STUDENTS TO HEAVY SCIENCE MAJOR DEVELOPMENTAL …

THE COMPARISON OF THE COLLEGE OF ARTS AND

SCIENCES UNDECLARED MAJOR DEVELOPMENTAL

STUDENTS TO HEAVY SCIENCE MAJOR

DEVELOPMENTAL STUDENTS

by

SHEYLEAH VERNESE HARRIS, B.A.

A THESIS

IN

MATHEMATICS

Submitted to the Graduate Faculty of Texas Tech University in

Partial Fulfillment of the Requirements for

the Degree of

MASTER OF SCIENCE

Approved

Chafllperson of ii\^ Codfaiittee

• ^ ~ / '

Accepted

Dean of the Graduate School

May, 2004

TABLE OF CONTENTS

LIST OF TABLES iv

CHAPTER

L INTRODUCTION 1

Statement of Problem 1

Purpose of Study l

Research Questions 2

Definition of Terms 2

II. REVIEW OF THE LITERATURE 7

Introduction 7

Research Question #1 9





m. METHODOLOGY 14

Introduction 14

Research Design 14

Data Analysis 15

IV. FINDINGS 17

Introduction 17

n

V. RESULTS 19

Developmental Mathematics Course 19

First College-Level Mathematics Course 20

Gender 22

Age 25

Ethnicity 28

Summary 31

REFERENCE LIST 33

APPENDIX A GENERAL STATISTICS FORMULAS 36

APPENDIX B TABLES OF INTERMEDIATE ALGEBRA GRADES, COLLEGE-LEVEL MATHEMATICS COURSES, GENDERS, AGES, ETHNICITY 39

HI

LIST OF TABLES

1.1: Heavy Science Majors 6

4.1: Number of Heavy Science Majors in Developmental Mathematics by Semesters... 18

4.2: Intermediate Algebra Course Outcome by Major 20

4.3: College-Level Mathematics Course Outcome by Major 21

4.4: College-Level Mathematics Course Outcome by Gender 24

4.5: College-Level Mathematics Course Outcomes by Age 26

4.6: College-Level Mathematics Course Outcome by Minority or Non-minority 29

4.7: Summary of Results of Success 31

B.l: Intermediate Algebra Grade by Majors 40

B.2: College-Level Mathematics Course Grade Distribution by Intermediate Algebra Grade 40

B.3: College-Level Mathematics Course Grade Distribution by Major 41

B.4: College-Level Mathematics Course Grade Distribution by Course 42

B.5: College-Level Mathematics Course Outcome by Course 43

B.6: College-Level Mathematics Courses by Major 44

B.7: College-Level Mathematics Course Grade Distribution by Gender 44

B.8: College-Level Course by Gender 45

B.9: College-Level Mathematics Course Grade Distribution by Age 45

B.IO: College-Level Mathematics Courses by Age 46

B. 11: College-Level Mathematics Course Grade Distribution by Ethnicity 47

B.12: College-Level Mathematics Courses by Ethnicity 48

iv

B.13: College-Level Mathematics Course Outcome by Ethnicity 49

CHAPTER I

INTRODUCTION

Statement of Problem

There seems to be some confusion among those who are involved in mathematics

education about whether developmental mathematics courses are effective. O'Connor

and Morrison (1997) found that developmental mathematics did not have a positive

measurable effect on the students in their first college-level mathematics course.

However, Peimy and White (1998) found sufficient evidence that successful completion

of developmental mathematics does have a positive measurable effect on the students in

their first college-level mathematics course. It has come to the researchers' attention that

many students who want to have a career in either the medical field, engineering field,

architecture field, or scientific research enter postsecondary education unprepared to do

college-level mathematics work. This presents a problem because the pre-professional,

science, engineering, mathematics, and architecture majors require more mathematics

and/or logic in their curriculum.

Purpose of Study

The purpose of this study in to determine if heavy science (HS) majors perform

better than Arts and Sciences undeclared (ASUD) majors in their first college-level

mathematics course at Texas Tech university. Factors considered were gender, age, and

ethnicity.

Research Ouestions

The research questions looked at is as follows:

1. How did the pre-professional, science, engineering, mathematics, and architecture

majors perform in the developmental mathematics course compared to the Arts

and Sciences undeclared majors?

2. How did the pre-professional, science, engineering, mathematics, and architecture

majors perform in their first college-level mathematics course compared to the

Arts and Sciences undeclared majors?

3. How did each gender of the pre-professional, science, engineering, mathematics,

and architecture majors, perform in their first college-level mathematics course

compared to the Arts and Science imdeclared majors?

4. How did the traditional students in both groups perform in comparison to non-

traditional students in their first college-level mathematics course?

5. How did minorities and non-minorities in both groups perform in their first

college-level mathematics course?

Definition of Terms

The terms needed, to be understood, in the paper are defined in the following list:

1, College-ready students are students that have the skills and knowledge necessary

to perform college-level work upon entering postsecondary schools (Van Etten,

1997).

2. Developmental courses provide instruction for students who are not expected

ordinarily to succeed in college without these courses (Kulik & Kulik, 1991).

This instruction includes skills and knowledge from the discipline areas of

mathematics, writing, reading, study skills, and English as a Second Language

that are required for student success in college-level course work (Van Etten,

1997).

3. Developmental students are students who need to learn skills that had not been

taught previously. Thus, the responsibility lies with their preparation, not their

capability (Van Etten, 1997).

4. Remedial students are students that have been taught the skills, but did not learn

them, hence the student must be retaught the same skills again. Remedial

instruction may be a tool used in a developmental program (Van Etten, 1997).

5. Students that are full-time, residential students within the ages of 18-22 are called

traditional students (Van Etten, 1997). For this paper, the researcher will only

be using the age component as an indicator of whether or not a student is

traditional. This is because the data set used does not distinguish whether a

person was full-time or part-time or if they commuted to or lived on campus.

6. A heavy science major (HS) is considered to have greater than two semesters of

mathematics and/or greater than two semesters of natural sciences with lab in

their curriculum. All natural sciences courses are taught in the College of Arts

and Sciences and all mathematics courses are taught by the Department of

Mathematics and Statistics.

7. The Mathematics Placement Exam (MPE) is the placement exam used by Texas

Tech University to assess a student's mathematical skill level. The exam guides

the student to the course he or she wishes to take or to a course that develops the

necessary prerequisite skills for the required courses in his or her degree program

(Texas Tech University, "Mathematics Placement Exam," 2003).

All of the major degree programs came from the Texas Tech University Catalog

for 2003 and 2004 (Texas Tech University, 2003). The researcher compared the

programs to the criteria stated above, and this dictated if a major was a heavy science or

not. Heavy science majors based upon this criterion include pre-professional majors,

science majors, engineering majors, architecture and other selected majors.

The researcher decided that Pre-dentistry, Pre-hearing Professional Assistant, Pre-

medicine, Pre-medicine Technology, Pre-nursing, Pre-optometry, Pre-pharmacy, Pre-

veterinary medicine, Pre-physical Therapy, Nursing, and Allied Health are the pre-

professional majors. The researcher also decided that Applied Physics, Biochemistry,

Biology, Cell and Molecular Biology, Chemistry, Geology, Geophysics, Geochemistry,

Mathematics, Microbiology, Physics, and Zoology are the science majors. The

researcher also decided that Chemical Engineering, Civil Engineering, Computer

Science, Construction Technology, Electrical Engineering, Electronics Technology,

Engineering, Engineering Physics, Environmental Engineering, Mechanical Engineering,

Mechanical Technology, and Petroleum Engineering are the engineering majors. Other

majors that fall into the heavy science majors are from the College of Agricultural

Sciences and Natural Resources are Animal Science, Environmental Conservation of

Natural Resources, Horticulture, Range Management, and Wildlife and Fisheries

Management. From the College of Architecture, the majors Architecture/ Civil

Engineering and Architecture fall into the heavy science category. The College of

Human Sciences has a heavy science major in Food and Nutrition. These are seen in

Table 1.1.

The researcher compared the number of heavy science majors in developmental

mathematics each semester in the data set. From this comparison, it came to the attention

of the researcher that there was an increase in the number of students that declared a

heavy science major in developmental mathematics courses. The researcher is interested

in how the heavy science majors do in their first college-level mathematics after their

developmental mathematics course in comparison to the College of Arts and Science

undeclared majors. We will be comparing the two groups by looking at grades in their

last developmental mathematics course, grades of the first college-level mathematics

course, gender, age, and ethnicity.

Table 1.1: Heavy Science Majors

Classification

Pre-professional

Science

Engineering

Architecture

Others

Majors Pre-dentistry

Pre-hearing Professional Assistant Pre-medicine

Pre-medicine Technology Pre-nursing

Pre-optometry Pre-pharmacy

Pre-veterinary medicine Pre-physical Therapy

Nursing Allied Health

Applied Physics Biochemistry

Biology Cell and Molecular Biology

Chemistry Geology

Geophysics Mathematics Microbiology

Physics Zoology

Chemical Engineering Civil Engineering Computer Science

Constmction Technology Electrical Engineering

Electronics Technology Engineering

Engineering Physics Environmental Engineering

Mechanical Engineering Mechanical Technology Petroleum Engineering

Architecture/Civil Engineering Architecture

Animal Science Environmental Conservation of Natural Resources

Horticulture Range Management

Wildlife Management Fisheries Management

Food and Nutrition

CHAPTER II

REVIEW OF THE LITERATURE

Introduction

At Texas Tech University, a student has to score below 230 on the Texas

Academic Skills Program (TASP) mathematics test (Texas Tech University, "TASP",

2004) or score below a 3 on the Mathematics Placement Exam (Texas Tech University,

"Mathematics Placement Exam", 2003) to be required to take Math 0301 (Essential

Mathematics) and/or Math 0302 (Intermediate Algebra). Students that successfully

complete Math 0302 with a grade of A or B will be allowed to eru-oU in college-level

mathematics courses, either Math 1320 (College Algebra), Math 1321 (Trigonometry),

Math 1330 (Introductory Mathematical Analysis), Math 1420 (College Algebra with

Review), Math 1430 (Introductory Mathematical Analysis with Review), Math 1550

(Pre-calculus), or Math 2300 (Statistical Methods). The curriculum requires most of the

students of the pre-professional, sciences, engineering, mathematics, and architecture

majors enter Math 1320, while mostly business majors enter Math 1330. Students who

exit Math 0302 with a grade of C or lower are required to retake the Mathematics

Placement Test or retake Math 0302. While success in developmental mathematics is

either an A or B, we will consider success in a college-level mathematics coiu-se as

passing with a C or better.

Some people consider mathematics to be the "Mother of all Logic" since it has a

very strong basis in logic. Everything in mathematics has to be proven to be accepted

and has an algorithm. This has bearing on the heavy science majors because physics is

applied mathematics and engineering is applied physics. At the same time, chemistry is

also applied physics and biology is applied chemistry. Therefore, even if a student will

not be using algebra overtly on an everyday basis, the student still has to use analytical

and critical thinking skills. This is true for all college majors. This is the point that most

instructors of mathematics try to convey to their students. Every major requires its

students to be able to recognize a problem, recognize what tools are needed to solve the

problem, and find the most efficient way to use those tools. This is solving word

problems and using critical thinking skills. This use of critical thinking skills is needed

especially for the heavy science majors that we are comparing to the undeclared majors

of the College of Arts and Sciences, and this is the reason the researcher is interested in

how each group did respectively.

In effect, failure in mathematics courses can be a limiting factor in an

undergraduate's choice of major (Berenson, Carter, & Norwood, 1992). One will often

come across a student that enters a field because of the amount of math required (or not

required) in the curriculimi. The researcher's biggest concern comes in the form of the

educational system of the future. Who will teach the next generation the skills of the

discipline that has been avoided?

Research Ouestion #1

Most instructors of developmental mathematics at Texas Tech University

emphasize or require attendance. According to Thomas and Higbee (2000), attendance is

an important factor in the success of students in developmental mathematics courses.

At Texas Tech University, intermediate algebra does not receive any college

credit. Waits and Demana (1988) found there was a strong relationship between

mathematics skills and college success, regardless of the major. Conversely, students

often feel that intermediate algebra will have little or no effect on their performance in

later mathematics courses (Wheland, Konet, & Butler, 2003).


Hoyt and Sorensen (2001) found that students needed at least 3 years of college

preparatory mathematics in high school and a B average in the courses to be successful in

college-level mathematics. According to Hoyt (1999), students often needed to repeat, in

college, the same level or a lower level of mathematics than they took in high school.

Both Hoyt (1999) and Hoyt and Sorensen (2001) studies raise a question about the level

of preparation in secondary schools and the level of commitment by the students toward

their studies while in secondary schools. An earlier study conducted by Lappan and

Phillips (1984) found that almost 70% of students enrolled in intermediate algebra at a

university had 3 to 4 years of Algebra I and higher level mathematics in high school. In

the same study, another 42% of students in elementary algebra had 2 to 3 years of college

mathematics preparatory courses in high school.

According to Boylan and Bliss (1997), students taking part in mandatory

assessment programs are more likely to pass their first college-level mathematics courses

than those in schools that do not have a mandatory assessment and placement

developmental program. Kolzow (1986) found about 44% of students receiving an A in

developmental mathematics passed higher-level mathematics courses.

In their study of students in Newfoundland, O'Connor and Morrison (1997) found

that remedial mathematics did not have a positive measurable effect on students entering

college-level mathematics coiu ses. However, Penny and White (1998) found abundant

data that the successful completion of developmental mathematics does have a

constructive quantifiable result of success on students in college-level mathematics

courses.

In a national study of developmental education, Boylan and Bonham (1992) found

that developmental mathematics courses have a constructive influence on continuation

and achievement of students in college-level mathematics courses. Boylan and Bonham

(1992) acknowledged that of the students who took and successfully completed

developmental mathematics with a grade of C or better, 77% of those students also

passed their college-level mathematics course with a grade of C or better. Short (1996)

confirmed that students who have succeeded in developmental algebra courses are as

successful in their general studies curriculum as those students who did not require

developmental coursework. According to Xu (2000), intermediate algebra was a good

leveling course for students with mathematics deficiencies for their first college-level

mathematics course. Thus, the research supports that intermediate algebra gives the

10

students in developmental mathematics courses the same opportunity to be successfiil in

their college-level mathematics courses.

Research Question #3

According to Walker and Plata (2000), females fail elementary and intermediate

algebra more often than their male counterparts do. According to Melange

(1988), an inexplicably high percentage of women fail developmental mathematics

courses. Schonberger (1981) found that males did better than females with algebraic

concepts. Conversely, Chang (1977) reported that females did significantly better than

males in two of three developmental mathematics courses. However, Conroy (1971)

foimd that there was no difference between the genders passing developmental

mathematics.

Research Question #4

According to Walker and Plata (2000), nonti-aditional students passed

intermediate algebra more often than traditional students did. According to Johnson

(1996), a college student's age and developmental course performance were notably and

positively correlated to later academic success. Elderveld (1983) found that age was a

determining factor of success or failure in developmental mathematics courses. Conroy

(1971) found that older students passed developmental mathematics more often than

younger students.

11


According to the 1995 Digest of Educational Statistics (U.S. Department of

Education, 1995), in 1992, 29.8% of African-American and 66.4% of Anglo 17 year-old

students could perform reasoning and problem solving involving fractions, decimals,

percents, elementary geometry, and simple algebra.

It appears that more African-American students are placed into a fundamental

mathematics or elementary algebra course more often than their Anglo counterparts are

(Walker & Plata, 2000).

African-American students failed elementary algebra more often than their Anglo

counterparts did. Anglos failed intermediate algebra more often than Afiican-Americans

did. Anglos earn more A's, while African-Americans earn more C's and D's in

intermediate algebra (Walker &, Plata, 2000). The researcher ponders on whether this has

anything to do with the attitude of each ethnic group toward mathematics.

The literature found by the researcher seems to suggest that a student's attitude

and prior preparation may be important criteria in predicting how well a student will do.

It also appears that gender, age, and ethnicity may have some bearing on how well a

student does in their first college mathematics course after taking a developmental

mathematics course.

The researcher found that there was little literature comparing the heavy science

majors and the College of Arts and Sciences undeclared majors' success in their first

college-level mathematics course. This prompted the researcher to think that it may well

12

be time for this type of research, especially since the nation wants to become more

competitive in the fields that are being studied.

13

CHAPTER III

METHODOLOGY

Introduction

The purpose of this study is to examine whether major, gender, age, and ethnicity

determine whether a student who has taken a developmental mathematics course

succeeds in their first college-level mathematics course. We will be examining the

variables through descriptive statistics, test of independent proportions, and Fisher's

exact test.

Research Design

Microsoft® Excel is the program in which the data set was prepared. The

researcher combined the four data sets into one worksheet. Afterwards, the researcher

made one entry for each student, which contained the last developmental mathematics

course and the first college-level mathematics course. The researcher then deleted all

majors that were not classified as a heavy science major or as an Arts and Sciences

undeclared major. All remaining records that did not have MATH 0302 or SPCM 0320

as the last developmental mathematics course were deleted. This brought the total

number of records in the database to 428 for the Arts and Sciences undeclared and heavy

science majors.

Microsoft® Access is the program that queried the data set. The students' records

were queried according to the variables listed. The files that contain missing data for any

14

student were deleted. The results from the queries where put into the tables in Chapter

IV.

Data Analysis

Subjects for this study were acquired from the Office of Institutional Research at

Texas Tech University. A data set was received from the Texas Tech Office of

Institutional Research that contains data for developmental mathematics students taking

courses at Texas Tech University from fall 2001 to spring 2002. The variables sex,

ethnicity, age, college, major, last developmental mathematics course taken, grade for the

last developmental mathematics course, semester the last developmental mathematics

course was taken, first college-level mathematics course taken, grade for the first college-

level mathematics course, and semester the first college-level mathematics course was

taken are some of the variables in the data set. All of the variables listed before will be

used in the analysis of the database. Student privacy was preserved since those directly

involved in this study did not receive the names or social security numbers of the

students. All tables and queries include all four semesters.

In this particular database received from the Office of Institutional Research,

students that took their developmental mathematics courses with South Plains College

receive a PR. Texas Tech University did not know if the student had made an A, B, or C

at the time the database was requested. The researcher had Microsoft® Access query out

the necessary variables for each question.

15

The researcher used the test of independent proportions and Fisher's exact test to

determine if there was a sufficient difference between the independent groups being

studied. The researcher used a level of significance of 0.05, thus the critical value of the

test statistic is ± 1.96. The researcher also computed a 95% confidence interval where

possible. The general formulas can be found in Appendix A.

16

CHAPTER IV

FINDINGS

Introduction

The purpose of this section is to find how each group performed in their

developmental mathematics course, how each of the groups performed in their first

college-level mathematics course, how each gender of each group performed in their first

college-level mathematics course, how the age of students in each group performed in

their first college-level mathematics course, and how minorities and non-minorities in

each group performed in their first college-level mathematics course on Texas Tech

University campus. This chapter will discuss the results found through the methodology.

As mentioned earlier in this study, the researcher noticed a growing trend in the

number of heavy science major students taking developmental mathematics courses.

Please refer to Table 4.1. These numbers yield 130 heavy science majors and 298 Arts

and Sciences undeclared majors in developmental mathematics courses.

17

Table 4.1: Number of Heavy Science Majors in Developmental Mathematics by Semesters

Semester

Spring

2001

2002

2003

Summer I

2001

2002

2003

Summer II

2001

2002

2003

Fall

2001

2002

2003

Total

Number of HS Majors

2

14

28

0

0

0

0

0

2

10

10

64

130

Number of ASUD Majors

73

5

48

7

3

3

4

2

4

16

100

33

298

18

CHAPTER V

RESULTS

From the results of the queries, described in Chapter III, tables were created for

the research questions.

Developmental Mathematics Course

Missing Data

Out of 428 developmental mathematics students for Fall and Spring semesters of

2001 and 2002, cases were omitted that contained the following:

• no developmental mathematics grade since they were taking developmental

mathematics the semester this thesis was written, 43 cases;

• no developmental math grade, 6 cases.

As seen in Table 4.2, in the 379 cases remaining, 189 (0.724) Arts and Sciences

undeclared were successful in their last developmental mathematics course. Also as seen

in Table 4.2,96 (0.814) heavy science majors were successful in their last developmental

mathematics course. The researcher considered Cs, Ds, Fs, and withdrawals as students

who were unsuccessful. The researcher tested the hypothesis that the proportion of Arts

and Sciences undeclared majors' success in intermediate algebra is equal to the

proportion of heavy science majors' success in intermediate algebra. Conducting a test of

independent proportions the researcher found the difference between the proportions has

a p-value of 0.0562 at a level of significance of 0.05 and reserved judgment and makes no

19

conclusions about the hypothesis. The researcher leaves the reader to make their own

conclusions about the proportion of declared heavy science majors' performance in

developmental mathematics and the proportion of the Arts and Sciences undeclared

majors' performance in developmental mathematics.

Table 4.2: Intermediate Algebra Course Outcome by Major

~ ~ ^ ~ ~ ^ - . _ ^

ASUD

HS

Total

Intermediate Algebra Course Outcome Pass 189

72.4% 96

81.4% 285

75.2%

Fail 72

27.6% 22

18.6% 94

24.8%

Total 261

118

379

First College-Level Mathematics Course

Missing Data



• failed their developmental mathematics course and took a college-level

mathematics course or have not taken a college-level mathematics course, 281

cases;

• no developmental college-level math grade, 4 cases.


undeclared were successful in their first college-level mathematics coiu-se. From Table

4.3, 50 (0.781) heavy science were successful in their first college-level mathematics

20

course. The researcher considered Ds, Fs, and withdrawals as students who were

unsuccessfiil. The researcher tested the hypothesis that the proportion of Arts and

Sciences undeclared majors' success in their first college-level mathematics course is

equal to the proportion of heavy science majors' success in their first college-level

mathematics course. Conducting a test of independent proportions the researcher found

the difference between the proportions is statistically significant a p-value of 0.0001 at a

level of significance of 0.05 and rejected the hypothesis. This lends support to the

rejection of the hypothesis that the proportion between the heavy science majors equals

the Arts and Sciences undeclared majors. The proportion of declared heavy science

majors' performance in their first college-level mathematics course differs from the

proportion of the Arts and Sciences undeclared majors' success and the heavy science

majors' success in their first college-level mathematics course. The researcher can be

95% confident that the heavy science majors will succeed at a rate that exceeds that of the

Arts and Sciences undeclared majors between 15.2% and 47.4%.

Table 4.3: College-Level Mathematics Course Outcome by Major

^ ^ ^ ^ ^ ^

ASUD

HS

Total

College-level mathematics course outcome

Pass 37

46.8% 50

78.1% 87

60.8%

Fail 42

53.2% 14

21.9% 56

39.2%

Total

79

64

143

21

The researcher found that unlike in Kolzow (1986) where 44% of students that

made an A in developmental mathematics passed their first college-level mathematics

course, of this set of students that made an A in developmental mathematics 72.5% of

them passed their first college-level mathematics course. Please refer to Table B.2 in

Appendix B.

According to Table 4.3, it would seem a larger percentage of the heavy science

majors pass their first college-level mathematics courses. Please refer to Table A.2 in

Appendix A to see the breakdown of the students that passed intermediate algebra and

how they did in their college-level mathematics course.

Gender

Missing Data





cases;

• no developmental college-level math grade, 4 cases.


undeclared males were successful in their first college-level mathematics course. From

Table 4.4, 30 (0.750) heavy science males were successful in their first college-level

mathematics course. The researcher considered Ds, Fs, and withdrawals as students who

22

were unsuccessful. The researcher tested the hypothesis that the proportion of Arts and

Sciences undeclared males' success in their first college-level mathematics course is

equal to the proportion of heavy science males' success in their first college-level

mathematics course. Conducting Fisher's exact test the researcher found the difference

between the proportions is statistically significant a p-value of 0.0001 at a level of

significance of 0.05 and rejected the hypothesis. This lends support to the rejection of the

hypothesis that the proportion between the heavy science majors equals the Arts and

Sciences undeclared majors. The proportion of declared heavy science majors'

performance in their fist college-level mathematics course differs from the proportion of

the Arts and Sciences undeclared majors' performance in their first college-level

mathematics course. Since the samples are so small, the researcher cannot compute the

confidence interval.

23

Table 4.4: College-Level Mathematics Course Outcome by Gender

Male

Female

Total

Grand Total

Majors

ASUD

HS

ASUD

HS

ASUD

HS


Pass 15

36.6% 30

75.0% 22

57.9% 20

83.3% 37

46.8% 50

78.1% 87

60.8%

Fail 26

63.4% 10

25.0% 16

42.1% 4

16.7% 42

53.2% 14

21.9% 56

39.2%

Total

41

40

38

24

79

64

143


undeclared females were successful in their first college-level mathematics course. From

Table 4.4,20 (0.833) heavy science females were successful in their first college-level

mathematics course. The researcher considered Ds, Fs, and withdrawals as students who

were unsuccessful. The researcher tested the hypothesis that the proportion of Arts and

Sciences undeclared females' success in their first college-level mathematics course is

equal to the proportion of heavy science females' success in their first college-level

mathematics course. Conducting Fisher's exact test the researcher found the difference

between the proportions has a p-value of 0.0516 at a level of significance of 0.05 and

reserved judgment and makes no conclusions about the hypothesis. The researcher

leaves the reader to make their own conclusions about the proportion of declared heavy

science majors' performance in their first college-level mathematics course differs from

24

the proportion of the Arts and Sciences undeclared majors' performance in their first

college-level mathematics course.

According the Walker and Plata (2000), males pass their developmental

mathematics courses more often. However, in this study, the data reveals that females in

both major groups passed their first college-level more than their respective male

counterparts. This could possibly be that developmental mathematics is a leveling course

for females.

Age

Missing Data





cases;

• no developmental math grade, 6 cases.


undeclared non-traditional students were successful in their first college-level

mathematics course. From Table 4.5,4 (0.667) heavy science non-traditional students

were successful in their first college-level mathematics course. The researcher

considered Ds, Fs, and withdrawals as students who were unsuccessful. The researcher

tested the hypothesis that the proportion of Arts and Sciences undeclared non-traditional

25

students' success in their first college-level mathematics course is equal to the proportion

of heavy science non-traditional students' success in their first college-level mathematics

course. Conducting Fisher's exact test the researcher found the difference between the

proportions is statistically insignificant a p-value of 1 at a level of significance of 0.05

and accepted the hypothesis. This lends support to the acceptance of the hypothesis that

the proportion between the heavy sciences major equals the Arts and Sciences undeclared

majors.

Table 4.5: College-Level Mathematics Course Outcomes by Age

Non-traditional

Traditional

Total

Grand Total

Major

ASUD

HS

ASUD

HS

ASUD

HS


Pass 2

50.0% 4

66.7% 35

46.7% 46

79.3% 37

46.8% 50

78.1% 87

60.8%

Fail 2

50.0% 2

33.3% 40

53.3% 12

20.7% 42

53.2% 14

21.9% 56

39.2%

Total

4

6

75

58

79

64

143


undeclared traditional were successful in their first college-level mathematics course.

From Table 4.5,46 (0.793) heavy science traditional were successful in their first

college-level mathematics course. The researcher considered Ds, Fs, and withdrawals as

26

students who were unsuccessful. The researcher tested the hypothesis that the proportion

of Arts and Science undeclared ti-aditional students' success in their first college-level

mathematics course is equal to the proportion of heavy science ti-aditional students'

success in their first college-level mathematics course. Conducting Fisher's exact test the

researcher found the difference between the proportions is statistically significant a p-

value of 0.0002 at a level of significance of 0.05 and rejected the hypothesis. This lends

support to the rejection of the hypothesis that the proportion between the heavy science

majors equals the Arts and Sciences undeclared majors. The proportion of declared

heavy science majors' performance in their first college-level mathematics course differs

from the proportion of the Arts and Sciences undeclared majors' performance in their

first college-level mathematics course. Since the samples are so small, the researcher

cannot compute the confidence interval.

According to Walker and Plata (2000), non-traditional students pass

developmental more often than traditional students do. Non-traditional students having

more obligations than their younger counterparts can explain this, as they have to be

more focused and studious. This study showed that Arts and Sciences undeclared non-

traditional students passed their first college-level mathematics course more often than

Arts and Science imdeclared traditional students. However, heavy science non-ft-aditional

students passed their first college-level mathematics course less often than heavy science

ti-aditional students did. This may be explained by developmental mathematics course

makes the heavy science traditional students more focused.

27

Ethnicity

Missing Data

Out of 428 developmental mathematics stiidents for Fall and Spring semesters of




cases;

• no developmental college-level math grade, 4 cases;

• no identified gender, 1 case.


undeclared non-minority students were successful in their first college-level mathematics

course. From Table 4.6,30 (0.750) heavy science non-minority students were successful

in their first college-level mathematics course. The researcher considered Ds, Fs, and

withdrawals as students who were unsuccessful. The researcher considered all ethnic

groups that were not considered minorities by the Federal Government to be non-

minority. The researcher tested the hypothesis that the proportion of Arts and Sciences

undeclared non-minority students' success in their first college-level mathematics course

is equal to the proportion of heavy science non-minority students' success in their first

college-level mathematics course. Conducting Fisher's exact test the researcher foimd



rejection of the hypothesis that the proportion between the heavy sciences major equals

28



proportion of the Arts and Sciences undeclared majors' performance in their first college-

level mathematics course. Since the samples are so small, the researcher cannot compute

the confidence interval.

Table 4.6: College-Level Mathematics Course Outcome by Minority or Non-minority

^ ^ - ^

Non-minority

Minority

Total

Grand Total

Co Major

ASUD

HS

ASUD

HS

ASUD

HS

lege-level mathematics course outcome Pass 30

48.4% 30

75.0% 6

37.5% 20

83.3% 36

46.2% 50

78.1% 86

60.6%

Fail 32

51.6% 10

25.0% 10

62.5% 4

16.7% 42

53.8% 14

21.9% 56

39.4%

Total

62

40

16

24

78

64

142


undeclared minority were successful in their first college-level mathematics course.

From Table 4.6, 20 (0.833) heavy science minority were successful in their first college-

level mathematics coiu-se. The researcher considered Ds, Fs, and withdrawals as students

who were unsuccessful. The researcher tested the hypothesis that the proportion of Arts

and Science undeclared minority students' success in their first college-level mathematics

29

course is equal to the proportion of heavy science minority students' success in their first

college-level mathematics course. Conducting Fisher's exact test the researcher found



rejection of the hypothesis that the proportion between the heavy science majors equals



proportion of the Arts and Sciences undeclared majors' performance in their first college-

level mathematics course. Since the samples are so small, the researcher cannot compute

the confidence interval.

Looking at the results in Table 4.7, the data contiadicts the opinion that males do

better in mathematics than females. Females passed their first college-level course more

often than males in both major groups. The heavy science traditional students passed

their first college-level mathematics course more often than the heavy science non-

traditional students. The heavy science minority students passed their first college-level

mathematics course more often than the heavy science non-minority students. The pre-

professional, science, engineering, mathematics, and architecture majors already know

that mathematics will have an important impact in their college and the professional

careers, while the undecided majors may not necessarily be aware of this concept.

30

Table 4.7: Summary of Results of Success

^ ~ - - - _ _

Developmental Mathematics Course First College-Level Mathematics Course Gender

Females

Males Age

Non-traditional Traditional

Ethnicity Non-minority

Minority

HS

81.4%

78.1%

83.3%

75.0%

66.7% 79.3%

75.0% 83.3%

ASUD

72.4%

46.8%

57.9%

36.6%

50.0% 46.7%

48.4% 37.5%

Statistically Significant Marginally

(left to reader)

Highly

Marginally (left to reader)

Highly

Not Highly

Significant Highly

p-value

0.0562

0.0001

0.0516

0.0001

1 0.0002

0.0129 0.0059

Summary

The purpose of this study is to determine if heavy science (HS) majors perform

better than Arts and Sciences undeclared (ASUD) majors in their first college level

mathematics course at Texas Tech University. Factors considered were gender, age, and

ethnicity. This study has shown there is a difference between heavy science majors and

Arts and Science undeclared majors in all areas except non-traditional students. There

needs to be continued study on the majors to find out which major does better and why.

Future research could involve a study to determine how Arts and Sciences undeclared

majors compare to other majors, if developmental mathematics courses makes students

more focused, if a student having a declared major does better in developmental

mathematics courses and college-level mathematics courses, if the heavy science major

31

students' and Arts and Sciences undeclared major students' attitudes are different toward

mathematics, and if this has any effect on their performance.

32

REFERENCES LIST

Berenson, S., Carter, G., & Morwood, K. (1992). The at-risk stiident in college developmental algebra. School Science and Mathematics, 92(2), 55-58.

Boylan, H. R., Bliss, L. B. (1997). Program components and their relationship to stiidents performance. Journal of Developmental Education. 20(3), 2-7.

Boylan, H. & Bonham, B. (1992). The impact of developmental education programs. Review of Research in Developmental Education, 9(5), 1-4.

Chang, P. T. (1977). Persistence in Small Group Instiaiction in Developmental Mathematics Courses on Relationships among Academic Performance, Sex Difference, Attitude, and Persistence. Paper Presented at the Annual Meeting of the American Mathematical Association of Two Year Colleges (Atianta, Georgia, October 1997). (ED162862).

Conroy, D. E. (1971). The Effects of Age and Sex Upon a Comparison Between Achievement Gains in Programmed Instruction and Conventional Instruction in Remedial Algebra I at Northem Virginia Community College. Ed.D. Dissertation, American University. (ED078640).

Elderveld, P. J. (1983). Factors related to success and failure in developmental mathematics in the community college. Community/Junior College Quarterly of Research and Practice, 7(2), 161-74. (EJ278390).

Hoyt, I.E. (1999). Level of math preparation in high school and its impact on remedial placement at an urban state college. College & University, 74,37-43.

Hoyt, J.E. & Sorensen, C. T. (2001). High school preparation, placement testing, and college remediation. Journal of Developmental Education, 25(2), 26-33.

Johnson, L. F. (1996). Developmental performance as a predictor of academic success in entry-level college mathematics. Community College Journal of Research and Practice, 20(A), 333-344.

Kolzow, L.C. (1986). Stiidy of Academic Progress by stiidents at Harper after Enrolling in Developmental Courses. (ERIC Document Reproduction Service No. ED 265 914).

Kulik, J.A. & Kulik, C.-L.C. (1991) Developmental instruction: An analysis of the ' research. (Research Report #1). Boone, NC: National Center for Developmental

Education and the Exxon Education Foundation.

33

Lappan, G. & Phillips, E. (1984). The mathematical preparation of entering college freshmen. NASSP Bulletin, (55(468), 79-84.

"Melange: Superconducting Supercollider and a Final Theory in Physics; Self-Segregation of Black Stiidents; The Mathematics Pipeline." Chronicle of Higher Education, 6 May 1988.

O'Connor, W. & Morrison.T. (1997). Do remedial mathematics programmes improve students' mathematical ability? Studies in Educational Evaluation, 23(3), 201-207.

Penny, M. & White, W. (1998). Developmental mathematics stiidents' performance: Impact of faculty and student characteristics. Journal of Developmental Education, 22(2), 2-12.

Schonberger, A. K. (1981). Gender Differences in Solving Mathematics Problems among Two-Year College Students in a Developmental Algebra Class and Related Factors. Paper presented at the Midyear Meeting of the American Education Research Association Special Interest Group on Women in Education (Washington, DC, October 17,1981). (ED214602).

Short, C. (1996). Stiong success in developmental algebra: Implications for retention and success in general studies. Research in Developmental Education, 13(4), 1-4.

Texas Tech University. (2003). Texas Tech University Catalog 2003-04. Lubbock, TX: Official Publication.

Texas Tech University, Lubbock, Mathematics Placement Exam (2003, June) Retiieved September 10,2003. from Texas Tech University Mathematics Web page. http://www.math.ttu.edu/placement/.

Texas Tech University, Lubbock, TASP (2004) Retiieved April 1,2004. from Tevas Tech University Office of Texas Academic Skills Program.

Thomas, P. & Higbee, J. (2000). The relationship between involvement and success in developmental algebra. Journal of College Reading and Learning, 30(2), 222-232.

United States Department of Education. (1995). Digest of Education Statistics 1995 (NCES 95-029). Washington, DC: National Center for Education Statistics, U.S. Government Printing Office.

34

http://www.math.ttu.edu/placement/

Van Etten, Karl. (1997) The Comparative Undergraduate Performance and Persistence of Students who do not enroll in Developmental Classes at Colorado State System Community Colleges. Dissertation Abstiacts International, 58(4A), 1187.

Walker, W. & Plata, M. (2000). Race/gender/age differences in college mathematics students. Journal of Developmental Educational, 23(3), 24-30.

Waits, B.K. & Demana, F. (1988). Relationship between mathematics skills of entering students and their success in college. The School Counselor, 35(4), 307-310.

Wheland, E, Konet, R. M., & Butler (2003). Perceived inhibitors to mathematics success. Journal of Developmental Education, 26(3), 18-20, 22, 24,26-7.

Xu, Bei. (2000). Intermediate algebra as a predictor of success in college-level math courses. University of Cential Oklahoma.

35

APPENDIX A

GENERAL STATISTICS FORMULAS

36

TEST OF INDEPENDENT PROPORTIONS

Criterion for Rejection

/ > - P , = 0

1 P » P . - P : = 1 ^ ^ - + —

/J, « 2 y

where p =

q = \-p f = frequency of occurrence in the first sample / j = frequency of occurrence in the second sample

Test Statistic

Confidence Interval

C / , 5 = U - P 2 ) ± ( 1 - 9 6 X V P J

37

CALCULATION FOR FISHER'S EXACT TEST

P = -

A+CYB+D^

A + B

(A + B)\(C + D)\{A + C)\{B + D)\

A\B\C\D\N\

CALCULATION FOR P-VALUE

p - value = 2P{Z>\z\)

where Z is N{0,\)

38

APPENDIX B

TABLES OF INTERMEDIATE ALGEBRA GRADES, COLLEGE-LEVEL

MATHEMATICS COURSES, GENDERS, AGES, ETHNICITY

39

Table B. 1: Intermediate Algebra Grade by Majors

\

ASUD

HS

Total

A 32

12.3% 26

22.0% 58

15.3%

B 45

17.2% 16

13.6% 61

16.1%

Intermediate Algebra Course Grade PR 112

42.9% 54

45.8% 166

43.8%

C 13

5.0% 6

5.1% 19

5.0%

D 14

5.4% 2

1.7% 16

4.2%

F 35

13.4% 8

6.8% 43

11.3%

W 10

3.8% 6

5.1% 16

4.2%

Total 261

118

379

Table B.2: College-Level Mathematics Course Grade Distiibution by Intermediate Algebra Grade

Texas Tech Intermediate

Algebra Grade

A

B

Total

South Plains

PR

Total

Grand Total

College-level Mathematics Course Grade

A

8 20.0%

2 5.4%

10 13.0%

3 7.5%

3 7.5%

13 11.1%

B

13 32.5%

8 21.6%

21 27.3%

11 27.5%

11 27.5%

32 27.4%

C

8 20.0%

7 18.9%

15 19.5%

14 35.0%

14 35.0%

29 24.8%

D

4 10.0%

2 5.4%

6 7.8%

2 5.0%

2 5.0%

8 6.8%

F

0 0.0%

10 27.0%

10 13.0%

2 5.0%

2 5.0%

12 10.3%

W

7 17.5%

8 21.6%

15 19.5%

8 20.0%

8 20.0%

23 19.7%

Total

40

37

77

40

40

117

40

Table B.3: College-Level Matiiematics Course Grade Distribution by Major

^ ^ ^ ^ - ~ , , ^

ASUD

HS

Total

College-level mathematics course grade A 10

12.7% 6

9.4% 16

11.2%

B 14

17.7% 22

34.4% 36

25.2%

C 13

16.5% 22

34.4% 35

24.5%

D 9

11.4% 0

0.0% 9

6.3%

F 9

11.4% 4

6.3% 13

9.1%

W 24

30.4% 10

15.6% 34

23.8%

Total

79

64

143

41

Table B.4: College-Level Mathematics Course Grade Distiibution by Course

^ - ^ ^

ASUD

Math 1320

Math 1330

Math 1420

Math 1430

Math 1550

Math 2300

Total

HS

Math 1320

Math 1330

Math 1420

Math 1430

Math 1550

Math 2300

Total

Grand Total

A

6 17.6%

1 4.2%

0 0.0%

2 28.6%

0 0.0%

0 0.0%

9 11.5%

4 11.8%

0 0.0%

0

0 0.0%

2 20.0%

0

6 11.5%

15 11.5%

College-level mathematics course grade B

6 17.6%

5 20.8%

3 33.3%

0 0.0%

0 0.0%

0 0.0%

14 17.9%

8 23.5%

4 66.7%

0

2 100.0%

2 20.0%

0

16 30.8%

30 23.1%

C

8 23.5%

3 12.5%

0 0.0%

0 0.0%

0 0.0%

2 66.7%

13 16.7%

16 47.1%

2 33.3%

0

0 0.0%

2 20.0%

0

20 38.5%

33 25.4%

D

1 2.9%

6 25.0%

2 22.2%

0 0.0%

0 0.0%

0 0.0%

9 11.5%

0 0.0%

0 0.0%

0

0 0.0%

0 0.0%

0

0 0.0%

9 6.9%

F

3 8.8%

5 20.8%

0 0.0%

1 14.3%

0 0.0%

0 0.0%

9 11.5%

2 5.9%

0 0.0%

0

0 0.0%

2 20.0%

0

4 7.7%

13 10.0%

W

10 29.4%

4 16.7%

4 44.4%

4 57.1%

1 100.0%

1 33.3%

24 30.8%

4 11.8%

0 0.0%

0

0 0.0%

2 20.0%

0

6 11.5%

30 23.1%

Total

34

24

9

7

1

3

78

34

6

0

2

10

0

52

130

42

Table B.5: College-Level Mathematics Course Outcome by Course

" ^ ^ - ^ ^

ASUD

Math 1320

Math 1330

Math 1420

Math 1430

Math 1550

Math 2300

Total

HS

Math 1320

Math 1330

Math 1420

Math 1430

Math 1550

Math 2300

Total

Grand Total


Pass

20 58.8%

9 37.5%

3 33.3%

2 28.6%

0 0.0%

2 66.7%

36 46.2%

28 82.4%

6 100.0%

0 2

100.0% 6

60.0% 0

42 80.8%

78 60.0%

Fail

14 41.2%

15 62.5%

6 66.7%

5 71.4%

1 100.0%

1 33.3%

42 53.8%

6 17.6%

0 0.0%

0 0

0.0% 4

40.0% 0 10

19.2% 52

40.0%

Total

34

24

9

7

1

3

78

34

6

0

2

10

0

52

130

43

Table B.6: College-Level Matiiematics Courses by Major

ASUD

HS

Total

College-level mathematics courses

Math 1320

46 45.1%

36 64.3%

82 51.9%

Math 1330 33

32.4% 6

10.7% 39

24.7%

Math 1420

9 8.8%

0 0.0%

9 5.7%

Math 1430

9 8.8%

4 7.1%

13 8.2%

Math 1550

2 2.0%

10 17.9%

12 7.6%

Math 2300

3 2.9%

0 0.0%

3 1.9%

Total

102

56

158

Table B.7: College-Level Mathematics Course Grade Distiibution by Gender

^ " ^ ^ ^

ASUD

Male

Female

Total

HS

Male

Female

Total

Grand Total

Co A

5 12.2%

5 13.2%

10 12.7%

2 5.0%

4 16.7%

6 9.4%

16 11.2%

B

6 14.6%

8 21.1%

14 17.7%

16 40.0%

6 25.0%

22 34.4%

36 25.2%

lege-level mathematics course grade C

4 9.8%

9 23.7%

13 16.5%

12 30.0%

10 41.7%

22 34.4%

35 24.5%

D

4 9.8%

5 13.2%

9 11.4%

0 0.0%

0 0.0%

0 0.0%

9 6.3%

F

7 17.1%

2 5.3%

9 11.4%

4 10.0%

0 0.0%

4 6.3%

13 9.1%

W

15 36.6%

9 23.7%

24 30.4%

6 15.0%

4 16.7%

10 15.6%

34 23.8%

Total

41

38

79

40

24

64

143

44

Table B.8: College-Level Course by Gender

ASUD

Male

Female

Total

HS

Male

Female

Total

Grand Total

College-level mathematics courses Math 1320

19 33.9%

27 58.7%

46 45.1%

20 58.8%

16 72.7%

36 64.3%

82 51.9%

Math 1330

25 44.6%

8 17.4%

33 32.4%

2 5.9%

4 18.2%

6 10.7%

39 24.7%

Math 1420

3 5.4%

6 13.0%

9 8.8%

0 0.0%

0 0.0%

0 0.0%

9 5.7%

Math 1430

7 12.5%

2 4.3%

9 8.8%

4 11.8%

0 0.0%

4 7.1%

13 8.2%

Math 1550

2 3.6%

0 0.0%

2 2.0%

8 23.5%

2 9.1%

10 17.9%

12 7.6%

Math 2300

0 0.0%

3 6.5%

3 3.0%

0 0.0%

0 0.0%

0 0.0%

3 1.9%

Total

56

46

102

34

22

56

158

Table B.9: College-Level Mathematics Course Grade Distribution by Age

^ ^ ^ - ^ ^

ASUD Non-

traditional

Traditional

Total

HS Non-

traditional

Traditional

Total

Grand Total

Col A

2 50.0%

8 10.7%

10 12.7%

0 0.0%

6 10.3%

6 9.4%

16 11.2%

B

0 0.0%

14 18.7%

14 17.7%

2 33.3%

20 34.4%

22 34.4%

36 25.2%

ege-level mathematics course grade C

0 0.0%

13 17.3%

13 16.5%

2 33.3%

20 34.4%

22 . 34.4%

35 24.5%

D

0 0.0%

9 12.0%

9 11.4%

0 0.0%

0 0.0%

0 0.0%

9 6.3%

F

0 0.0%

9 12.0%

9 11.4%

0 0.0%

4 6.9%

4 6.3%

13 9.1%

W

2 50.0%

22 29.3%

24 30.4%

2 33.3%

8 13.8%

10 15.6%

34 23.8%

Total

4

75

79

6

58

64

143

45

Table B.IO: College-Level Mathematics Courses by Age

^ " ^ - ^

ASUD

Non-traditional

Traditional

Total

HS

Non-traditional

Traditional

Total

Grand Total

Co Math 1320

4 57.1%

42 44.2%

46 45.1%

4 66.7%

32 64.0%

36 64.3%

82 51.9%

Math 1330

3 42.9%

30 31.6%

33 32.4%

2 33.3%

4 8.0%

6 10.7%

39 1 24.7%

lege-level mathematics courses Math 1420

0 0.0%

9 9.5%

9 8.8%

0 0.0%

0 0.0%

0 0.0%

9 5.7%

Math 1430

0 0.0%

9 9.5%

9 8.8%

0 0.0%

4 8.0%

4 7.1%

13 8.2%

Math 1550

0 0.0%

2 2.1%

2 2.0%

0 0.0%

10 20.0%

10 17.9%

12 7.6%

Math 2300

0 0.0%

3 3.2%

3 2.9%

0 0.0%

0 0.0%

0 0.0%

3 1.9%

Total

7

95

102

6

50

56

158

46

Table B. 11: College-Level Mathematics Course Grade Distiibution by Ethnicity

^ ^ - \

ASUD

Anglo

Hispanic

Black

Native American

Other

Total

HS

Anglo

Hispanic

Black

Native American

Other

Total

Grand Total

A

9 14.5%

1 25.0%

0 0.0%

0

0

10 12.8%

4 10.5%

2 12.5%

0 0.0%

0

0 0.0%

6 9.4%

16 11.3%

College-level mathematics course erade B

12 19.4%

0 0.0%

1 8.3%

0

0

13 16.7%

16 42.1%

0 0.0%

4 50.0%

0

2 100.0%

22 34.4%

35 24.6%

C

9 14.5%

1 25.0%

3 25.0%

0

0

13 16.7%

8 21.1%

12 75.0%

2 25.0%

0

0 0.0%

22 34.4%

35 24.6%

D

6 9.7%

0 0.0%

3 25.0%

0

0

9 11.5%

0 0.0%

0 0.0%

0 0.0%

0

0 0.0%

0 0.0%

9 6.3%

F

4 6.5%

1 25.0%

4 33.3%

0

0

9 11.5%

4 10.5%

0 0.0%

0 0.0%

0

0 0.0%

4 6.3%

13 9.2%

W

22 35.5%

1 25.0%

1 8.3%

0

0

24 30.8%

6 15.8%

2 12.5%

2 25.0%

0

0 0.0%

10 15.6%

34 23.9%

Total

62

4

12

0

0

78

38

16

8

0

2

64

142

47

Table B.12: College-Level Mathematics Courses by Ethnicity

^ - \

ASUD

Anglo

Hispanic

Black

Native American

Other

Total

HS

Anglo

Hispanic

Black

Native American

Other

Total

Grand Total

College-level mathematics courses Math 1320

31 40.8%

5 55.6%

8 53.3%

1 100.0%

0

45 44.6%

20 62.5%

12 85.7%

4 50.0%

0

0 0.0%

36 64.3%

81 51.6%

Math 1330

27 35.5%

1 11.1%

5 33.3%

0 0.0%

0

33 32.7%

4 12.5%

0 0.0%

2 25.0%

0

0 0.0%

6 10.7%

39 24.8%

Math 1420

9 11.8%

0 0.0%

0 0.0%

0 0.0%

0

9 8.9%

0 0.0%

0 0.0%

0 0.0%

0

0 0.0%

0 0.0%

9 5.7%

Math 1430

7 9.2%

2 22.2%

0 0.0%

0 0.0%

0

9 8.9%

2 6.3%

2 14.3%

0 0.0%

0

0 0.0%

4 7.1%

13 1 8.3%

Math 1550

1 1.3%

1 11.1%

0 0.0%

0 0.0%

0

2 2.0%

6 18.8%

0 0.0%

2 25.0%

0

2 100.0%

10 17.9%

12 7.6%

Math 2300

1 1.3%

0 0.0%

2 13.3%

0 0.0%

0

3 3.0%

0 0.0%

0 0.0%

0 0.0%

0

0 0.0%

0 0.0%

3 1.9%

Total

76

9

15

1

0

101

32

14

8

0

2

56

157

48

Table B.13: College-Level Mathematics Course Outcome by Etimicity

ASUD

Anglo

Hispanic

Black

Native American Other

Total

HS

Anglo

Hispanic

Black

Native American

Other

Total

Grand Total


Pass

30 48.4%

2 50.0%

4 33.3%

0 0 36

46.2%

28 73.7%

14 87.5%

6 75.0%

0 2

100.0% 50

78.1% 86

60.6%

Fail

32 51.6%

2 50.0%

8 66.7%

0 0

42 53.8%

10 26.3%

2 12.5%

2 25.0%

0 0

0.0% 14

21.9% 56

39.4%

Total

62

4

12

0 0

78

38

16

8

0

2

64

142

49

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degree at Texas Tech University or Texas Tech University Health Sciences Center, I

agree that the Library and my major department shall make it freely available for

research purposes. Permission to copy this thesis for scholarly purposes may be

granted by the Director of the Library or my major professor. It is understood that any

copying or publication of this thesis for financial gain shall not be allowed without my

further written permission and that any user may be liable for copyright infringement.

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Student Signature Date

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Student Signatiire Date

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