ASSESSMENT OF FACTORS LIMITING SUCCESSFUL

COMPLETION OF QUANTITATIVE COURSES IN

THE UNDERGRADUATE HOSPITALITY CURRICULUM

by

J. B. WARD, B.S.

A THESIS

IN

RESTAURANT. HOTEL, AND INSTITUTIONAL MANAGEMENT

Submitted to the Graduate Faculty of Texas Tech University in

Partial Fulfillment of the Requirements for

die Degree of

MASTER OF SCIENCE

Approved

May, 2001

ACKNOWLEDGEMENTS

I would like to thank my wife Catherine, for her unwavering support. I would like

to thank my parents, Donald and Ramona, for their support and encouragement. I am

grateful to my committee chair. Dr. Lynda D. March, for her guidance, and more

importantly, her time. I would like to thank Dr. Ben Goh for his assistance on my survey

preparation.

I would also like to thank my committee members, Dr. Tim Dodd, and Dr. Ginny

Felstehausen for their advice and thoughtful critiques of this study.

This is for you, Jack.

11

TABLE OF CONTENTS

ACKNOWLEDGEMENTS ii

LIST OF TABLES vi

CHAPTER

I. INTRODUCTION 1

Justification 2

Purpose 3

Objectives of the Study 3

Hypotheses 4

Terms 4

II. REVIEW OF LITERATURE 6

Definition and Assessment of Math Anxiety 6

Additional Impact of Math Anxiety and Performance 8

College Student Performance and Retention 12

Quantitative Skills Needed by Hospitality Managers 18

III. METHOLODOGY 21

Research Design 21

Description of the Population and Sampling 22

Development and Testing of Instrument 22

Data Collection Procedures 24

Statistical Analysis 24

Data Treatment 25

111

IV. RESULTS AND DISCUSSION 27

Demographic Characteristics 27

Student High School Math Performance and Place of Origm 30

Quantitative Courses Completed by Hospitality Students Prior to Study 32

Grades Received in Completed Quantitative Courses 32

Student Quantitative Ability 34

Student Math Confidence and Math Anxiety 36

The Relationship Between Confidence Levels and Demographics 39

The Relationship Between Math Performance and Demographics 39

Confidence and Math Performance 40

Overall Confidence and Aspects of Math Confidence Levels 42

Student Anxiety of Basic Quantitative Course Components

and Quantitative Performance 44

V. CONCLUSION 48

Summary of Findings 49

HI: Relationship Between Student Demographics

and Confidence Level 49

H2: Relationship Between Demographics and Math Performance 50

H3: Relationship Between Math Performance

and Student Confidence Levels 51

H4: Student Math Confidence and Aspects of Math Confidence 51

H5: Situational Variables Affecting Math Anxiety and Math Performance 52

Comparison of Results to Prior Works 5 2 IV

Conclusion and AppUcations 54

Limitations of the Research 5 5

Areas for Future Research 55

REFERENCES 57

APPENDIX: SURVEY INSTRUMENT 59

LIST OF TABLES

1. Demographic Characteristics of the College Student Participants 28

2. Student Background Information on High School Performance and Original Community 31

3. Grades Received in Completed Quantitative Courses 33

4. ResultsofQuantitative Ability Assessment 35

5. Student Reported Math Anxiety Levels 37

6. Overall Confidence Levels and Math Confidence 43

7. Relation of Anxiety Levels to Math Performance 45

VI

CHAPTER I

INTRODUCTION

Due to die increasing proportion of jobs wdtiim the service sector, growth and

employment needs in tiie hospitality industry are expected to increase by over 20% in the

American job force during the next seven years (Bureau of Labor Statistics, 2001).

Increased employment in the hospitality industry provides opportunities for

socioeconomic advancement. One fourth of these new jobs will require a bachelor's

degree, so the need to succeed in college will be vital to obtaining a well-paying and

challenging job in the hospitality industry after graduation. The $400 billion dollar food

service industry has over 2,000 restaurant/hospitality management or culinary programs

currently available to aspiring industry professionals (National Restaurant Association,

2001).

Hospitality professionals seeking career advancement will find a college degree crucial

to their success. The industry will require comprehensive skill sets which will allow

companies to achieve goals of profitability and growth. Part of the curriculum will need

to include quantitative courses requiring performance understanding of mathematics to

coincide with industry skills of financial management. However, math skills of

hospitality majors are imperative and have been reported to be limited. Others have

observed that hospitality students seem anxious to perform quantitatively.

Hotel management schools and imdergraduate hospitality programs are viewed as

important when responding to the changing needs of the hospitality industry (Anderson,

2000). An issue plaguing hospitality graduates is die external perception tiiat it does not

require a great deal of skill to operate a hospitality establishment. Koteff (2000) remarked

that running a restaurant is the same as operating most other businesses, often much more

difficult. The ability to compute labor and material costs were seen as vital. A study

conducted by the firm of Arthur Anderson (2000) suggested that accounting and finance

were important to prepare students for success within hospitality college education

programs. Hospitality managers need a thorough knowledge of accounting to understand

financial data if a business is to continue operation.

Quantitative courses are required in most college curriculums. The number of required

courses will vary between majors. An understanding of math and accounting is

imperative for most business-related fields of study. Quantitative anxiety in math and

accounting in college has been an issue for students for some time. The overall anxiety

levels in college are significant enough to warrant numerous individuals to conclude that

this problem can lead to student success or complete withdrawal from the college

existence. While numerous studies have assessed students' anxiety toward math and

accounting classes in college, none have focused primarily on the hospitality student.

Justification

The need for college students to successfully complete quantitative courses will

determine their success in college and their future careers. One four-year accredited

institution has suggested that as many as 20% of college students suffer from nervousness

which becomes so severe that their grades and quality of life declines (Program for

Academic Support Services, 2000). It also was suggested that math anxiety is part of a

greater learning disability related to impaired visual ability

Prior research has been conducted on math and anxiety, but none focused on the field

of hospitality. A pilot project for the current research confirmed high anxiety, low

confidence and low performance levels of hospitality students. Students' anxiety levels

can lead to decreased performance and a decline in grades received in quantitative

courses. In addition, lack of quantitative confidence can lead to a decline in overall

confidence and can resuh in a premature end to the college career of some students. The

results of the pilot study indicated further investigated was merited.

Purpose

The purpose of this research was to assess math anxiety performance levels of

hospitality undergraduate students at the beginning and termination of their college

career. Specifically studied were demographics, math confidence and anxiety levels,

math performance ability and the interrelationship between them.

Objectives of the Study

Three research objectives were established:

1. To assess the level of math and accounting anxiety of U.S. hospitality students.

2. To measure U.S. hospitality students' ability to solve basic math and accounting problems

3. To assess the interrelationship of demographic factors, quantitative confidence, quantitative

anxiety, and calculation performance of U.S. hospitality undergraduate students

Hypotheses

Matii anxiety appears to occur nationwide witiiin hospitality programs. Demographic

factors may increase tiie level of anxiety, but hospitality programs appear to attract a

large number of students from diverse backgrounds witii quantitative anxiety. To begin

to address the reduction of math anxiety levels and develop methods to improve

quantitative performance of hospitality students, initial relationships between

demographics, confidence and anxiety levels, and performance need to be assessed. The

following hypotheses will be addressed:

HI: There is a relationship between student demographics and math confidence levels.

H2: There is a relationship between student demographics and math performance.

H3: There is a relationship between matii performance and student math confidence

level.

H4: Attitude to math is related to math confidence level.

H5: Situations contributing to math anxiety level will be related to math performance.

Terms

The following were specifically defined for this research:

Ouantitative courses are college-level courses requiring quantitative ability or math for

successful completion. Examples include math, statistics, accounting, and finance.

Math anxiety (Richardson & Suinn 1972) is a set of feelings of "tension and anxiety

that interfere with the manipulation of numbers and the solving of mathematical problems

in a wide variety of ordinary hfe and academic situations" (p. 552).

Math confidence is the level of self-assurance students posses toward thefr ability to

perform in quantitative courses.

Math performance is the level of desired academic performance exhibited in quantitative

courses and assessments on the high school and college level.

CHAPTER II

REVIEW OF LITERATURE

The review of literature will support the need to study the effects of impact of

demographics, math anxiety, and quantitative ability on quantitative course performance

of hospitality students. While no studies were found to date focusing specifically on

hospitality students, investigators in related fields have published a body of literature

discussing math performance, math confidence and anxiety, and die necessity of

acquiring quantitative skills for career success in hospitality management.

The following topics will be explored:

1. Definition and assessment of math anxiety.

2. Impacts of anxiety on math performance.

3. College student quantitative performance and retention.

4. Quantitative skills needed by hospitality managers.

Definition and Assessment of Math Anxiety

Quantitative skills are necessary in the business world; yet many people feel anxious

when performing simple or complex quantitative functions which could prevent

successful completion of these tasks. Measuring anxiety allows assessment of the

problem and can enable planning for solutions.

Measurement of math anxiety levels quantifies perceived computational apprehension.

Richardson and Suirm (1972) developed the Mathematics Anxiety Rating Scale (MARS),

a 98-item Likert-type scale containing brief descriptions of behavioral situations related

to math. The scale has been used for research and treatment for matii anxiety. The MARS

was developed because: (1) math anxiety was relatively common in college; (2) tiie tool

and accompanying research could measure tiie effectiveness of matii anxiety treatments;

(3) the MARS test could yield a ranking order for use in treatment; and (4) measurement

of test score changes could measure treatment effectiveness.

To initially test tiie MARS instrument for reliability and validity, tiie authors collected

normative data on 397 freshman and sophomore students enrolled in entry level

education courses. A high mtemal and consistency reliability rating (.97) for the MARS

test was determined. While a majority of the respondents were female (80%), no

significant differences were found related to math anxiety. The test-retest results were

similar, which was suggested to result from the short interval of time between the two

testing periods. Camp (1992) retested the instrument and found reliability coefficients of

.78 recorded at two weeks and .85 at seven weeks. The MARS scale has become a widely

adopted tool to measure math anxiety.

Richardson and Suinn (1972) found no significant gender differences conceming math

anxiety in their initial studies to validate the instrument. A subsequent study conducted

by Dew, Galassi, and Galassi (1984) measured math anxiety with the MARS and two

other scales. The 63 paid participants consisted of 23 men and 40 women selected using

stratified random sampling. The students were primarily first and second year

undergraduate students with limited math course work beyond high school. The students

were observed for heart rate changes, skin fluctuations, and avoidance behavior. Four

areas of matii anxiety were explored: (1) tiie relation of matii anxiety to test-anxiety,

specifically situation-specific test anxiety and worry and emotionality components; (2)

die extent to which matii anxiety interfered witii performance; (3) tiie relation of matii

anxiety to physiological arousal during problem solving; and (4) tiie association between

matii anxiety and avoidance of performing matii problem-solving.

To measure tiieir matii ability, tiie first problem set included 20 aritiunetic computation

problems, tiie second section consisted of 15 stated problems, and tiie tiiird set was

administered under test-like conditions with a time constraint. A post-test questionnaire

to gather demographic information was administered after students completed the tiiird

section. Results indicated that math and test anxiety were related, but not identical. The

author suggested that better measurement procedures were needed to measure math

avoidance. They also found that math anxiety had a modest relationship to math

performance, and a weak relationship to physiological arousal during problem solving.

The MARS scale remains the most widely used instrument to measure math anxiety,

and a subsequently developed modified version allows assessment in a shorter time

period. Measuring math anxiety is imperative to identify and discuss additional impacts

on scholastic performance and career choices which may include successful quantitative

performance.

Additional Impact of Math Anxiety and Math Performance

In addition to measuring math anxiety, external factors may directly or indirectly

impact the level of student performance. Engelhard (1989) conducted a study focusing on

tiie relationship of mathematics performance, matii anxiety, motiier's education, and

gender. Thirteen-year-old children from tiie United States (n = 4,091) and Thailand (n =

3,613) completed a matii performance test. The extent of matii anxiety to assess matii

performance was measured using a 40-question Likert scale (1= strongly disagree, 5=

strongly agree). Problems concentrated on tiie areas of algebra, aritiimetic, and geometry.

High score totals indicated increased levels of matii anxiety. Information about the

mother's education level was collected using a questionnaire accompanied by a math

posttest. The posttest gathered additional information on the mothers' background and

demographic information. Females exhibited higher levels of anxiety than males. Thai

females performed better in math than Thai males, while American males outperformed

American females. Gender differences in performance were observed to be minimal until

the eighth grade when differences increased substantially during the next five years

through high school for both nationalities. The mothers' education level also was an

important factor affecting a child's math performance. The mother significantiy

influenced the child's linguistic skills and educational aspirations, because the mother

was more likely to have custody of the child. A significant and inverse relationship was

indicated between math anxiety and math performance for the American and Thai

adolescents.

Additional analysis examined the correlation between math performance and anxiety.

While direct effects of matii anxiety were small, tiie indirect effects of tiie anxiety were

thought to be profound. People with math anxiety have been suggested to avoid matii

classes, and possibly develop a more negative attitude toward computers (Engelhard,

1989).

Students exhibitmg matii anxiety in quantitative courses also may be poor performers.

Camp (1992) conducted a study to assess tiie relationship between matii performance and

anxiety in tiie fall of 1990 at one eastern university. Four research question areas were

explored: (1) tiie relationship between matii anxiety, confidence in matii, and attimdes

about math; (2) nonintellective variables of anxiety predicted anxiety in relation to tiie

college arena besides gender and previous matii experience; (3) gender differences in

matii anxiety and confidence; and (4) Impact of course format on matii performance

(Camp, 1992).

A total of 957 students completed the survey yielding 918 sets of useable data.

Participants mean age was 21 witii 63% of tiie respondents being female. Descriptive

statistics and separate t-tests were used for each variable, and analysis of variance was

used to determine group differences between the lab and lecture formats. Students

enrolled in lab format classes indicated higher levels of math anxiety (p<_.001) and self-

efficacy for math problems (p< .001). Students in the lecture section received higher

math grades tiian those in the lab sections (Camp, 1992).

Llabre and Suarez (1985) studied 184 college students who previously had not been

involved in the field of mathematics to determine math anxiety levels. All students were

enrolled in a basic algebra class with no more than two years of high school algebra.

Most respondents (62%) were female. A shortened version of the MARS measured

10

anxiety. The students completed tiie test during tiie first class session, and regression

analysis and correlations were used to analyze the data.

Women reported higher levels of anxiety toward matii tiian men; however, male

dominance could not be confirmed from tiiis study. Females witiiin tiie study had higher

grades in math courses than males. The level of matii anxiety students reported prior to

class enrollment had little or no impact on the final course grade (Llabre and Suarez,

1985).

A later study used a convenience sample of 90 introductory English students in a

northeastern community college to determine gender differences in math anxiety and

math avoidance (Ruben, 1998). Three categories of anxiety were identified: matii anxiety,

numerical test anxiety, and quantitative course anxiety. Five research hypotheses were

proposed:

HI. Males report their math anxiety less frequently than females

H2. Males seek help less often with math than females

H3. Males and females avoid taking required math courses with similar frequency

H4. Males avoid programs of study requiring math as frequently as females

H5. Student perception of math difficulty appears related to math anxiety

All hypotheses were supported, except that there was no significance between student

perception of math difficulty and anxiety. Men and women were not significantly

different when avoiding math courses, but men reported less anxiety than women.

Earlier studies assessmg math anxiety indicated that younger females exhibit higher

levels of anxiety than males, which appears to continue into college. Previous studies

II

have indicated that there may be a difference in math anxiety occurrence. Further study

could be focused on determining the amount of contact a person has had with math in

relation to the level of anxiety.

College Student Performance and Retention

Quantitative performance success is likely important to retaining students in college.

As tiie student reaches college level, a new set of quantitative challenges arise.

Depending on tiie chosen field of study, students can study more math m a year tiian tiiey

have attempted during their entire high school education.

Jackson and Leffingwell (1999) sought to determine the genesis of math anxiety. The

percentage of persons reporting positive feelings toward matii from kindergarten tiirough

college was less than 10%. The beginning of matii-related difficulty in tiie elementary

years occurred for most students as tiiey approached tiie fourth grade. Difficulties

increased throughout high school, with the majority of problems in college occurring

during the freshman year.

The elementary problems began with the introduction of fractions and timed tests, and

the addition of multiplication tables increased the students' anxiety. With these new

problems came new attitudes from teachers who were reported to be angered by students'

inability to imderstand the material without help resulting in derogatory comments

toward students not understanding the concepts. Girls seemed to receive criticism more

often than boys. Students appeared to be encouraged by their instructors to tease students

who could not keep up m math (Jackson & Leffingwell, 1990).

12

While colleges and universities work to retain young people, large numbers of older

people entering the workforce experience matii anxiety. Studies involving matii anxiety

more frequently focus on traditional students or younger adults without paying attention

to needs of older adults (Handler, 1990). Adults may change tiieir career patii, or miss

promotions due to math anxiety. An understanding of tiie factors causing math anxiety is

essential to help older adults. Symptoms may not be evident until years after traditional

schooling is completed. The educator's role for adults was suggested as isolating and

reducing the math anxiety levels of the older adult student.

Handler (1990) also noted that one factor leading to math anxiety was exam or test-

takmg fear in both older men and women. Student personal self-expectation and

perceived ideas of who could be successful in math could reduce performance or even

precipitate avoidance of math classes entirely. This may limit career choices to jobs that

require little or no math, or end a college career due to failure in math-related subjects.

Teachers can reduce anxiety by repeating material and organizing new ways to

comprehend math problems (Handler, 1990). Students may withhold their opinions of

math hatred, fearing retaliation by their professors. The first step to reducing math

dislike is assuring students that they are not alone in feeling dislike and that it does not

make them a "bad person" to dislike math. Many people with math anxiety may rely on

memorization to help them get through the class. Handler also suggested that educators'

greatest problems may be finding inventive ways to encourage individuals to cope w ith

their anxiety while providing several concrete teaching tactics. It was suggested that

educators begin at the basic level and use easily understood examples instead of using

13

abstract numbers and formulas. Teachers also could ask students to respond to open-

ended questions, tiius forcing tiiem to propose creative solutions. Teachers must keep

students motivated, ensuring tiiat tiiey are clearing obstacles, and finding new ones to

tackle and encourage tiiem to track anxious feelings, and help tiiem work tiirough tiiese

feelings. Working in groups or teams places responsibility on tiie roles of tiie individual

members. Creative teaching approaches have been shown to reduce or eliminate tiie matii

anxiety.

Skiba (1980) suggested that teachers should begin witii easy problems, praise tiie

students when tiiey are correct, and gradually progress to problems tiiat are more

difficult. Students were found to improve matii performance if tiiey kept records of

personal problem-solving methods, which provided a manual to study for upcoming

assignments and tests. Student work and discipline tiien apparently corrected math

anxiety.

Hospitality students also require accounting knowledge which is an extension of basic

quantitative ability to be successful. A two-stage study was conducted to investigate the

relationship between knowledge, skill, self-efficacy, and computer education in an

accounting education setting (Stone , Arunachalam, & Chandler, 1996). The first stage of

the study segmented students into two groups. One group received software-specific

training and accounting systems knowledge (SSTASK), while the second group received

only accounting systems knowledge (ASK). The second group was taught accounting

systems knowledge for eight weeks, followed by eight weeks of combined software-

specific training and accounting systems knowledge. The study measured three main

14

competencies for students: (1) spreadsheet self-efificacy, (2) computer self-efficacy, and

(3) computer anxiety. The benchmark of internal consistency was > .84. Student

participants in tiie pilot study (n=239) had taken introductory accounting information

systems; however, only a portion of the students received prior spreadsheet training.

In tiie first stage of tiie study, a survey was distributed on the first class day to

determine the differences in the group's age, number of high school accounting classes,

previous computer usage, self-reported cumulative and accounting GPA, and montiis of

previous work experience. A general spreadsheet test was given to 160 students enrolled

at the beginning of a semester from an introductory accounting class. One hundred seven

passed tiie test witii a score of 80% or better. The remaining 53 students who did not pass

were required to take a software-specific training and accounting systems knowledge

course. A weakness in the study was due to the course prerequisite variance that affected

the students' knowledge level. At the end of the semester, all of the 53 students passed

the retest and were adequately knowledgeable in computing and accounting skills.

Too often it is assumed that the basis for math anxiety is due to a fear of numbers and

mathematical equations. Educators may need to look at their actions and contributions to

student anxiety levels, and take appropriate steps to assist their students. Assistance may

be proposed in the form of a clinic to reduce math anxiety.

In a study conducted by Wadlington, Austui, and Bitner (1992), 78 teachers in training

were tested with the MARS. Thirty-six subjects with the highest anxiety scores on the

original test were selected for subsequent treatment for the subjects' math anxiety. This

15

study illustrated tiie advantages of long-term group coimseling sessions to reduce math

anxiety.

Ten years ago, almost half of students enrolling in college before the age of 19 did not

complete a degree. Jackson and Leffingwell (1999) noted tiiat tiie responsibility for

retention and learning ultimately falls upon tiie student, but tiie institutions and faculty

influence student success.

Some studies have focused on the hospitality majors success or failure in college. The

hospitality student is one subset of college students experiencing math anxiety in college.

Tobias (1991) proposed an area for students to receive help with tiieir quantitative

anxiety. The overall goal was to help alleviate the problem by establishing a math anxiety

clinic. Response to the clinic was slow even after the clinic created clever little gimmicks

to get people to come in. Findings suggested that people with severe math anxiety still

did not enter the clinic, primarily because they felt the clinic could not help them. Clinic

representatives went out to lecture and dispel many math rumors, and wrote papers on the

subject.

Upon entry to the clinic a subject would write dowm their math experiences.

Similarities existed between subjects' embarrassment of having to go to the head of the

classroom and the pressure of tests that have a time limit. The instructor began setting the

pace of sessions, allowing the students to set the pace in subsequent sessions. Students

also were encouraged to take notes beside their math problems to communicate to

instructors their feelings about their current work. If a subject chose to share their notes

with the class, it became part of the class discussion. Once the students attended the

16

clinic, increased success in class performance was expected (Tobias, 1991). Clinics to

assist students may be shown to be affective in alleviating math anxiety.

Breiter (1993) studied factors tiiat appeared to impact hospitality student retention.

Students involved in campus activities and tiiose living on campus during tiieir first year

of college were observed to remain in school longer tiian tiieir counterparts. Breiter also

found that students witii clear-cut goals and intentions were more likely to remain in

school. Working in a particular field of study before degree completion was found to

have a possible negative impact on a decision to stay in tiiat field. Hospitality majors

may discover that the complexity of operational management involves more than waiting

tables. A heightened awareness of these factors could assist teachers and administrators

to focus assisting students to achieve their personal goals and complete a baccalaureate

degree.

Breiter (1993) also suggested that universities could increase retention by helping

students adjust to new social and academic surroundings. Providing students the

opportunity to interface with professionals helps students commit to the hospitality

profession and would open up some interesting career opportunities. The William F.

Harrah College of the University of Nevada at Las Vegas (UNLV), an institution

internationally known for its hospitality program, took a unique approach to the retention

problem. The advising department would track students whose grade pomt averages

dropped below a standard and required those students to meet with directors until their

academic performance improved. Librarians were assigned to assist students in

acclimating to the imiversities Informational Resoiu^ces College. Representatives from

17

Student Affairs met with new students to direct them to help resources. Student response

was favorable when further study was considered to measure with an empirical analysis

of student satisfaction "retention." Socially integrating students was suggested as

possibly the most important factor in retention of new students (Breiter, 1993).

New students were tracked into retention programs. UNLV scheduled meetings for

new students and their parents to meet the faculty before the semester began.

Representatives from student clubs came in during the first weeks of school to recruit

students and to encourage college involvement. Professional organizations may increase

exposure to the reality of the business world, and may open career paths. Personal

factors, university support, and social opportunities appeared to affect student success.

Faculty and staff could use this information and resources to assist in student retention

(Breiter, 1993).

Ouantitative Skills Needed bv Hospitality Managers

The level of educational attainment in the hospitality industry has increased over the

last ten to twenty years within the hospitality industry. These expectations have

contributed to the rapid growth of college-based hospitality management programs.

Breiter and Clements (1996) conducted a survey of managers employed in fifty

restaurants and fifty hotels. Two-thirds of the respondents believed that a general

manager should have a four-year degree, and one-third listed the same educational

requirement for assistant managers. Thus, the hospitality industry is seeking practical

18

skillsets included in advanced education for staff leadership positions traditionally filled

by hospitality graduates.

Su, Miller, and Shanklm (1997,1998) also surveyed hospitality professionals.

Respondents were 145 industry professionals and 12 faculty (49.6% response rate) who

were members of tiie Council on Hotel, Restaurant, and Institutional Education (CHRIE)

with familiarity of the hospitality accreditation process. They were asked to list tiie

importance of knowledge and skill areas important to hospitality students entering tiie

workforce. Differences between the educators and mdustry professionals were not

significantly different. Areas tiiat were considered most important by both educators and

professionals were interpersonal communication, management information systems,

financial management, ethical considerations, personnel management, marketing,

accounting, foodservice and lodging operations, administrative processes, areas of

specialization, quantitative methods, and the legal environment. Human resource

management was seen as a vital need in hospitality programs and leadership development

needed more focus. Knowledge of software and computers was identified to be a major

component of future success. Respondents also supported the idea of student-run

restaurants as an incentive for leaming and student preparation (Su, Miller, & Shanklin

1997, 1998). The authors concluded that academia needs to provide solid knowledge and

skills in areas identified as crucial by the industry which supports inclusion of

quantitative courses to address identified needs in the hospitality curriculum.

Schmidgall, Rutherford, Sciarini, and Woods (1999) also pointed out that knowledge

of financial data and keeping cost-control are pivotal to the success of being a general

19

manager of a hotel. Increasing tiie Gross Operating Profit (GOP) of the hotel constantly

rated high on the list of what the general managers in the survey deemed as one of the

most important characteristics to their continued success. Knowledge of numbers is

paramount to achieving and retaining the position of general manager.

The new millenium will bring many changes for hospitality managers. Hospitality

professionals will need to match job performance to mcreased customer expectations.

Hospitality programs will need to recognize and adapt to these changes in order to

produce the quality programs sought by the industry.

Quantitative skills are a crucial component within the undergraduate hospitality college

curriculum. Because the literature indicates that math anxiety is a problem on the

collegiate level, further research on this subject is warranted. In hospitality education,

there has been no research to date focusing on the level of math anxiety students face.

Because the hospitality major has not been traditionally considered math intensive, there

may be some correlation between anxiety levels and the selection of hospitality as a field

of study. The current study investigated factors related to increased math anxiety for

college level American hospitality students.

20

CHAPTER III

METHODOLOGY

The following is a discussion of the study methodology. The research design

includes: description of the study population and sampling, development and testing of

the instrument, data collection procedures, methods of statistical analysis, and treatment

of data.

Research Design

The purpose of this research was to assess math anxiety performance levels of

hospitality undergraduate students at the beginning and termination of their college

career. Specifically studied were demographics, math confidence and anxiety levels

performance abilities and these interrelationship. A written questionnaire captured the

independent variables of demographic information, quantitative confidence level, and

quantitative anxiety levels. The dependent variable math and accounting performance,

was defined as the letter grade received in courses requiring quantitative tasks and

student performance on a math inventory within the instrument. The survey instrument

also included a modified version of the Math Anxiety Rating Scale (MARS) (Richardson

&Suinn, 1972; Camp, 1992).

21

Description of the Population and Sampling

The sample population was drawn from accredited four-year hospitality programs

in tiie United States, as identified by the Council for Hotel Restaurant Institutional

Education (CHRIE, 2000). Globally, tiiere are 153 accredited CHRIE institutions

offering baccalaureate degrees. This population was chosen for the current study because

the programs have completed a self-study program and have had a site visit to evaluate

educational quality which would increase quality outcomes. Geographical representation

tiiroughout the U.S. is mherent in the population. The average accredited four-year

hospitality undergraduate program enrolled 293 students. Median enrollment was 150

students.

Six schools were selected usmg convenience sampling. Programs were

volvmteered by senior faculty to participate. Schools were invited and chosen from both

the east and west coasts and the middle section of U.S to reduce sampling bias inherent in

the volunteering of faculty. All students enrolled in freshman and senior seminars within

these programs were asked to participate.

Development and Testing of Instrument

The questionnaire was composed of three sections. The first section included questions

about demographic and enrollment information, prior math performance, and high school

completion and performance levels for math and accounting, and a Likert-type scale to

assess perceived confidence m quantitative skills.

22

The second section of the survey assessed math anxiety. The mstrument used to

measure math anxiety was a modified version of tiie MARS, tiie MARS-r, (Richardson &

Suinn, 1972) based on a five-point Likert-type continuum, witii " 1 " mdicating no

anxiety, and "5" indicatmg a very high level of anxiety. The MARS has a verified and

reverified high internal consistency and reliability ratio (Camp, 1992; Richardson &

Suinn, 1972). To reduce student response time and possible fatigue prior to questionnaire

completion, the modified version was used to capture key points of the traditional 98-

item scale. The 24-item scale was based on the original MARS and has been used to

assess math anxiety in the college classroom setting (Camp, 1992).

Five tj/pes of mathematical problems assessed students' quantitative ability in the

third section of the questionnaire. The first problem assessed basic algebra knowledge

using numbers and a symbol to solve for the unknown variable "x". The second problem

asked students to solve for order of operations when parentheses were introduced with

numbers and multiple operations. The third problem introduced a stated or worded

algebraic situation asking students to solve for an unknown. The fourth problem asked

students to integrate accoimting concepts and calculate cost of goods sold. Finally, the

students were asked to solve a stated food cost percentage problem which combined prior

concepts germane to hospitality industry problem-solving and calculation ability.

A pilot study was conducted in the fall of 1999 at one university and revisions to

the data collection instrument and analytical procedures were made. The pilot study

served as a small-scale trial using a few subjects that would be related to those providing

information in tiie actual study (Shanklin, 1998). The practice run assisted in

23

determining flaws in design, data collection techniques, admmistration and scoring of

mstruments, and instrument imprecision (Sowell & Casey, 1986). The only changes to

the pilot study consisted of clarifying course names for mdividual institutions.

Data Collection Procedures

The study was approved by tiie Human Subjects Committee at tiie university. Surveys

were mailed directly to the instructors at the participating universities, and a letter was

sent with specific instructions on how to administer the survey. Freshman and senior

students were informed that theu: identity and responses were completely anonymous.

The study required approximately 10 minutes to complete, and the use of calculators was

not permitted when attempting to solve the quantitative problems. Completed surveys

were placed in a self-addressed stamped envelope and returned to the institution for

analysis.

Statistical Analysis

Data were analyzed using the SPSS 10 (1989-99) software package. Frequencies

were run to detect missing or erroneously recorded data information and to compile

reports on categorical variables. Descriptive statistics includmg mean, median, variance,

and standard deviation were reported for each numeric variable. Hypotheses testing was

non-directional because of lack of prior research to support directional testing. Chi-

square procedures tested categorical variables including demographic data and correct

math inventory responses for significant differences between observed and expected

24

frequencies. Correlation measured relationships between numeric variables for Likert-

scale responses to confidence and anxiety questions. Significance was set at A <_.05 to

allow for non-directional testing based on the lack of prior similar studies to

accommodate a sizable sample size.

Data Treatment

The data collected answered the following research questions:

1. Is there a relationship between student demographics and math confidence?

The variables high school grade point average, high school math grade point average,

college algebra, introductory cost accounting, cost control and accounting, and

financial analysis were crosstabulated with general anxiety levels on a variety of

quantitative subjects.

2. Is there a relationship between student demographics and math performance?

The variables of age, gender, class sizes, area of origin, parents education level, hours

of work per week, number of credit hours, full or part-time status, and enrollment

classification were crosstabulated with high school GPA and high school math GPA,

and college level quantitative courses including college algebra, introductory cost

accounting, cost control accoimting, and financial analysis.

3. Is there a relationship between math performance and student math confidence

levels?

25

Student grades in high school and math high school grades were combined with

grades in college quantitative courses and tiien crosstabulated with anxiety levels for

each of fourteen variables related to quantitative anxiety on the college level.

4. Does student attitude or anxiety to math relate to overall matii confidence level?

Responses to student perception of matii usefiilness, enjoyment, pleasantness, and

general liking of math were correlated with overall student quantitative confidence.

5. Are certain situations that contribute to math anxiety levels related to math

performance?

Fourteen specific anxiety questions related to math and accounting were assessed

individually and then crosstabulated with grades in college quantitative courses and

high school GPA and math GPA.

The following hypotheses were tested:

1. There is a relationship between student demographics and math confidence levels

2. There is a relationship between student demographics and math performance

3. There is a relationship between math performance and student math confidence levels

4. There is a relationship between attitude to math anxiety and math confidence level

5. There is a relationship between factors that contribute to math anxiety and overall

math performance

26

CHAPTER rv

RESULTS AND DISCUSSION

This section discusses the results of data from six university undergraduate hospitality

programs assessing math anxiety and performance. The following will be presented and

discussed: descriptive analysis of demographic characteristics; student high school math

performance and place of origin; completed quantitative courses; grades received in

completed quantitative courses; and results of quantitative ability assessment. Inferential

analysis hypotheses testing results will be presented for the relationships of assessment of

student demographics and confidence levels, demographics and math performance, math

confidence levels and college quantitative performance, attitude towards math and math

confidence level, and situations contributing to math anxiety level and quantitative

performance.

Demographic Characteristics

Participants were enrolled in introductory and senior seminar classes at participating

universities during the fall and spring semesters of 2000 and 2001. Four hundred twenty-

four students completed the questionnaire. More participants (48%) were 22 years of age

or older, with about one-third reporting ages of 20-21 years and 17% reporting ages of 17

to 19 years (Table 1). The majority of the participants were seniors (53%). The study

sample included more programs offering classes beginning at the junior level, which

coincides with more students indicating that they were upper classmen.

27

Table 1 Demographic Characteristics of the College Student Participants

Demographics Number (%)

Age 17-19 20-21 22 +

Gender Male Female No response

Classification Freshman Sophomore Junior Senior Graduate/ Other

Enrollment Classification Full-time Part-time No response

Credits l t o 3 4 to 6 7 to 10 11 to 15 16 or more No response

Hours worked per week Do not work l t o 9 10 to 19 20-29 30-39 40 or more No response

70 150 204

214 202 8

46 80 69 226 3

395 25 4

2 7 27 274 112 2

124 32 83 107 54 21 3

(17 %) (35 %) (48 %)

(51 %) (48 %) (2 %)

(11%) (19%) (16%) (53 %)

(1 %)

(93 %) (6 %) (1 %)

(.5 %)

(2 %) (6 %) (65 %) (26 %) (.5 %)

(29 %) (7 %) (20 %) (25 %) (13 %) (5 %)

(1 %)

Note: N=424

28

Observed was a nearly even gender distribution, with 51% males and 48% females.

Increased enrollment over the last few years has helped evenly distribute gender over the

surveyed campuses. Female students may be enrolling m hospitality programs more

because of increased quantitative anxiety levels. The association of hospitality programs

and low-skill levels may have helped to increase enrollment to even out the gender

distribution. The hospitality mdustry has been considered a male-dominated industry.

The rapid growth of the industry and the need for skilled workers has opened the door for

advancement opportunities for both men and women. The relatively even male-female

distribution indicates a changing industry and the importance of the role of females in the

fixture success of the hospitality industry.

Ninety-three percent of the students were enrolled full-time and 91% of the students

were taking 11 or more credit hours per semester. Work patterns were evenly divided

with more students (29%) not working; students working 20-29 hours per week

comprised 25% of the sample. Outside employment may indirectly contribute to anxiety

levels for the undergraduate hospitality student, and may also affect overall student

performance in other areas.

29

Student High School Matii Performance and Place of Origin

Students were asked to provide information about tiiefr hometown, high school, and

history of math performance in high school. Hometown designation was listed m broad

descriptive terms (rural, urban, suburban).

Most students (49%) originated from suburban areas (Table 2). The average high

school class size ranged from 201-500 students (38%). Sixty-tiiree percent of tiiose

surveyed had completed four years of high school matii and a B average was realized by

half (50%) of the respondents. Fifty-seven percent listed a B as tiieir overall high school

grade point average. Parent-educational level was high as 66% of the students' fatiiers

and 60% of mothers had attended college.

Students came from small to medium communities, and attended high schools with a

critical student population mass to offer adequate math preparation. Their high school

math grades indicate that they likely were adequately prepared to successfully navigate

quantitative courses in the collegiate arena. Their higher overall grade point average

suggested that they would be able to adapt to a slightly more difficult college

environment.

Overall, the respondents were better than average students, but not the best high

school students. Academically inclined students may choose different majors (e.g.,

engineering and business) which are perceived as rewarding graduates with greater career

success. Students choosing hospitality majors may realize their need to depend on other

skills within a field of study that brings reasonable financial rewards. Parents' high

education level may also contribute to college entry. The relatively equal educational

30

attamment of both parents indicates strong educational values that are subsequentiy

conununicated to theu children. This may influence tiie lesser academically inclined

student to attend college and may enroll in hospitality programs.

Table 2 Student Background Information on High School Performance and Original Community Student Information Number (%) Area of origin

Rural Urban Suburban Otiier No response

High school class size Less than 200 201-500 501-700 701 + No response

Years of high school math One or two years Three Four No response

High school math GPA A B C D

Overall high school GPA A B C D

Fathers education level Middle/junior high High school College or beyond Other/ not sure

Mothers education level Middle/junior high High school College or beyond Other/ not sure

114 92 206 10 2

149 162 80 32 1

35 119 269 1

104 211 99 10

133 240 47 4

12 114 279 19

6 151 254 13

(27) (21) (49) (2) (1)

(35) (38) (18) (8) (1)

(8) (28) (63)

(1)

(25) (50) (23) (2)

(31) (57)

(11) (1)

(3) (27) (66) (4)

(I) (36) (60) (3)

31

Ouantitative Courses Completed bv Hospitality Students Prior to Study

Students were asked which math and accoimting courses were completed within the

hospitality curriculum. Requued courses included college algebra, statistical methods,

introductory accounting, cost accounting and finance. While most students (66%)

completed college algebra, other quantitative courses had lower completion rates

(statistics -51%, introductory hospitality accountmg - 57%, cost control - 42%, financial

analysis -29%). Students had not completed several quantitative courses at the time of

the survey, yet most were classified as seniors. Accounting, finance and statistics courses

are more advanced courses, and are somewhat more difficult than an introductory math

course.

Grades Received in Completed Quantitative Courses

Students indicated the eamed letter grades in each completed quantitative course

(Table 3). A high rate of "no response" in this area coincided with the relatively low

completion rate of many courses at the time of survey administration. Of the students

completing college algebra, more received a grade of B (20%). Students completing the

introductory accounting course had similar results with 22% receiving a B. While

student grades continued to cluster in the B range, the actual percentage earning this

grade declined as tiie course difficulty increased.

Accounting and finance courses are more difficult at tiie higher level. In addition to

courses containing quantitative expectations, students must integrate new tiieory and

problem-solving skills to successftilly complete tiiese courses. There is more information

32

to assimilate, and tiie exams are generally more difficult. These upper-level classes are

designed to test the skills package of students preparing to enter the workforce.

Table 3 Grades Received in Completed Quantitative Courses

Courses

College algebra A B C D No response

Introductory Hospitality Accounting A B C D No response

Cost Control and Accounting A B C D No response

Financial Analysis A B C D No response

Note: N=424

Number (

77 ( 84 ( 60 1 7 ( 196 (

69 ( 92 ( 51 ( 2 ( 210

55 82 47 5 235

42 60 50 14 258

{%)

[18%) [20 %) [14 %) [2 %) [46 %)

[16 %) [22 %) [12%) [1 %) (49 %)

(13 %) (19%) (11%) (2 %) (55 %)

(10%) (14 %) (12%) (3 %) (61 %)

33

Student Ouantitative Ability

Students attempted six basic quantitative problems without calculators. The first

question was a basic matii problem, and the students solved for tiie value of "x". Ninety-

two percent of the students correctly solved the problem (Table 4). The next question

asked the students to solve an order of operations problem, assessing knowledge of

parentiieses use in an equation. Eighty-eight percent of the students correctly answered

tiie question. A simple percentage problem followed, and ninety percent of the students

answered correctly.

The next question assessed ability to average, asking the students to calculate a missing

test grade to determine a final average. This was the first problem in which words were

added to the quantitative problem. Correct response rate dropped to 52%. Students were

then asked to interpret data to calculate the accounting concept of cost of goods sold.

Sixty-four percent of the students answered correctly. The final problem asked the

students to calculate the foodservice concept of food cost percentage. Students had to

read data and interpret the information to set up the problem correctly. Seventy percent

answered correctly.

The problems were intentionally ordered with an increasing level of concept and

difficulty. The first three problems did not include words and most students (90%)

calculated the correct answer. As words were added and concept difficulty increased,

success decreased. This occurrence may indicate an underlying problem of student

quantitative anxiety beyond calculation ability.

34

Table 4 Results of C iantitative Ability Assessment

Ouantitative problem type Number 1%}

Basic math Correct Incorrect No response

Order of operations Correct Incorrect No response

Percentage Correct Incorrect No response

Averaging (addition of words) Correct Incorrect No response

Cost of goods sold Correct Incorrect No response

Food Cost Correct Incorrect No response

Note: N=424

388 18 18

375 21 28

383 24 17

222 168 34

273 111 40

298 90 36

(92)

(4) (4)

(88)

(6) (6)

(90)

(5) (5)

(52) (39) (9)

(64) (26) (10)

(70) (21)

(9)

35

Student Math Confidence and Math Anxiety

Student quantitative confidence and dimensions of math performance were assessed

before completion of a math anxiety assessment. Overall confidence was measured usmg

a Likert-type scale (1= not confident, 5= completely confident). The mean for overall

quantitative confidence was 3.5 (SD=1.1). The scale for the issues related to math

confidence factors was reversed (1= confidence, 5= no confidence). Categories included

liking math (mean = 3.3, SD = 1.5), enjoying matii (mean = 3.4, SD = 1.4), finding matii

pleasant (mean = 3.4, SD = 1.4), and usefulness of math (mean = 2.9, SD = 1.6).

Students apparently perceive themselves more confident in quantitative problem-

solving abilities than not. However, the scale measuring their attitude when approaching

these situations may affect performance. Negative feelings such as dislike and

unpleasantness may undermine expressed confidence. Students appear to value math

somewhat more than they like or enjoy it.

The anxiety assessment implemented tiie MARS-r inventory (Camp, 1992). Overall

anxiety level and fourteen specific situations that a student might encounter to increase

math anxiety during the course of tiie semester were presented in a Likert-type scale (1 =

no confidence, 5 = confidence). Student responses indicated that testing situations

increased anxiety levels (Table 5). Taking a final examination in a math or accounting

ranked highest on tiie anxiety scale (mean = 3.8, + 1.6). Studying for a math or

accounting test ranked second (mean = 3.3, + 1.6), and otiier test-related variables

comprised tiie highest levels of quantitative anxiety.

36

Table 5 Student Reported Math Anxiety Levels

Math anxiety aspect Mean^+ SD

Starting a new chapter in a math/accounting book 2.3 + 1.7

Listening to a lecture in a math/accounting class 2.6 + 1.7

Registering for a course in math or accounting 2.6 + 1.7

Reading and interpreting graphs or charts 2.7 + 1.6

Picking up your book to begin work on an assignment 2.8 + 1.7

Taking a quiz in a math/accounting course 2.8 + 1.7

Given a difficult homework assignment 2.9 + .07

Walking into a math/accounting class 2.9 + 1.7

Waiting for the results of your math/accounting test 3.0+1.8

Thinking about an upcoming math/accoimting test 3.1 + 1.7

Being given a "pop" quiz in a math/accounting class

Studying for a math/accounting test

' Based on a scale 1= none; 5 = very much ^ sd = standard deviation

3.2 + 1.7

Reading a math/accounting formula 3.2 + 1.6

3.3 + 1.6

Taking a final examination m a math/accounting class 3.8+1.6

37

Class performance appeared to contribute little to no anxiety. Issues such as reading

graphs, registering for a course, and starting a new chapter in a math or accounting class

were associated with lower anxiety levels (Table V). The descriptive inventory indicated

testing and evaluation situations may be the greatest contributors to anxiety levels and

may be a target for student assistance. Other math-related activities contributing to lower

stress levels may be useful to support students preparing for higher intensity exam

situations.

38

The Relationship Between Confidence Levels and Demographics

Certain demographic factors were related to student confidence level. There was a

positive significant relationship between age and confidence level (p < .000). Older

students were more confident when approaching quantitative courses. Confidence

levels also were positively related to student enrollment classification (p < .000).

Higher-level students exhibited more confidence with overall quantitative

performance.

Confidence levels were not different student was enrolled on a full or part-time

basis or if the number of credit hours varied. There was no significant relationship

found between confidence level and gender. Math confidence levels also were

directiy related to completion of quantitative courses (p < .000). Other unrelated

demographics to student math confidence level included the number of hours that a

student spends working while in college, area of origin, high school class size, and

both parents' education levels.

Student confidence levels appear to be more closely related to age-related

variables. Older students exhibit higher math confidence levels. Older more mature

students more confident in math may be cultivated as good role models to

underclassmen.

The Relationship Between Math Performance and Demographics

Matii performance was measured by grades received in high school and college

quantitative courses. More years of high school matii positively impacted overall high

39

school math performance (p< .000). Female students had better overall grades in high

school than males. Students graduating withm classes of smaller class size yielded a

higher overall high school GPA (p < .000). High school math GPA was significantly

related to the number of hours a college student worked in a week (p < .000).

On the college level, age and enrollment status positively and significantly affected

college math performance (p < .000). Older students tended to do better in

quantitative courses. Students may wait until the last possible moment to enroll in

required quantitative coursework. Eighty percent of those still needmg to complete

introductory accounting were not freshman (p < .000). The cost accounting and

finance classes shared similar outcomes and characteristics and also was significantly

and positively related to the number of years of high school math (p < .000). In the

cost accounting class parents' education level positively affected student

performance.

Course performance appears related to student maturity and secondary level

preparation. Advising staff also may need to be more aware of high school

performance and the tendency to delay enrollment. These significant factors affecting

math performance could be areas on which to base future assistance efforts.

Confidence and Math Performance

Student confidence levels were crosstabulated with performance variables of high

school matii and overall grade pomt average (GPA), grades eamed in college level

quantitative courses, and results from the survey matii quiz. High school math and

40

overall high school GPA positively impacted student math confidence (p < .000).

Student math performance in math during high school may be an important

determinant for quantitative success or failure on tiie college level. Students may

already have predetermined notions of ability to succeed in quantitative courses prior

to entering college.

Confidence levels were similarly related to grades received in quantitative college

level courses (p < .000). Students performing well in college algebra had higher

confidence levels toward math in general (p< .000). High grades in accounting and

cost accounting also were positively related to math confidence (p < .000). Similar

results were found for the financial analysis course (p < .000). These college level

courses are requued to complete a baccalaureate degree, and student confidence can

impact enrollment, success in completion, or repeating the class and struggling to

pass it during a second attempt.

Student confidence also impacted success in answering the six quantitative

problems on the survey. As the questions increased in difficulty, student confidence

levels decreased. Basic problems were met with success and high confidence (p <

.000). The addition of words were added to the problem and the increase of math

complexity negatively impacted student confidence and response accuracy (p < .000).

Ability to perform math courses in high school and college is an expectation of

today's youth. Performance levels must be closely monitored to ensure that student

remains stable while the quantitative courseload increases in difficulty. Student

41

confidence in math can significantly impact math course performance throughout the

students' college career.

Overall Confidence and Aspects of Math Confidence Levels

A correlation analysis determined significance between overall math confidence

and aspects of math confidence. Math confidence factors included pleasantness,

enjoyment, affinity, and usefulness. These factors were tested against each other.

Significance levels were determined to be p <.000 for all comparisons. Correlational

values were reversed due to the reversal of the scales.

Student responses indicate there was a strong relationship between pleasantness (r =

-. 478), enjoyment (r = -. 487), and affinity (r = -. 487). The correlation coefficient

for usefiilness was lower (r = -. 294). The Pearson's r for math usefulness was the

same between students with overall math confidence (Table 6).

Confidence levels and the various perceptions of quantitative confidence will

greatly mfluence math performance. While students do not necessarily associate

positive emotions with math, they maintain an attitude of acceptance. A more

positive student attitude assists in mamtaining the attention level during the class

time.

42

Table 6 Overall Confidence Levels and Math Confidence (N = 424)

Confidence Pearson's r Sig. (2-tail)

Enjoy Pearson's r Sig. (2-tail)

Like Pearson's r Sig. (2-tail)

Pleasant Pearson's r Sig. (2-tail)

Usefiil Pearson's r Sig. (2-tail)

Confidence

1.000

-.487 .000

-.487 .000

-.478 .000

-.294 .000

Enjoy

-.487 .000

1.000

.915

.000

.909

.000

.515

.000

Like

-.487 .000

.915

.000

1.000

.872

.000

.543

.000

Pleasant

-.478 .000

.909

.000

.872

.000

1.000

.479

.000

Usefiil

-.294 .000

.515

.000

.543

.000

.479

.000

1.000

43

Student Anxiety of Basic Ouantitative Course Components and Ouantitative Performance

The anxiety variables of registering for a course, tiiinking about a pending test,

taking a quiz, picking books to begin work on a new assignment, and listening to a

lecture had significant relationships witii all of tiie tiuee aspects of matii performance

variables (Table 7). The anxiety variables of homework, reading and mterpreting

graph, walkmg into class, staring a new chapter, studying for a matii or accounting

class, taking a "pop" quiz, reading a matii or accounting formula, waiting for tiie

results of your exam, and taking a final exam in a quantitative course had at least one

insignificant matii performance relationship. Except for tiie final exam anxiety factor,

college algebra was not significant. High school preparation appeared to mitigate

stress, as overall math GPA seemed insignificant more often. Other quantitative

variables not related appeared to be courses students had not completed.

The addition of any kind of quantitative situation seems to increase stress levels.

The student may have viewed the math inventory quiz as a surprise or unannounced

situation that impacted outcome. Student course performance affects student anxiety.

The higher the student math performance level, the lower the student math anxiety

level. Students experienced anxiety with a majority of the fourteen quantitative

course situational factors. Results of the analysis indicate that student confidence

levels can be affected by all facets of tested college quantitative variables.

44

Table 7 Relation of Anxiety Levels by Math Performance

Anxiety Inventory Question

Being given a difficult homework assignment, and having it due next class

Reading and interpreting graphs or charts

Registering for a course in Math or Accounting

Thinking about a pending Math/Accounting test the day before.

Walking into a Math/accounting class

Significant Math Performance Variables Order of operations problem (.006), Percentage problem (.000),

Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.052), Food cost problem (.000), Basic accounting (.005) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost (.000), Basic accounting course (.005), Cost accounting course (.000), College algebra course (.044),

Financial analysis course (.042) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000),

Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Accounting course (.006), Cost accounting course (.001), College algebra course (.000), Financial analysis course (.000), HS GPA (.000), HS math GPA (.000)

Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.001), Food cost problem (.001), Basic accounting course (.000), Cost accounting course (.001), Financial analysis course (.030), HS GPA (.003), HS matii GPA (.016)

Nonsignificant Math Performance Variables Basic math problem, HS " GPA, HS math GPA, Cost accounting course, Financial Analysis course. College algebra course College algebra course, Financial analysis course, HS GPS, HS math GPA

College algebra course

45

Table 7 Cont. Anxiety Inventory Question

Starting a new chapter in a Math/Accounting book

Taking a quiz in Math/Accounting course

Studying for a Math Accounting course

Picking up your book to begin work on an assignment

Significant Math Performance Variables Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Basic accounting course (.009), Cost accounting course (.004), HS GPA (.000). HS math GPA (.000) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods problem (.000), Food cost problem (.000), Basic accounting course (.011), Cost accounting course (.000), College algebra course (.000), Financial analysis course (.000), HS GPA (.000), HS math GPA (.010) Basic math problem (.000), Order of operations (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Basic accounting course (.008), Cost accounting course (.000), College algebra course (.005), Financial analysis (.045), HS math GPA (.000) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.001), Food cost problem (.000), Basic accounting course (.000), Cost accounting course (.001), College algebra course (.010), Financial analysis course (.001) , HS GPA (.037), HS madi GPA (.002)

Nonsignificant Math Performance Variables College algebra course, Financial analysis

HSGPA

46

Table 7 Cont. Anxiety Inventory Question Significant Math Performance

Variables Nonsignificant Math Performance Variables

Being given a "pop" quiz in a Math/Accounting class

Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Cost accounting course (.038), Financial analysis (.031), HS math GPA (.002)

Reading a Math/Accounting formula

Basic math problem (.000), Order of operations (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.003), Food cost problem (.000), Basic accounting course (.043), HS math GPA (.001)

Listening to lecture m a Math/Accounting class

Waiting for the results of your Math/Accounting test

Taking a final exammation m Math/Accounting class

Basic math problem (.000), Order of operations (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold (.000), Food Cost problem (.000), Basic accounting course (.040), Cost accounting course (.020), College algebra course (.008), Financial analysis course (.045), HSGPA (.014), HS math GPA (.000) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Basic accounting course (.028), HS GPA (.040), HS math GPA (.000) Basic math problem (.000), Order of operations problem (.000), Percentage problem (.000), Averaging problem (.000), Cost of goods sold problem (.000), Food cost problem (.000), Cost accounting course (.002), HS matii GPA (.000)

Basic accounting course, college algebra course, HSGPA

Cost accounting course. College algebra course, Financial analysis course, HSGPA

Cost accounting course. College algebra course, Financial analysis course

Basic accountmg course, Financial analysis course, HSGPA

47

CHAPTER V

CONCLUSION

Quantitative anxiety for undergraduates in hospitality programs is a product of

many different factors. Some students choose hospitality as a major under tiie

assumption that it is not very math intensive. Anxiety levels can escalate to tiie point

where students will terminate tiieu college careers. Currently, no programs are in

place to help students who are experiencing these problems. Data fi-om tiie study

indicates that levels are high enough to warrant furtiier study in this field.

The purpose of this research was to assess math anxiety performance levels of

hospitality undergraduate students at the beginning and termination of their college

career. Specifically studied were demographics, math confidence and anxiety levels,

math performance ability and the interrelationship between these factors. Six

accredited four-year U.S. hospitality programs volunteered to represent accredited

programs throughout the country and were reasonable geographically representative.

Four hundred twenty-four surveys were collected between the Spring 2000 and the

Spring 2001.

The questionnaire captured the independent variables of demographic information,

math confidence, and math anxiety levels. The dependent variable math and

accounting performance, was defined as a letter grade received in high school and

college courses requiring quantitative tasks and student performance on a math

mventory within the instrument.

48

Descriptive statistics including mean, median, variance, and standard deviation were

reported for each numeric variable. Chi-square procedures tested categorical variables

for significant differences between observed and expected fi-equencies. Correlations

tested the difference between categorical and numeric data.

Summary of Findings

Several relationships were found between the independent and dependent variables.

Significant relationships existed between student demographics, math confidence levels

and math performance. Student math confidence level also affected math performance.

Aspects of math confidence were related to overall confidence levels. Situations

contributing to math anxiety levels affected overall student math performance. The

following will summarize the testing of hypotheses.

Hypothesis 1: Relationship Between Student Demographics and Math Confidence Level

Student demographics were evaluated to provide descriptive data. Student math

confidence levels were then crosstabulated with demographic variables.

Results of analysis indicate that student confidence is related to some demographic

variables. A positive relationship existed between age of the students and overall

confidence level. Older students were more confident when approaching quantitative

courses. Confidence levels also were positively related to tiie enrollment classification of

the students. Upperclassmen exhibited more confidence in quantitative courses.

49

The remammg demographic variables were not significant in relation to math

confidence levels. Hypothesis 1 was supported for age and enrollment classification.

Hypothesis 2: Relationship Between Demographics and Math Performance

Student demographic variables were crosstabulated with math performance in high

school, grades received in quantitative college courses, and the math quiz section of the

survey.

The number of years of high school math completed positively impacted overall high

school math performance. Female hospitality students made better grades in high school

than males. Smaller class sizes yielded a higher overall high school grade point average.

College enrollment status positively and significantly affected college math

performance. Older students did better in quantitative courses. Students may wait until

the last possible moment to take the required quantitative courses. Introductory

quantitative courses were being taken by a large majority of upper-level students at the

time of the survey.

Parents' education level also positively affected student performance in quantitative

courses. Course performance appears to be related to the maturity of tiie student and

preparation for upper level quantitative coursework. Hypothesis 2 was supported.

50

Hypothesis 3: Relationship Between Math Performance and Student Confidence Levels

Student confidence levels were compared to performance variables of high school

math and overall grade point average (GPA), grades eamed in college level quantitative

courses, and response to the math quiz on the survey.

High school math and overall high school GPA positively impacted student math

confidence. Student performance in high school may be an important determinant for

quantitative success or failure on the college level.

Confidence level was similarly related to grades in quantitative college level courses.

Students performing well in college algebra had higher overall confidence levels toward

math. High grades in introductory and cost accounting as well as financial analysis

courses also were positively related to math confidence.

Student confidence also impacted success in answering the six quantitative problems

on the survey. As the questions increased in difficulty, student confidence levels

decreased. The addition of words were added to the problem and the increase of math

complexity negatively impacted student confidence and response accuracy. Hypothesis 3

was supported.

Hvpotiiesis 4: Student Overall Math Confidence and Aspects of Math Confidence

Students perceived themselves as fairly confident in general when approaching

quantitative situations. Overall confidence was strongly positively correlated with

expressed emotions or feelmgs about matii. The overall confidence level did not impair

51

students valumg math. While affectmg emotions are difficult to influence, and

understanding of these would be of help in the design of math assistance programs.

Hypothesis 4 was supported.

Hypothesis 5: Situational Variables Affecting Math Anxiety and Math Performance

Students were asked to rate overall anxiety levels on 14 quantitative course scenarios

contained in the MARS-r inventory (Camp, 1992).

Anxiety levels affected math performance in almost all quantitative situations. With

the exception of classes not taken during the time of the survey, student anxiety levels

were found to be related to all three major sections of quantitative performance. Anxiety

level affected students' ability to perform the calculation problems at the end of the

survey. Hypothesis 5 was supported.

Comparison of Results to Prior Works

The current study provided similar yet contrasting results when compared to prior

works. Results of the study were similar to a study conducted by Engelhard (1989),

demographic characteristics affected student math confidence. However, Engelhard

determined that parents' education level was significant although the current study did

not confirm this finding. Engelhard (1989) also noted tiiat females exhibited higher

anxiety levels tiian males. The new study also could not support that hypotiiesis.

Students' negative attitude toward matii was confirmed in the present research, which

was comparable to previous findings.

52

Llabre and Suarez (1985) also reported tiiat females reported higher anxiety levels tiian

men. In addition, females witiiin tiie study had higher course grades tiian tiieir male

counterparts. Females m the current study did have an overall higher GPA in high school

than their male counterparts, but anxiety levels were not significantiy different between

genders.

Jackson and Leffingwell (1990) pomted out tiiat new quantitative skill-level problems

can increase student anxiety. From the results of tiie six quantitative problems that tiie

students calculated, the same would appear to be true. The addition of words to a

problem saw the number correct decrease dramatically, mdicating that anxiety levels are

still very pronounced a decade later.

Handler (1990) also noted that exam or test-taking fear was still a problem for older

men and women. This study did not include older adults, but it is worth noting that test-

taking anxiety is a problem for students of all ages and does not appear to significantly

decrease with age.

Su, Miller, and Shanklin (1997,1998) listed several factors that hospitality

professionals are looking for when hiring industry professionals. Quantitative skills are

vital for success in career positions in the hospitality profession. Results of this study

indicated that students are having dificulty grasping some these concepts needed to

ensure future success.

53

Conclusion and Applications

Hospitality student anxiety levels were found to experience significantiy high anxiety

levels to warrant fiirther study in this field. There are still few, if any, programs in place

to assist students m alleviating tiieir quantitative anxiety. In addition, educators must

realize the role they play in ensuring student success.

Tobias (1991) has laid the foundation for an idea that hospitality programs need to

adopt. Hospitality students need an environment where they can receive assistance with

quantitative courses. A clinic can be developed in hospitality programs to cater to their

needs. It is important to note that these clinics are not meant to be study sessions for

students. Students are encouraged to voice their concerns as soon they see a concept that

may cause them to feel nervous or anxious. Other students would then discuss what they

are feeling at that time. The clinic instructor must let the students set the pace so they

feel as comfortable as possible. The instructors would assist the students as much as

possible; however, as soon as the students are comfortable on their own, the clinic is no

longer available to them. Anxiety clinics are meant to assist students to deal with the

underlying problem, not to help them to study for regularly scheduled exams.

Educators must not forget the role they play in student math performance and

confidence. Students will only be as effective as the teachers they learn from. Teachers

need to recognize that they set the pace for leaming, and that tiiey should use easy to

follow examples. Abstract formulas and concepts should be thoroughly explained.

Educators should make tiieir goal to help students grasp tiie concepts and comprehend tiie

material.

54

Limitations of the Research

The lack of random sampling within the hospitality student population somewhat

limits general ability. The response level (424) and tiie intention to contact schools in

many geographic areas would strengthen tiie study against tiiis limitation.

The second limitation concemed tiie inability to cover all factors contributing to matii

anxiety. While many significant relationships were found, tiiere may be additional

factors contributing to student math anxiety.

Areas for Future Research

Results of the study indicate that educator approaches to teaching quantitative courses

must be examined fiirther. Students have confirmed the impact that teachers have on

quantitative performance. In addition, another study should be run on other collegiate

programs that are not math intensive to see if similar survey results are achieved.

A tool must be developed to identify the math anxious student, so that a clinic can be

put in place to reduce their anxiety levels. Results of this study have identified

characteristics that researchers could look for to determine the most probable candidates.

Areas to focus on would be overall school performance, and career tracks of the students

entering college.

Student anxiety levels in relation to quantitative courses in hospitality programs are

significant, yet there are no programs in place to assist students alleviate the anxiety. The

transition fi-om high school quantitative courses to college level quantitative courses is

55

stressful for most hospitality students, and various demographic factors and classroom

situations only seem to compound their anxiety levels.

Performance levels indicate that the knowledge and skill level is in place for most

students to do well in quantitative courses. However, student confidence levels indicate

that they are struggling with comprehending most quantitative college courses.

56

REFERENCES

Agresti, A., & Finlay, B. (1997). Statistical methods for the social sciences. Engelwood Cliffs, N.J. p.43 8-473.

Arthur Anderson (2000). Report on hospitality education programs. Presented August 15, 2000 at Texas Tech University RHIM Conference.

Breiter, D (1993). Strategies for the retention of undergraduate hospitality students. Hospitality and Tourism Educator, 5(4), 71-73.

Breiter, D., & Clements, C.J. (1996). Hospitality management curricula for tiie 21'^ century. Hospitality and Tourism Educator, 8(\), 57-60.

Bureau of Labor statistics (2001). 1999-2000 occupational handbook- Restaurant and food service Mananagers. Available: hftp://stats, bis. 2ov/oco/. Viewed March 13„ 2001.

Camp, C. (1992). "A Comparison of the Math Anxiety and Math Self-Efficacy Constructs." Master's Thesis. Virginia Commonwealth University.

Dew, K.M., Galassi, J., & Galassi, M. (1984). Math anxiety: Relation with situational test anxiety, performance, physiological arousal, and math avoidance behavior. Journal of Counseling Psychology, 31 (4), 580-583.

Engelhard Jr., G. (1990). Math anxiety, mother's education and the mathematics performance of adolescent boys and girls: Evidence from the United States and Thailand. The Journal of Psychology, 124(3), 289-298.

Handler, J. (1990). Math anxiety in adult leaming. Adult Learning, 1(6), 20-26.

Jackson, C , & Lefingwell, R. (1999). The role of instructors in creating math anxiety in students from kindergarten through college. The Mathematics Teacher, 92(1), 583-586.

Kleinfeld, J. (1999). Gender and myth: Data about student performance. Current 412, 3-10.

Koteff, E. (2000).Operators dig into a "Mary Poppins" bag of tricks to successftilly manage a restaurant. Nations Restaurant News, August 7, 2000, p.39.

Llabre, M., & Suarez, E. (1985). Predicting matii anxiety and course performance in college women and men. Journal of Counseling Psychology, 32(2), 283-287.

57

National Restaurant Association (2001). Get ahead: opportunities for education and professional development in the restaurant industry. Available: http://restaurant, ors. Viewed March 13, 2001.

Richardson, F.C., & Suinn, R.M. The mathematics anxiety rating scale: psychometric data. Journal of Counseling Psychology, 19(6), 551-554.

Ruben, T. (1998). "A comparison between male and female mathematics anxiety at a community college." Master's Thesis. Central Connecticut State University.

Schmidgall, R., Rutherford, D., Sciarini, M., & Woods, R. (1999). Preparation, performance, payoff. Lodging 55-59.

Skiba, A. E. (1990). Reviewing an old subject: Math anxiety. The Mathematics Teacher 84(3), 188-89.

Sowell, E.J., & Casey, R.J. (1982). Research methods in Education. Belmont, Califomia: Wadsworth Publishing Company.

SPSS Version 10.0.0 (1989-1999). SPSS Inc., Chicago, 111.

Stone, D.N., Arunachalam, V., & Chandler, J.S. (1996). An empirical investigation of knowledge, skill, self-efficacy and computer anxiety in accounting education. Issues in Accounting Education, 11(2), 345-376.

Su, A.Y., Miller, J.L., & Shanklin, C.W. (1997/98). Perceptions of industry professionals and program administrators about accreditation curriculum standards for hospitality programs. Journal of Hospitality and Tourism Education, 9(4), 36-40.

Texas Tech University (2000). Are you "Test Anxious"? Program for Academic Support Services (PASS).

The International Council on Hotel Restaurant Institutional Education (CHRIE) (2000). CHRIE annual publication.

Tobias, S. (1991). Math mental anxiety. Adult Learning, 39(3), 20-26.

Wadlmgton, S.A., & Bitner, J. (1992). The treatment of math anxiety and negative math self-concept in college students. College Student Journal. 26(1), 61-65.

Williams, J.A., & DiMicco, F.J. (1998). The challenge of mutidepartment management for fiiture hospitality graduates. Journal of Hospitality and Tourism Education 10(\), 13-17.

58

APPENDIX

SURVEY INSTRUMENT

59

Section I

Instructions: Please mark an (x) in tiie blank beside tiie answer which best describes your current status regarding math and math related courses.

What is your age? (1) 17-19 (2)20-21

(3) 22 or older

2. What is your gender? Male Female

3. What is your current enrollment status? (1) Freshman (2) Sophomore (3) Junior

(4) Senior (5) Graduate/Otiier

What is your enrollment classification? (1) Full-time

How many credits are you currently registered for? (1) 1 to 3 credits (2) 4 to 6 credits (3) 7 to 10 credits

(2) Part-time

(4) 11 to 15 credits (5) 16 or more credits

6. What Math/Accounting classes have you completed with a "C" or better? Matii 1320 RHIM 2322 Matii 2300 RHIM 3322

RHIM 4322

7. How many hours a week do you spend working on your job? (1) Do not work (4) 20-29 hours per week (2) 1-9 hours per week (5) 30-39 hours per week (3) 10-19 hours per week (6) 40 or more hours per week

8. What area best describes where you were originally raised? (1) Rural (3) Suburban (2) Urban (4) Otiier

9. What was the size of your high school graduating class? (1) Less tiian 50 (2)51-200 (3)201-500

(4)501-700 (5)701 +

60

10. How many years were you enrolled in math during high school (grades 9-12)? (1) One year (3) Three years (2) Two Years (4) Four Years

11. What was your grade point average for high school matii courses? (1)A (3)C (2) B (4) D or less

12. What was your cumulative high school grade point average? (1)A (3)C (2) B (4) D or less

13. What is the highest level of school that your father has completed? (1) Middle school / Jr. High (3) College or beyond (2) High School (4) Otiier/ Not sure

14. What is tiie highest level of school that your mother has completed? (1) Middle school / Jr. High (3) College or beyond (2) High School (4) Otiier/ Not sure

15. In general, how confident do you feel in your ability to do math? (Circle the number that most accurately reflects your feelings) 1 2 3 4 5 Not Completely

Confident Confident

16. Please rate how you feel about "Doing Math" on the following dimensions

(+) Like 1 Enjoyable 1 Pleasant 1 Usefiil 1

2 2 2 2

3 3 3 3

4 4 4 4

5 5 5 5

( - ) Dislike Unenjoyable Unpleasant Useless

17. What grade did you receive m the followmg courses (seniors only) Accounting/Cost controls I A B C D Accounting/Cost controls II A B C D College Math A B C D Finance D

61

Section n

Read each statement careftilly. Cu*cle one number below for each question tiiat best describes tiie level of anxiety you would experience in each situation based on tiie following scale.

None A little A fair amount Much Very much 1 2 3 4 5

1. Being given a difficult homework assignment, 1 2 3 4 5 and having it due the next class.

2. Reading and interpreting graphs or charts. 1 2 3 4 5

3. Registering for a course m Matii or Accounting. 1 2 3 4 5

4. Thinking about an upcoming Math/Accounting test 1 2 3 4 5

the day before.

5. Walking into a Math/Accountmg class. 1 2 3 4 5

6. Starting a new chapter in a Math/Accounting book. 1 2 3 4 5

7. Taking a quiz in a Math/Accounting course. 1 2 3 4 5

8. Studying for a Math/Accounting test. 1 2 3 4 5

9. Picking up your book to begin work on 1 2 3 4 5

an assignment.

10. Being given a "pop" quiz in a Math/Accounting class. 1 2 3 4 5

11. Reading a Math/Accounting formula 1 2 3 4 5

12. Listening to lecture in a Math/Accounting class. 1 2 3 4 5

13. Waiting for the results of your Math/Accounting test. 1 2 3 4 5 14. Taking a final examination in a Math/Accounting class. 1 2 3 4 5

62

Section i n

Read each problem carefully, then select tiie best answer.

1. Find tiie value of "x" if 10 + 5x = 60 (1) 12 (2) 10

2. What is tiie value of7 + ( 1 4 x 3 ) - 4 ? (1)38 (2) 35

3. Whatis25%of200? (1) 25 (2) 50

4. You have three test scores of 80, 75, and 65. What grade will you need to receive on your fourth exam to finish with a 70 average for the course?

(1) 60 (3) 70 (2) 65 (4) 80

4. Beginning Inventory = 20,000, Purchases=30,000, Ending Inventory= 10,000 What is the cost of goods sold?

(1) 60,000 (3) 50,000 (2) 20,000 (4) 40,000

(3)5 (4)14

(3)45 (4)41

(3)75 (4) 100

5. If food cost is $6.00 and food sales are $24.00, what is tiie food cost percentage?

(1) 20 (3) 25 (3) 30 (4) 35

63

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