3.24 1.441
Change of Connection with Class Cohort 300 1 3 1.79 .687
Participated Extra Curricular Activities 300 1 2 1.14 .351
School Intervention Available 300 1 2 1.69 .465
Table 5
Descriptive Statistics for all Variable (cont.)
N Min. Max. Mean Std. Deviation
Participate in School Intervention 300 1 2 1.85 .354
Class Subjects Liked 300 1 6 3.84 1.284
Class Subjects Grades 300 1 4 3.54 .719
IV14SCHtypeKthru12 300 1 4 2.81 .513
Connection to Culture 300 1 5 2.08 1.297
Eng., Math, Sci., History, Social Studies GPA 296 .40 4.00 3.03 .715
College Admissions Status 300 1 3 1.27 .641
College Financial Aid 300 1 3 1.59 .690
Loans 300 1 3 1.64 .726
Michigan Indian Tuition Waiver 300 1 3 1.80 .684
Tribal Scholarships 300 1 3 1.93 .690
Native Services 300 1 3 2.03 .817
Use Services at Multi-Cultural or NA Office 300 1 4 2.30 1.024
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 53
The full frequency distributions and default graphs are appended (F) as a separate PASW Output
file. Graphs depicting significant differences between High School Graduates versus those who
earned their GEDs are show in Appendix G.
Visual Inspection of Data with t-Test and ANOVA Confirmations
PASW (2009) formerly SPSS, has features that provide any number of ways to display
data. One such way is through the production of graphs to show differences or similarities
between respondent groups. The two main populations examined in this study are Michigan
Natives who complete high school with a diploma versus those who earned their GEDs. To
appreciate comparisons among these two groups, totals for each legend variable category in the
Chart Builder feature was selected to show the relative percentages for each separate group with
bar codes lined up side by side with the comparison group. Using the independent variable
which asked whether or not individuals knew what they wanted to be when they grow up (IV1)
for example, the responses were: 1=Yes; 2 = No; 3=Don’t Know. The percent who responded yes
for the two main populations (High School Graduate versus GED recipient) are displayed side by
side. Then, those who reported no are displayed side by side with those who responded don’t
know following. A visual inspection of the data suggests there is a distinct difference in the two
populations on several response items. What follows is a brief descriptive narrative of these
differences followed by a more robust analysis including the use of t-test and ANOVA tests to
determine if these differences are indeed significant. For variables with more than two response
categories, an ANOVA was used while those variables that have dichotomous responses, a t-test
was used. All 24 graphs appear in Appendix G.
For the variable question which asked if the respondents knew what they wanted to be
when they grow up (IV1), there was no appreciable difference. With respect to the variable
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 54
family income while growing up (IV2) there appears to be a difference with GED recipients
reporting a total low income of 69% versus high school diploma recipients at 51%. Twenty eight
percent of GED recipients reported middle income versus 44% for high school diploma
recipients. Thus, GED recipients appear to be from a lower socio-economic class than high
school diploma recipients. Given, there are more than two response categories for this variable,
however, an ANOVA was used to determine if these differences are significant. The results
show that there is a significant difference with respect to income between the groups F(4,295) =
4.17, p < .01, r = .23(2
=.04) which represents a small effect size (Kirk, 1996 as cited in
Field, 2009, p. 390) with the significant differences appearing in the following table:
Table 6
Mean Differences of Family Income While Growing Up (IV2) Between Respondent Groups
1 2 3 4 5
1 Very Low -
2 Low .185* -
3 Medium .210* .026 -
4 Upper .089 -.096 .121 -
5 Don’t Know .289 .104 .200 .200 -
* p < .05
Looking at educational attainment as represented in the variable family education (IV3),
there appears to be no appreciable difference between the two groups. With respective to
parental expectation of the respondent to graduate high school (IV4), however, there appears to
be a difference with 88% of high school graduates reporting yes, while 53% of GED earners
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 55
reporting yes – a 35% spread. Treating the don’t know response as missing values in order to run
a t-test, we see those who earned their GEDs (M=1.39, SE =.09) was significantly lower than
those who graduated high school (M=1.09, SE=.02) t(32) = -3.277, p < .01 and an effect size of
50%.
A visual inspection of IV5 (family substance abuse) 37% of high school graduates
reported someone in the immediate family with a substance abuse problem while the respondent
was growing up versus 58% for GED recipients, a 21% difference. Using a t-test, the mean of
responses for GED recipients (M=1.40, SE=.08) was significantly lower that for high school
graduates (M=1.61, SE=.03) t(285) = 2.391, p < .05 with an effect size of 14%. Recall that 1 =
yes a family member had a substance abuse problem and 2 = no.
With respect to a student’s connection or engagement in school (IV6), with their class
cohort (IV7) or any changes in connection with their class cohort (IV8) and participation in
school activities (IV9) a visual inspection appears to show differences. GED recipients report a
total low connection with school (IV6) at 83% while those who earned high school diplomas at
46%. Neither of these statistics are particularly encouraging given a level of disconnection or
disengagement of Native students overall in school. Applying an ANOVA, we see that these
differences are significant F(3,296) = 10.426, p < .001, r = .31(2
=.08) which represents
a medium effect size. Given there was only one respondent who reported a high connection to
school, this response category was collapsed into somewhat high & high. The significance
appears in the following table:
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 56
Table 7
Mean Differences of School Connection (IV6) Between Respondent Groups
1 2 3 4
1 Low -
2 Somewhat Low .192* -
3 Moderate .285* .093 -
4 Somewhat High & High .342* .150* .057 -
* p < .05
Connection class (IV7) shows some startling differences between the two groups with a
70% of GED recipients reporting a total low connection versus a total low connection of high
school graduates at 28% . This difference is significant F(4,276) = 12.896, p < .001, r = .40
(2
=.15) which represents a large effect size.. The respective differences are shown in
the following table:
Table 8
Mean Differences of Connection to Class Cohort (IV7) Between Respondent Groups
1 2 3 4 5
1 Low -
2 Somewhat Low .287* -
3 Moderate .253* -.034 -
4 Somewhat High .327* .040 .074 -
5 High .346* .060 .094 .020 -
* p < .05
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 57
With respect to any changes in the student’s connection to their class cohort (IV8), 50%
of GED recipients reported that there was a period in their education when there was a change in
their connection to class versus 34% for high school graduates. Applying a t-test to see if this
difference is significant, we see that it is with GED (M=1.33, SE=.09) versus high school
diploma (M=1.60, SE=.03) t(252) = 2.713, p < .01 with an effect size of 17%. Finally, 64% of
those who earned a GED reported participating in extra-curricular activities (IV9) while 89% of
the high school graduate group reported participation. The t-test borne out the significance of
these results as well with GED (M=1.36, SE=.08) and high school graduates (M=1.11, SE=.02)
t(39) = -.2.963, p < .01 with an effect size of 43%.
For the variables school intervention available (IV10), participate in school intervention
(IV11), class subjects grades (IV13), school type (IV14), and connection to culture (IV15) there
doesn’t appear to be any appreciable difference between the high school graduates versus GED
recipients. A visual inspection of class subjects liked (IV12) appears to show differences
between the two groups and an ANOVA test does show a significant differences at the .05 level,
F(4,235) = 2.408, p < .05, r = .21(2
=.02) which represents a medium effect size.
However, post hoc analysis though the application of a Tukey table does not show any
significance individuals differences in the table below.
The mean difference in academic grade point average (IV17) for high school graduates
versus GED recipients appears significant and a t-test bears this out with GED recipients
(M=2.51, SE=.12), high school graduate (M=3.09, SE=.04) t(294) = 4.588, p< .01 with an effect
size of 26%. Given GED recipients reported lower grade point averages and dropped out of high
school (potentially before SAT and ACT exams), it is intuitive that their college admissions
(IV18) would show a distinction between the two groups. A graphical depiction of the
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 58
differences shows that 86% of high school graduate respondents entered college under regular
admissions and 67% of the GED recipients entered college under regular admissions. This
difference, however, is not significant with GED recipients (M=1.11, SE=.06) and high school
graduates (M=1.05, SE=.02) t(29) = -.903, p >.01 (.374).
Table 9
Mean Differences of Class Subjects Liked (IV12) Between Respondent Groups
1 2 3 4 5
1 Did Not Like -
2 Moderate Dislike .100 -
3 Neutral .249 .149 -
4 Moderately Liked .258 .158 .009 -
5 Really Liked .333 .233 .084 .075 -
* p < .05
Regarding variables at the college level we also see some notable differences between
high school graduates versus those who earned their GED. First, high school graduates reported
accessing financial aid (IV19) at a rate of 50% versus GED recipients at 67% marking a 17%
difference. This difference is significant with GED recipients (M=1.17, SE=.07) and high school
graduates (M=1.44, SE=.03) t(263) = 2.759, p < .01 with an effect size of 47%. Access and use
of loans (IV20) between the two groups, however, shows no difference. The remaining college
variables show differences. Those who accessed and used the Michigan Indian Tuition Waiver
(IV21) - a State of Michigan program which provides full tuition funding for Michigan Natives
who are residents of Michigan for at least one year who have at least ¼ certified Indian blood -
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 59
shows a difference with GED recipients receiving the waiver at 53% versus 33% for high school
graduates, a 20% difference which is significant with GED recipients (M=1.32, SE=.09) and high
school graduates (M=1.62, SE=.03) t(252) = 3.013. p < .01) with an effect size of 19%. There
was also a discernable difference in those who received tribal scholarships (IV22) with 26% of
high school graduates versus 39% of GED recipients receiving tribal scholarships which
represents a significant difference with GED recipients (M=1.42, SE=.10) and high school
graduates (M=1.68, SE=.03) t(237) = 2.586, p < .01 with an effect size of 17%.
Finally, there were differences with respect to students who accessed Native (IV23) -
47% versus 30% respectively for GED recipients versus high school graduates - and Multi-
Cultural services (IV24) - 39% versus 17% respectively for GED recipients versus high school -
while in college. These difference in use of Native services in college are not significant at the p
< .05 or .01 level but are at the .07 level with GED recipients (M=1.35, SE=.10) and high school
graduates (M=1.54, SE=.04) t(34) = 1.874, p < .07 with an effect size of 31%. There was a more
definitive difference in those who accessed the services of the multi-cultural affairs office at their
respective colleges with GED recipients (M=1.42, SE=.10) and high school graduates (M=1.76,
SE=.03) t(27) = 3.228, p < .01) with an effect size of 53%.
Correlations
With twenty four independent and two dependent variables and the resulting 676
different pairings, there are too many correlations to give each individualized attention here.
There is some value, however, in looking at the strongest effect sizes of correlations in order to
decipher relationships among variables identified. One hundred and one variable pairs had
significant correlations with 35 pairings at the p < .05 level and 66 at p < .01 level. The
following will summarize those pairings of variables that have significant correlations and effect
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 60
sizes greater than or equal to 15% which translates to a correlation of nearly .39. Then those
with effect sizes at or greater than 10% up to 15% will be presented. This review provides a
simple review of the relationships of variables. The full correlations matrix is appended (E).
A student’s connection to their class cohort (IV7) is positively correlated with their
connection with school (IV6) across the all grade levels, r = .72, p < .01 and a 52% effect size
(i.e. variance in connection with school explained by a student’s connection to class). Not
surprisingly, the extent to which a student participates in school interventions during high
schools (IV11) is positively correlated with the availability of school interventions (IV10), r =
.614, p < .01 with a 38% effect size. Again, somewhat tautological, whether or not a student
received college financial aid (IV19) is positively correlated with their acceptance into college
(IV18), r = .420, p < .05 with an effect size of 18%. Whether or not a student receives college
loans (IV20) is positive correlated with their acceptance into college (IV18), r = .504, p < .05
with an effect size of 25%. Whether or not a student receives tribal scholarships (IV22) to
support attending college is positive correlated with their acceptance into college (IV18), r =
.415, p < .01 with an effect size of 17%. The use of the multi-cultural affairs office (IV24) is
positively correlated with their acceptance into college (IV18), r = .382, p < .05 with an effect
size of 15%. Correspondingly, the correlation for a student’s use of the Native student services
office is r = .309, p < .01 with an effect size of 10% and a student’s use of the multi-cultural
affairs office (IV24) is positively correlated with their use of a college’s Native office (IV23), r =
.465, p < .01 with an effect size of 22%. This is not surprising given these offices are often one
and the same, located in adjoining offices, or affiliated through organizational planning. A
student’s use of college loans (IV20) is positively correlated with their accessing financial aid
(IV19), r = .579, p < .01 with an effect size of 34%. Whether or not a student receives a tribal
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 61
scholarship (IV22) to support college is positively correlated with receipt of college loans
(IV20), r = 494, p < .01 and whether or not they received the Michigan Indian Tuition Waiver
(IV21), r = .401, p < .01 with effect sizes of 24% and 18% respectively.
Moderate positive pairings of variables with correlations greater than r = .30 and less
than .39 with effect sizes greater than or equal to 10% but less than 15% follow. Participation
in school extra-curricular activities (IV9) is negatively correlated with a student’s connection to
their class cohort (IV7), r = -.333, p < .01 with an effect size of 11%. Interpreting this is difficult
as it seems counterintuitive as it seems that the more involved in extra-curricular activities a
student is, the more connection they would have with their class cohort unless what is being
captured is a level of participation that lessens opportunity for leisure involvement with class
cohorts. A student’s high school academic grade point average (IV) is positively correlated with
their connection with school (IV6) and connection to their class cohort (IV7), r = .317 and r =
.309, p < .01 with effect sizes of 10% respectively. Again, not surprisingly, the grades a student
receives in high school per class subject (IV13) is positively related to how well they liked their
class subjects (IV12), r = .360, p < .01 with an effect size of 13%. A student’s use of the
Michigan Indian Tuition Waiver (IV21) is positively correlated with their acceptance to college
(IV18), and their use of college financial aid (IV19) and loans (IV20), r = .366, .330, .311, p <
.01 with effect sizes of 13%, 11%, and 10% respectively. Additionally, a student’s use of tribal
scholarships (IV22) is positively correlated with their use of college financial aid (IV19), r =
.352, p < .01 with an effect size of 12%. This is not surprising given tribal scholarships are
typically considered last resort funding with a recommendation made after all other forms of gift
assistance are applied and a recommendation made to the tribe by the college financial aid office.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 62
A student’s reported use of their college’s Native office (IV24) is positively correlated
with acceptance into college (IV18), use of financial aid (IV19), and use of the Michigan Indian
Tuition Waiver (IV21), r = .309, .327, .311, p < .01 with effect sizes of 10%, 11% and 10%
respectively. It is also worth noting that both access to student loans (IV20) and tribal
scholarships (IV22) are positively correlated with use of the Native office (IV24), r = .280, .289,
p < .01 [effect size 8% respectively]. Additionally, a student’s use of the multi-cultural affairs
office (IV24) is positively correlated with their accessing financial aid (IV19), student loans
(IV20) and the Michigan Indian Tuition Waiver (IV21), r = .335, .329, .365, p < .01 with effect
sizes of 11%, 11% and 13% respectively. Taken together with the larger correlations and effect
sizes reported earlier for this combination of variables between accessing services and the multi-
cultural or Native office, the critical importance and value of these offices as a hub of service
delivery is underscored.
RQ1 Results – College Graduating GPA between High School Graduates versus GED
Earners
Is there a significant difference in college graduating GPAs between MI Natives who
graduated from high school versus those who attained their GEDs? The independent t-test,
should show whether or not the two groups are significantly different with respect to their mean
graduating college GPAs. The null hypothesis is stated that there is no difference (the means are
equal). In order to conduct a the independent t-test, we needed to first determine if the
homogeneity of variance is assumed using Levine’s test (Field, p. 152). The results indicated
that the assumption was not violated with F(1,261) = .32, ns, p > .05 [p=.56]. The results of the
t-test showed the average college GPA of respondents who earned their GEDs (M=3.37, SE =
.09) was higher than the average college GPA of those who earned high school diplomas
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 63
(M=3.35, SE .03). The difference between the two mean GPAs, however, was not significant
t(263) = -.269, p > .05 (.788), and had a very low effect size at r = .02. Given the associated
significance value is (p > .05) for a 95 percent confidence interval for the t statistic, we fail to
reject null and conclude that mean college graduating GPA for respondents is not significantly
different for those who graduated high school versus those who attained a GED.
RQ2 Results – All Pre-College and Select College Independent Variables on College GPA
Regression results indicate an overall model of eighteen predictor variables that in
combination significantly predict college GPA, R2 = .145, R
2adj = .077, F(18,228) =2.140, p <
.001 with IV12 (Class Subjects Liked), IV15 (Connection to Culture), DV1 (high school
graduate or GED), IV17 (Academic GPA in high school) having significant predictive value at p
< .10 or lower. This model accounted for 14.5% of the variance in college GPA’s. A summary
of the regression model is presented in Table 1. The unstandardized and standardized
coefficients and standard error between each predictor and dependent variable are presented in
the table below.
Table 10
RQ2 Coefficients for Final Model
B β S.E.
IV1 -.019 -.020 .060
IV2 -.024 -.041 .040
IV3 -.009 .078 .007
IV4 .068 .072 .064
IV5 -.028 -.034 .054
IV6 .021 .039 .051
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 64
IV7 -.003 -.009 .032
IV8 -.061 -.086 .045
IV9 -.053 -.038 .096
IV10 .015 .015 .084
IV11 .107 .079 .110
IV12 -.045*** -.119 .027
IV13 .046 .067 .050
IV14 .022 .023 .066
IV15 .043** .112 .025
DV1 .193*** .125 .110
IV17 .184* .266 .050
IV18 -.075 -.065 .079
* p < .001, ** p < .05, *** p < .10
RQ 3 - High School Graduate or GED and Select College Independent Variables on college
GPA
Regression results indicate an overall model of nine predictor variables that in
combination significantly predict college GPA, R2 = .112, R
2adj = .080, F(9,252) =3.523, p < .001
with DV1 (high school graduate or GED), IV17 (Academic GPA in high school), and IV24 (Use
of the Multi-Cultural Affairs Office in college) having some predictive value at p < .10 or lower.
This model accounted for 11.2% of the variance in college GPA. A summary of the regression
model is presented in Table 1. The unstandardized and standardized coefficients and standard
error between each predictor and dependent variable are presented in Table 11.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 65
Table 11
RQ3 Coefficients for Final Model
B β S.E.
DV1 .185*** .121 .099
IV17 .198* .290 .044
IV18 -.113 -.100 .076
IV19 .011 .014 .055
IV20 .041 .054 .054
IV21 -.006 -.008 .049
IV22 .009 .012 .049
IV23 .021 .035 .040
IV24 .064** .127 .033
* p < .001, ** p < .05, *** p < .10
RQ4 - All Pre-College and All College Independent Variables on College GPA
Regression results indicate an overall model of 24 predictor variables that in combination
significantly predict college GPA, R2 = .168, R
2adj = .079, F(24,222) = 1.873, p < .01 with DV1
(high school graduate or GED), IV12 (class subjects liked), IV15 (connection to culture), and
IV17 (Academic GPA in high school) having some predictive value at p < .10 or lower. This
model accounted for 16.8% of the variance in college GPA. A summary of the regression model
is presented in Table 1. The unstandardized and standardized coefficients and standard error
between each predictor and dependent variable are presented in the following table:
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 66
Table 12
RQ4 Coefficients for Final Model
B Β S.E.
DV1 .220** .142 .112
IV1 -.031 -.034 .061
IV2 -.022 -.038 .041
IV3 .009 .078 .007
IV4 .064 .068 .064
IV5 -.045 -.054 .056
IV6 .017 .031 .052
IV7 -.001 -.002 .032
IV8 -.060 -.085 .046
IV9 -.069 -.049 .100
IV10 .024 .023 .085
IV11 .044 .032 .114
IV12 -.0528** -.137 .027
IV13 .036 .053 .050
IV14 .027 .028 .067
IV15 .0448** .115 .026
IV17 .194* .279 .051
IV18 -.099 -.086 .082
IV19 .034 .040 .060
IV20 .043 .056 .057
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 67
IV21 .000 .000 .053
IV22 .020 .026 .055
IV23 .031 .050 .043
IV24 .048 .093 .036
* p < .001, ** p < .05, *** p < .10
RQ5 Results – High School GPA between High School Graduates versus GED Earners
Is there a significant difference in high school GPAs between MI Natives who graduated
from high school versus those who attained their GEDs? The independent t-test, should show
whether or not the two groups are significantly different with respect to their mean high school
GPAs. The null hypothesis is stated that there is no difference (the means are equal). The results
of the t-test showed the average high school GPA of respondents who earned their GEDs
(M=2.51, SE=.12) was lower than the average college GPA of those who earned high school
diplomas (M=3.09, SE=.04). The difference between the two mean GPAs was significant t(294)
= 4.588, p< .01 with an effect size of 26%. Given the associated significance value is (p < .05)
for a 95 percent confidence interval for the t statistic, we reject null and conclude that mean high
school GPA for respondents is significantly different (greater) for those who graduated high
school versus those who attained a GED.
RQ6 - All Pre-College Independent Variables on High School GPA
Regression results indicate an overall model of 15predictor variables that in combination
significantly predict high school GPA, R2 = .230, R
2adj = .185, F(15,258) = 5.141, p < .001 with
IV1 (be when you grow up ), IV6 (connection in school), IV7(connection to class cohort), IV8
(change in connection to class cohort), IV13 (class subject grades), IV14 (school type), and IV15
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 68
(connection to culture) having some predictive value at p < .10 or lower. This model accounted
for 23% of the variance in high school GPA. A summary of the regression model is presented in
Table 1. The unstandardized and standardized coefficients and standard error between each
predictor and dependent variable are presented in the following table:
Table 13
RQ6 Coefficients for Final Model
B β S.E.
IV1 -.052** -.038 .078
IV2 .033 .040 .048
IV3 .003 .021 .010
IV4 .014 .010 .080
IV5 .025 .020 .073
IV6 .121*** .156 .063
IV7 .066*** .137 .040
IV8 .1218** .117 .058
IV9 -.188 -.092 .122
IV10 -.063 -.042 .104
IV11 -.105 -.053 .140
IV12 -.029 -.053 .034
IV13 .181* .184 .061
IV14 .233* .176 .078
IV15 .059*** .109 .031
* p < .001, ** p < .05, *** p < .10
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 69
RQ7 - Pre-College Independent Variables on High School Graduation versus GED
Forward logistic regression was conducted to determine which pre-college independent
variables were predictors of graduating high school versus obtaining a GED. Regression results
indicated that the overall model of just two of the fifteen predictors (parental expectation to
graduate and a student’s connection to their class cohort) were statistically reliable in
distinguishing between which outcome was more likely – earning a high school diploma versus a
GED (-2 log likelihood = 145.088, 2(2) =114.908, p < .001). The model correctly classified
89.2% of the cases. Regression coefficients are presented in the following table. Though, the
Wald statistics indicate that both variables significantly predict high school graduation versus
GED, the odds ratio for these variables indicate little change in the likelihood of high school
graduation versus GED.
Table 14
RQ7 Coefficients for Final Model
B Wald df
p Odds
Ratio
Parental Expectation to Graduate 1.096 11.718 1 .001 2.993
Connection to Class -.857 22.019 1 .000 .424
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 70
CHAPTER V: CONCLUSIONS
Conclusions
We began our inquiry with the intent of finding factors for conditions which influence
whether Michigan Native Americans surveyed graduated with a high school diploma or earned a
GED, and to determine if differences exist on key outcomes like high school and college grade
point averages. Though the outcome of this research is enlightening with notable and significant
differences, the election of variables to study did not result in findings in which to build a
comprehensive intervention strategy through the use of regression results. There are notable
differences between high school graduates and GED recipients in several pre-college variables
for which school administrators may want to dedicate some attention. When interpreting results
of the first research question – whether or not there is a difference in college graduating GPAs
between high school graduates and GED recipients, we do note that the college GPA for the
GED recipients. Again, however, the difference is not significant. This finding itself is a
revelation in that when we look back at the high school GPA differences between these two
groups, we do see a difference with an inverse outcome with high school graduates having a
significantly higher GPA than their counterparts who earned a GED. It would be logical to
assume the college GPAs for GED earners would also be significantly less than for high school
graduates. This is, however, not the case. The fact that GED recipients have higher GPAs (or
statistically equal) lends support to Tribal GED preparation programs which exist to ameliorate
the reality of the high drop-out rate for Natives at nearly 50%.
With respect to research questions two, three, four and six, we did see an increasingly
greater amount of variance in outcome variables explained by combinations of select
independent variables. This is encouraging as it identifies factors or conditions for which
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 71
educational administrators can try to facilitate the introduction or withholding of various
variables that effect educational outcomes for Michigan Natives. For example, though not a
large percentage, 14.5% of the variance in college GPA explainable by class subjects liked,
connection to culture, whether or not an individual earns a high school diploma or GED and the
students respective high school GPA, provides college administrators with some level of data to
affect the retention rate of Native American students. The combination of independent variables
high school graduate or GED recipients, high school GPA, and the use of the college multi-
cultural affairs office explains 11.2% of the variance in college GPA. Though college
administrators cannot control the first two variables, they can underscore the value of services to
minority populations and the utility this has for Michigan Natives. Admittedly, research
question four has some reliability concerns with only 300 survey respondents yet a projected 360
needed. Nonetheless, with 16.8% of the variance in college GPA explainable through a
combination of pre-college and college independent variables like high school graduate or GED
recipient, class subjects liked, connection to culture, and academic GPA in high school, this
provides college administrators with information in which to program interventions. Research
question six provides the greatest level of predictability with 23% of the variance in high school
GPA with be when you grow up, connection to school, connection to class cohort, change in
connection to class cohort, class subject grades, school type, and connection to culture all
playing a significant role in predicting high school GPAs. Intervention strategies which monitor
a student's feelings of being connected at school and offers options to facilitate a greater level of
connection hold promise for higher graduating GPAs. Identifying, the point at which students
feel this change is the point at which intensive interventions should be programmed.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 72
Incorporating a student’s respective culture holds promise for adding to a student’s feeling of
connectedness.
Finally, for this research select questions were chosen to be analyzed in a consumable
manner. Many more variables were collected and will be retained in a PASW database for later
analyses as the researcher becomes more proficient in both quantitative methods, as well as, the
use of PASW as a tool. For now, however, two independent variables lend some predictability
for whether or not a student graduates with a high school diploma or a GED. These are parental
expectation to graduate and connection to class. These results mirror those of affecting high
school and college GPAs as an outcome. For the first – expectation to graduate – the students’
respective educational institution may not be able to directly affect this, but they could afford
information to parents to reinforce the value of having positive expectations of their child to
graduate high school and to demonstrate strategies for how to productively share these
expectations with their child. With the research shared above with respect to a level of alienation
Natives may be facing due to historical trauma, it is not surprising that feeling of connection to
class plays an important role in whether or not a student graduates high school. There are any
number of ways to make someone feel more connected and engaged with their cohort, with their
school, and to intervene at key times of change in order to retain students through to graduation.
Areas of Further Research: What Was Missed
Not all tribes responded to the survey. The distribution to the survey through a
convenience sample is a notable short coming and one that would explain what not all tribes
participated. More work is needed to ensure all tribes have a sufficient number of respondents in
order to make inferences. It is hoped that presenting the results to the Michigan Tribal Education
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 73
Directors to the Michigan Indian Education Consortium Annual Conference in March 2012, will
peak their interest with the current results and build support to engage in another level of study.
Given the research is primarily retrospective; there are some concerns with reliability of the
respondent responses. As noted previously, additional work in cross referencing these results
and designing future studies with national data sets, may help to better identify questions to ask
and possible more appropriate ways to elicit responses. One vary glaring result that came to
light after the data was collected was that of not having asked the question of gender on the
survey. This was in an earlier incarnation of the survey draft, but somehow did not make it into
the survey that was deployed. It would be interesting to see any differences between male and
females as national data sets do show a lower graduation rate for male Natives compared to their
female counterparts.
Limitations of study
There are many challenges to studying Natives in general. The condition or state of
being a high school drop-out has a negative connation for which some may be too embarrassed
to acknowledge. Given the possible reasons for dropping out dealing with impoverished
backgrounds or possible negative and racist experiences Natives face while growing up, some
potential respondents may simply choose to forge reliving such adverse experiences. There is
also the challenge of a cognitive disconnect with being Native American but not recognizing this
which some describe as an issue of cultural dissonance. In a pluralistic society where
assimilation was not only the ethic, but the official United States policy toward American
Indians with the abusive practices of Indian Boarding schools, it is not only surprising that some
Natives struggle with their Indian identities. This experience might very well explain a Natives’
hesitancy to remain part of an educational institution. Often, the struggle with understanding
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 74
one’s culture, heritage and their racial-ethnic (or in this case national) identity plays itself out
during a Native students’ high school and college years. Though some possible indicators in this
study will touch the surface of some of these issues, the research design employed is not
equipped to answers some of more qualitative questions of why. Data collection such as this
study will endeavor to undertake, certainly can provide a starting point for further research.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 75
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A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 79
APPENDIX A
Respondent Calculator Based on Number of Variables
RQ 1
2 # of Variables*
15 Sample X
30 Needed Returns
30% Projected return rate
100 Survey Total
RQ 2
19 # of Variables*
15 Sample X
285 Needed Returns
30% Projected return rate
950 Survey Total
RQ 3
10 # of Variables*
15 Sample X
150 Needed Returns
30% Projected return rate
500 Survey Total
RQ 4
24 # of Variables*
15 Sample X
360 Needed Returns
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 80
30% Projected return rate
1200 Survey Total
RQ 5
2 # of Variables*
15 Sample X
30 Needed Returns
30% Projected return rate
100 Survey Total
RQ 6
16 # of Variables*
15 Sample X
240 Needed Returns
30% Projected return rate
800 Survey Total
RQ 7
16 # of Variables*
15 Sample X
240 Needed Returns
30% Projected return rate
800 Survey Total
* Includes both IV and DV variables
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 81
APPENDIX B (1 OF 3)
Survey Instrument
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 82
APPENDIX B (2 OF 3)
Draft Survey Instrument
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 83
APPENDIX B (3 OF 3)
Draft Survey Instrument
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 84
APPENDIX C
Variable Names, Value Labels & Values Sorted by Research Question
Factor Variable Name Value Label Values Measure
RQ 1 DV234_GPACol College GPA Actual Scale
School DV1_GEDorHSGrad High School Graduation or GED 1=HS Graduate; 2 = GED Nominal
RQ 2 DV234_GPACol College GPA Actual Ratio
RQ1 IV+
School DV1_GEDorHSGrad High School Graduation or GED 1=HS Graduate; 2 = GED Nominal
School IV17_AcadGPA English, Math, Science, History, Social
Studies GPA Actual Scale
School IV18_CollAccept College Admissions Status 1=Regular; 2=Probationary; 3=Don't Know Nominal
RQ 3 DV234_GPACol College GPA Actual Scale
School DV1_GEDorHSGrad High School Graduation or GED 1=HS Graduate; 2 = GED Nominal
School IV17_AcadGPA English, Math, Science, History, Social
Studies Actual Scale
School IV18_CollAccept College Admissions Status 1=Regular; 2=Probationary; 3=Don't Know Nominal
Family IV19_FFAPELL College Financial aid 1=Yes; 2=No; 3=Don't Know Nominal
Family IV20_LOANS Loans 1=Yes; 2=No; 3=Don't Know Nominal
Cultural IV21_MITW Michigan Indian Tuition Waiver 1=Yes; 2=No; 3=Don't Know Nominal
Cultural IV22_TSCHOLSHIP Tribal Scholarships 1=Yes; 2=No; 3=Don't Know Nominal
Cultural IV23_NAOffice Natives Services 1=Yes; 2=No; 3=Don't Know Nominal
Cultural IV24_MultiCultOff Multi-Cultural Office 1=Yes; 2=No; 3=Don't Know Nominal
RQ 4 DV234_GPACol College GPA Scale
All Pre-College IV (RQ7) + All College
IV (IV17-IV24)
Various
Various
RQ 5 IV17 High School GPA Scale
High School Graduation or GED Nominal
RQ 6 IV17 High School GPA Scale
All Pre-College IV (RQ7) Various Various
RQ 7 DV1_GEDorHSGrad High School Graduation or GED 1=HS Graduate; 2 = GED Nominal
Personal IV1_BwhenGrown Be When You Grow Up 1=Yes; 2=No; 3=Don't Know Nominal
Family IV2_Income Family Income While Growing Up 1=Very Low; 2=Low; 3=Middle; 4=Upper; 5=Don't
Know Ordinal
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 85
Family IV3_FamEDlvl Highest Level of Education of Family 1=Elementary & Middle School; 2=High School;
3=12th Grade or GED; 4=College; 5 = Don't Know Scale
Family IV4_EX2Grad Parental Expectations to Graduate 1=Yes; 2=No; 3=Don't Know Nominal
Family IV5_Sabuse Family Substance Abuse 1=Yes; 2=No; 3=Don't Know Nominal
School IV6_SCHCon Connection at Elementary, Middle and
High School
1=Low; 2=Somewhat Low; 3=Moderate;
4=Somewhat High; 5=High Ordinal
School IV7_ClsCon Connection to Class Cohort 1=Low; 2=Somewhat Low; 3=Moderate;
4=Somewhat High; 5=High Ordinal
School IV8_ChgCon Change of Connection with Class Cohort 1=Yes; 2=No; 3=Don't Know Nominal
School IV9_SCHPartiALL Participated in Extra Curricular Activities 1=Yes; 2=No Nominal
School IV10_SCHIntot School Intervention Available? 1=Yes; 2=No; 3=Don't Know Nominal
School IV11_SCHIntotParti Participate in School Intervention? 1=Yes; 2=No or Blank Nominal
School IV12_ClsSubLike Class Subjects Liked 1=Did Not Like; 2=Moderate Dislike; 3=Neutral;
4=Moderate Like; 5=Really Like; 6= No Opinion Ordinal
School IV13_ClsSubGr Class Subjects Grades 0=F; 1=D; 2=C; 3=B; 4=A Scale
School IV14_SCHtype School Type 1=Parochial; 2=Private; 3=Public; 4=Tribal Nominal
Cultural IV15_NACon Connection to Culture 1=Low; 2=Somewhat Low; 3=Moderate;
4=Somewhat High; 5=High Ordinal
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 86
APPENDIX D
Interview Prompts for Phase II
GENERAL EXPERIENCE:
1. What was your experience and frame of mind throughout your educational experience [elementary, middle
school, high school, post high school]?
2. Have you ever wanted to give up on your education?
3. What reason(s) [did/ didn’t] you [not] give up?
4. What is your view of formal education for your child?
5. In what ways is this view different that your parent’s view for you when you were in school?
6. What differences do you see today in education versus when you were going to school?
7. What is your role (Dad) in your child’s education? What is your wife [girlfriend]’s role?
8. What is your role (Mom) in your child’s education? What is your husband [boyfriend]’s role?
9. What is your role [grandma, grandpa, uncle, auntie, cousin] in your child’s education?
10. In what way[s] is your role as it is today the same or different [Dad, Mom, Grandpa, Grandma, boyfriend,
girlfriend, uncle, auntie, cousin] that it was when you were growing up?
CONNECTEDNESS TO ‘SCHOOL’
1. In what ways did you feel a connection (if any) to your school or classmates?
2. In what ways did you feel disconnected (if at all) from your school or classmates?
3. Are your core group of friends those you know from school or outside of school?
4. What factor(s), if any, made you feel more or less connected at school?
ACCESS OR BARRIERS TO EDUCATION:
1. Were there any barriers you feel you had to overcome while in K-12 education?
2. What about college access issues?
3. If so, what factors aided you in graduating high school?
4. College?
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 87
FOR THOSE WHO TAKE A LESS CONVENTION ROUTE TO GRADUATE:
1. For those times you took time off from school, what compelled you to [want/need] to take time off?
2. What motivated you to continue and/or return?
3. What would it take for you to return?
AMERICAN INDIAN ID:
1. What does it mean to you to be an American Indian or Native American?
2. Does being an American Indian or Native American mean the same thing for your generation compared to
your parents? How so?
3. Does being an American Indian or Native American mean the same thing for you compared your
children’s? How so?
4. What does it mean to be an American Indian or Native American attending a [public/private/parochial]
school [K-12, community college, university, vocational trade school]?
5. In what ways do you think the experience is the same or different for American Indians or Native
Americans versus non-Natives? Please explain.
6. Do you think it is possible to be authentically an American Indian or Native American while also being a
college student? Please explain.
EDUCATION PARTICIPATION QUESTIONS:
1. Do you volunteer or participate in your child’s education?
2. What led you to want to volunteer or get involved in your child’s education?
3. Why do you suppose others volunteer or get involved in their child’s education?
4. Is your involvement with your child’s education something that began with you or your generation or is it
something you learned from others?
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 88
APPENDIX E.1
Correlation Matrix – Page 1 of 2
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 89
APPENDIX E.2
Correlation Matrix – Page 2 of 2
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 90
APPENDIX F
Frequency Distributions and Graphs
[Appended as a separate PASW Output File]
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 91
APPENDIX G.1
Graphs of Significant Differences on Select Variables Between
MI Native High School Graduates Versus those who earned their GED.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 92
APPENDIX G.2
Graphs of Significant Differences on Select Variables Between
MI Native High School Graduates Versus those who earned their GED.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 93
APPENDIX G.3
Graphs of Significant Differences on Select Variables Between
MI Native High School Graduates Versus those who earned their GED.
A PERSISTING PROBLEM IN SEARCH OF A SOLUTION 94
APPENDIX G.4
Graphs of Significant Differences on Select Variables Between
MI Native High School Graduates Versus those who earned their GED.