Determinants of students learning case study in macroeconomics at the university of econommics ho chi minh city

I
UNIVERSITY OF ECONOMICS

INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY - VIETNAM

THE HAGUE - THE NETHERLANDS

THE VIETNAM- NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF STUDENT'S LEARNING:
CASE STUDY IN MACROECONOMICS
AT THE UNIVERSITY OF ECONOMICS- HO CHI MINH CITY
~

-~-~--

~

-~~-

--~--

By Le Thanh Nhan

MASTER OF ARTS IN DEVELOPMENT ECONOMICS
• BQ GIAO DVC DAO T~O
TRliONG fl~l HQC KINH TE TP.HCM

THU'VIEN
~J ~{r
HO CHI MINH CITY, NOVEMBER 2009


UNIVERSITY OF ECONOMICS

INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY - VIETNAM

THE HAGUE -THE NETHERLANDS

THE VIETNAM- NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

A thesis submitted in partial fulfillment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

DETERMINANTS OF STUDENT'S LEARNING:
CASE STUDY IN MACROECONOMICS
AT THE UNIVERSITY OF ECONOMICS- HO CHI MINH CITY
By Le Thanh Nhan

Academic Supervisors:
-

Assoc. Prof. Nguyen Trong Hoai, PhD

-

Chau Van Thanh, M.A

HO CHI MINH CITY, NOVEMBER 2009


CERTIFICATION
I declare that the thesis hereby submitted for the Master degree at the Vietnam Netherlands Programme for M.A in Development Economics is my own work
and has not been previously submitted by me at another university for any
degree. I cede copyright of the thesis in favor of the Vietnam - Netherlands
programme for M.A in Development Economics at the University of Economics,
Ho Chi Minh City.

Ho Chi Minh City, November 2009

Le Thanh Nhan

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ACKNOWLEDGEMENT
I would like to express my gratitude to all those who gave me the possibility to
complete this thesis.

I am most grateful to my supervisors, Assoc. Prof. Dr. Nguyen Trong Hoai and

Mr. Chau Van Thanh, who have instructed, encouraged and given me comments
for my thesis, as well as forgiven my mistakes while I was carrying out this
research.

I would like to thank to all lectures and staff of the Vietnam - Netherlands
Programme at the University of Economics, Ho Chi Minh City .

. I also want to say thank you to my colleagues and friends at the Office of
Undergraduate Training and Students Service Office at the University of
Economics, Ho Chi Minh City for their assistance in the process of my thesis
completion.

Finally, I especially thank to my partner friend, who hel_2ed _me in __finding __
materials, designing the survey and collecting data for the thesis.

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ABSTRACT
The objective of this thesis is to fmd out the determinants that influence the
performance of studying macroeconomics and their relationships. The scope of
this research is limited to sophomore students at the University of Economics, Ho
Chi Minh City.

In the conceptual framework, hypotheses about determinants related to
performance of studying macroeconomics were proposed. They are students'
aptitude,

efforts,

attitude toward economics along with their personal

characteristics.

A survey designed from Survey Economic Attitude from the National Committee
on Economic Attitude Measurement has been used with Exploratory Factor
Analysis to measure if the theoretical constructs in this research were satisfactory
in terms of reliability and validity. The relationships and hypotheses then have
been tested by using a Two Stage Least Square method.

The main findings are the significant impacts of aptitude and efforts on studying_ __ .... ···-macroeconomics but the attitude toward it.

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TABLE OF CONTENTS
CERTIFICATION ................................................................................................... i
AC:KN"OWLEDGEMENT ..................................................................................... ii
ABSTRACT ............................................................................................................ iii
TABLE OF CONTENTS ...................................................................................... iv
LIST OF TABLES ................................................................................................ vii
LIST OF FIRGUES .............................................................................................. vii

Chapter 1: Introduction ......................................................................................... 1
1.1 Problem statement .......................................................................................... 1
1.2 Research Objectives ........................................................................................ 3
1. 3 Research questions ......................................................................................... 4
1. 4. Research methodology ................................................................................... 4
1. 5 Delimitation .................................................................................................... 4
1.6 Thesis structure: ............................................................................................. 5

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-ehapter~:-biterature-review: ....... ~.-:~~:.~:-.~:~~::::~·.--::.::.~-.-.--:.-:::::-::-.~~~~~~~~:-:-.-:-.-:~~~~: ..-.::.~6-----

2.1 Definitions ....................................................................................................... 6
2.2 Theoretical backgrounds ................................................................................ 6
2.2.1 Student learning ..................................................................................... 10
2.2.2 Aptitude .................................................................................................. 11
2.2.3 Efforts .................................................................................................... 12
2.2.4 Attitude ................................................................................................... 12
2. 3 Empirical studies .......................................................................................... 13
2.4 Chapter remarks: .......................................................................................... 18

IV


Chapter 3: Research Methodology ...................................................................... 19

3.1 Independent variables and its measurement ................................................. 19
3.2 Descriptive analysis ...................................................................................... 22
3.3 Empirical research model ............................................................................. 22
3. 4 Sampling process .......................................................................................... 23
3.5 Research context ........................................................................................... 24
3.6 Chapter remarks: .......................................................................................... 28
Chapter 4: Research findings .............................................................................. 29

4.1 Sample description ....................................................................................... 29
4.2 Gender .......................................................................................................... 29
4.3 Location ........................................................................................................ 30
4.4 Attitude and efforts toward macroeconomics ............................................... 32
4. 5 Reliability analysis ........................................................................................ 34
4.6 Factor analysis ............................................................................................. 35

-- ----4;'1-Betermlnants-injluence-macroeconomics-scor~ ............................ :-~37 ___ Chapter 5: Conclusions, Policy recommendation and limitations ................... 41

5.1 Conclusions ................................................................................................... 41
5.2 Recommendations ......................................................................................... 43
5. 3 Limitations ofthe research ........................................................................... 44
REFERENCES ...................................................................................................... 45
APPENDICES ....................................................................................................... 50

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ABBREVIATIONS

-

ACT:

American College Testing

-

ATE:

Attitude Toward Economics

-

GPA:

Grade Point Average

-

MOET:

Ministry of Education and Training

-

NUEE:

National University Entrance Examination

-

OLS:

Ordinary Least Squares

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SAT:

Scholastic Aptitude Test

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SEA:

Survey Economic Attitude

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TSLS:

Two-Stage Least Squares

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TUCE:

Test of Understanding of College Economics

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UEH:

University of Economics, Ho Chi Minh City

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UTSS:

Undergraduate Training and Student Services

-

WTO:

World Trade Organization

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LIST OFTABLES
Table 4.1: Gender and Average ofMacroeconomics score
Table 4.2: Testing the Mean Difference between two groups of gender
Table 4.3: Descriptive analysis of location and average macroeconomics score
Table 4.4: ANOVA analysis the difference between groups of location
Table 4.5: Test of Homogeneity of Variances among locations
Table 4.6: Tamhane test for the specific differences between groups oflocation
Table 4.7: Attitude toward macroeconomics before studying
Table 4.8: Attitude toward macroeconomics after studying
Table 4.9: Efforts toward studying macroeconomics
Table 4.10: Reliability statistics about efforts and attitude toward macroeconomics
Table 4.11: Factor analysis for attitude before studying macroeconomics
Table 4.12: Factor analysis for attitude after studying macroeconomics
Table 4.13: Factor analysis for efforts toward studying macroeconomics
Table 4.14: Summary ofthe hypotheses testing

LIST OF FIRGUES
Ftgure 2.1: Circular flow of influence from attitude through intention to
performance as a feedback influence on attitude
Figure 2.2: Conceptual framework

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Chapter 1: Introduction

1.1 Problem statement

The economic development in Vietnam was very impressive during the I990
decade. The growth of the economy comes along with many factors, directly and ·
indirectly. One of them is from education, in my opinion. Although there have
been some controversies about the progression as well as the fall while some
renovations were deployed during last more than I 0 years, nowadays, many
(domestic and oversea) professors pay attention to a vast and complete educational
renovation again, especially when Vietnam has accessed to WTO since 2006.
A system of education stretches from kindergarten to higher education. The rapid
economic development brings about high demand of labor, so does the demand of
managers. Then, a high proportion of high school pupils apply to universities
which are major in economics and business administration. So are in-service
students. The number of students enrolled in universities major in economics and
business administration has been always higher than other disciplines recently.
Vietnamese people usually say that "first business, second medicine". A famous
ancient scholar Le Quy Don said that "No trade no wealth". Another example is
about the higher demand in field of finance and banking after stock market was
established in Vietnam since 200 I, lead to a number of faculties and universities
focus in this field has grown while people are in doubt about their quality.
Therefore, quality assurance of learning and teaching principles of economics is so
quite important.
In the field of economics and business administration, it is much concerned about
economics education at the undergraduate level. In my opinion, principles of
economics are basic courses for any student, not only in universities of economics
and business administration but also some other universities of social science. At
the University of Economics, Ho Chi Minh City (UEH), although they are
compulsory subjects, only a small ratio of students paid high attention and spend

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more time on studying economics while the total load of education has been
decreasing recently, generally about 240 credits required for an undergraduate
student in 2004 reduced to 180 since 2006 (UEH 2006). The average score of
microeconomics and macroeconomics at UEH in the last school year is only about
6.22 - 6.42 over 10, most focus on the range from 5 to 7 (Data from UTSS Office).
In a recent contest "Commentary essays for Vietnamese economy in 2008"
organized by Student and Youth Union at UEH, only a little number of students
could apply economics knowledge into their papers (UEH Youth Union 2008). So
in this research, a wonder about which factors affected the outcome of a student
studying principles of economics at the UEH has been raised. Then we could find
out how to improve their performance as well as students classification for a better
outcome.

What determinants that influence student learning economics? Many economic
education studies have attempted to answer this question. A number of studies
have examined the impact of student characteristics on student performance in

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introductory economics courses (Myatt and Waddel 1990; Anderson, Benjamin
and Fuss 1994; Brasfield, Harrison and McCoy 1993, Betts and Morell 1999).
Other studies evaluated the effectiveness of alternative methods of teaching on
students' study result (Davisson and Bonello 1976; Paden, Dalgaard and Barr
1977; Attiyeh, Bach and Lumsen 1969-1970; Bach and Saunders 1965; Charkins,
O'Toole and Wetzel 1983). Aptitude, attitude and efforts toward studying
economics have also been concerned in many researches. Allison (cited in
Siegfried and Fels, 1979), Becker (1983a) has found low positive correlation
between achievement and student's effort, but Becker and Salemi (1977) didn't

find any impact of study time on performance while Siegfried and Fels (1979)
confirmed that aptitude is the most important determinant, which is positively
related to test performance. In recently, Romer (1993) tested the effect of
attendance on student performance. His fmding is the attendance did contribute
significantly to the academic performance of students in a large intermediate
macro-course. The same to the research result ofDevadoss and Foltz (1996). King

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(1999) and Schmidt (1983) found that the time spending for studying economics
outside the classroom is also important related to student achievement. In the other
hand, Park and Merr (1990) proved that effort and intelligence determine the
academic performance in money and banking courses while demographic variables
did not contribute.

Briefly it is said that, researches about economic education have been started since
1960s in the US with factor determination, from simple socio-characteristics
(gender, race, parents' education, income, hours of work ... ) or time-distribution to
more complicated factors (attitude, efforts, learning and teaching styles .. ) and then
the difference of culture, race, gender on learning style, effects on performance and
expansions applied to other countries as well as using modern teaching methods
like computer-assisted, class game, web-based, etc.

All students at UEH must study microeconomics, and then, macroeconomics in the
general period. The structure of the macroeconomics examination consists of 2
parts, writing and multiple-choice while structure of microeconomics test has
multiple-choice questions alone. In fact, there is difference in what the two types
of exams measure. "Multiple-choice questions may encourage memorization of

information, rather than the understanding of concepts, are more likely to be
misconstrued by students, and leave more to chance in the form of guessing"
(Kreig and Uyar, p.230, 2001). Yates (1978, cited in Becker 1983a) argued that
many educational objectives can not be only measured by multiple-choice tests.
So, in order to have a better assessment, macroeconomics would be the reasonable
decision for this research to find out the answers related to the wonder above at the
UEH.

1.2 Research Objectives
The main objectives are:
-

To fmd out which determinants that influence students' performance in
studying macroeconomics.

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To determine the relationship between determinants and UEH student's
performance in studying macroeconomics.
-

To suggest policy recommendations for lecturers, students and educational
managers at UEH.

1. 3 Research questions

Finding out determinants and theirs relationships to outcome of studying
macroeconomics in order to answer the following questions
Question 1: Does aptitude of an UEH student have an effect on the

performance of studying macroeconomics?
Question 2: Does attitude toward economics have an effect on the
achievement of studying macroeconomics?
Question 3: Does efforts in studying economics have an effect on the
achievement of studying macroeconomics?

1. 4. Research methodology

Firstly, a descriptive analysis focus on the relationships between personal
characteristics such as gender, location to their achievement in economics was
made to obtain a general view about UEH students. Secondly, a qualitative study
was deployed to explore potential factors which may effects on studying
macroeconomics. Finally, an Exploratory Factor Analysis was used to test
reliability and validity along with simultaneous regression and TSLS method to
measure the relationships between outcome of studying macroeconomics and
determinants identified.

The Microsoft Excel and SPSS software are main useful tools to process the data
for the precise factor analysis as well as regression.

1. 5 Delimitation

This research based on information from students at UEH after they study
microeconomics and before macroeconomics. Some information are archived at

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the office of undergraduate training, others are self-evaluations from a paper of
questionnaire.

1. 6 Thesis structure:

This thesis has 5 chapters, starting with an introduction about Problem statement,
Research objectives, Research questions, Research methodology, and its
delimitation. The second chapter presents the literature review on theory and
conceptual framework, empirical studies that serve as the background for
hypothesis development. The third chapter is about the methodology consisting of
research design, concept measurement and data collection. The chapter 4 reports
the result of data analysis before the chapter 5 which summarizes all about the
research results and its recommendations.

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Chapter 2: Literature review

This chapter is presented by 3 parts. The ftrst one is a discussion about concepts
related to the research. Secondly, some theories related to economic education that
would be useful to formulate a conceptual model for our study would be reviewed.
Finally, a glance at some empirical studies which have been researched will help
us to identify the most significant variables that we can use to ftnd out the
relationship

between

these

determinants

and

performance

of studying

macroeconomics at UEH.

2.1 Definitions

First of all, there should be a clear understanding about macroeconomics and then,
performance of a student on macroeconomics.

Macroeconomics

Macroeconomics is a branch of economics. It provides students basic concepts and
analytical methods about performance, structure, and behavior of the economy of a
nation, a region or the global economy. Along with microeconomics,
macroeconomics is one the most important and compulsive subjects at any
university which is major in economics and business administration education.

Performance ofstudying macroeconomics

Performance of studying macroeconomics shows us how students learn and
acquire the knowledge from studying it, how they understand and identify as well
as analyze macroeconomics problems. It is usually measured by an examination
score, in combination with some extra testing activities.

2.2 Theoretical backgrounds

Most of researchers on economic education based on the assumption that the major
objective of economic education is very narrowly defmed concept of learning,
related in the way student performance measured by achievement or course grade

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(Yates 1978 in Siegfried and Fels 1979), as an indicator of how much information
that a student has after the course. Researchers have attempted to model student
learning by incorporating a set of variables measuring the relationships between
student achievement and age, gender, teaching mode, textbook, instructor, class
size, computers, time and effort, prior economic knowledge, aptitude, entry score,
attitude toward economics (Cowie et al. 1997, Siegfried and Fels 1979, Becker
1983a, Manahan 1983, Davisson and Bonello 1976, Simmons and Alexander
1978). These models have typically taken the form of production function where
the output is the performance of learning, which is measured by achievement or
course grades.

According to summary of Bowles ( 1970), an educational production functions
used to seek the affected educational output by altering school inputs in the
common form as followed:
A;= fo + fiXn + JiX2; + ... + /:Xz; + u;

[2.1]

Where

A;: the achievement score (or other output measure for the i'h student);

fo, ... ,fz: the parameters of the production function to be estimated;

}[_j;: the amount of input} devoted to observation i 's education,}= 1... z
ui: the disturbance term.

This model was used frequently for a long time with research in economic
education. One of the common things that could be easily recognized from
production function is the personal characteristics and aptitude usually appears in
every research about this field. Not always, but mostly these variables are
significant. The few studies that have included measures of student's
socioeconomics backgrounds have found such variables as family income and/or
parent's education to be unimportant (Siegfried and Fels, 1979). Another example,
Simmons and Alexander (1978) used a model about Educational Production
Function as
Ait

=

g[F;(tJ' S;(tJ, P;(tJ' l;(t)]

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[2.2]


Among that, F stands for family background characteristics, S for school inputs, P
for peer group characteristics and I for initial endowments (or innate abilities).
Another research example is from Ziegert (2000) using a model to estimate the
effect of personality temperament on learning in economics like this:

Output =/(Student abilities, student demographic, personal temperament) [2. 3J

Gender, age, race, and family background have also been used in learning studies
(Manahan 1983, Navarro and Shoemaker 2000, Bonello, Swartz and Davisson
1984, Anderson, Benjamin and Fuss 1994, Betts and Morell 1999). But "measures

of student maturity, such as age, year in school, and number of previous college
credit hour, usually show no relationship to cognitive performance" (Siegfried and
Fels, p.938, 1979) while Simmons and Alexander (1978) came to a conclusion that
home background or parental socioeconomic status; strongly influences student
performance. Betts and Morell (1999) also come to the same conclusion with
confirmation about the strong affects on GPA at a university by personal
background; include student's family background (income and race), gender as
well as demographic environment.

However, this general test is not likely to conform to the purpose and content of a
particular economics course, which is only concerned with a few topics (Siegfried
and Fels, p.926, 1979). They made a comment that, due to lack of theory of
learning, some problems of the production function above needs to be concerned.

"There has been little concern with such issues as simultaneity (if student interest
is an output, does it not feed back into cognitive understanding?), functional form
(are there interactions among the independent variable) and the statistical
techniques employed". Becker (1983b) also affirmed with this comment.

Becker (1983b) proposed a framework to build general equilibrium model in
which it shows demand of student when studying economics. According to
Becker's model, students have to allocate their time and resources between
economics and other subjects in the same semester as well as opportunity for a

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part-time job or recreation to maximize their utility. Anyway, Becker thought that
it is not easy to formalize a model of full educational process because of the
market imperfections that arise once a student has decided to attend a given
institution. Student doesn't demand economic education by themselves but follow
a bundle of education goods provided by their institution.

Davisson and Bonello (1976) proposed taxonomy for orgamzmg empirical
research. They specify three categories of explanatory variables and the model of
learning is human capital (e.g. Math, ACT score, grade point average), utilization
rate (e.g. attendance, study time), and technology (e.g. lectures, computer usage).

Student Learning= f(human capital, utilization rates, technology)

[2.4]

Follow model [2.4], Davisson and Bonello (1976) argued that when participating
in a specific subject, personal characteristics of each student will interact with the
teaching method from teacher along with time they spending for the subject. The
final target of a student is to maximize utilization which means a best educational
achievement. Durr (1999) proposed the model

Grade =/(Motivation, Ability, Gender, Effort) [2. 5]
- - - -- - - - - - -

. · However, Bowles (f970) discussed that theieast squares-technique yields unbiased
estimates of the regression coefficients only if the independent variables are
exogenous. When some school inputs can perhaps be regarded as exogenous to the
system, there are still some endogenous inputs, for example, student attitudes.
Bowles (p.18, 1970) argued that "student attitudes toward self and toward

learning are a consequence of past and present achievement (as well as other
influences) and are important determinants of achievement". The production
function above could be rewritten as

A= f(X;, ... ,Xs, attitudes)

[2.5]

And

Attitudes= g(Xp ... ,XZJ achievement- past and present) [2.6]

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Based on theory of information, with the same purpose when paying attention to
two-way causation between attitude and performance, Hodgin (1984) also
suggested using TSLS method to test it by a model with the bidirectional causality
between attitude and economics learning. He argued that, during studying
economics course, two things are simultaneously and interactively occurring:
attitudes are being modified due to information concerning economics and relative
performance, and vice-versus, performance is altered by attitude toward
economics. As student collects information about nature of economics, and his or
her ability to comprehend the course, attitude and grade expectation seemed to be
modified. And once new information is received, student will make a prediction
about chance of success or failure in the course. It means grade expectation and
attitude toward economics may be changed

2.2.1 Student learning

Studying and examination are two of important issues of education. To study is to
acquire the knowledge, information about a typical subject then to apply into daily
activities. Examination is a way of checking how much information a student has
effected to collect and comprehend. In economic education researches, some
typical measurements to measure student learning are Test of Economics
Understanding (TEU), Test of Economics Comprehensions (TEC) or the most
widely used instrument is Test of Understanding in College Economics (TUCE). ,
. TUCE is a multiple-choice test developed in 1968, which tests both micro and
macroeconomics. It is said that, TUCE is an effective discrimination of students
with high and low levels of ability and a good measure of prior ability and
analytical skills (Buckles and Welsh 1972 in Siegfried and Fels 1979). TUCE
could be used to measure the absolute achievement, absolute improvement, and
percentage improvement in studying economics with pre- and post-score ofTUCE.

Recent studies have relied on using student course grades (Navarro and Shoemaker
1999, Navarro and Shoemaker 2000). Course grades or tests can be used as
indicators of how much information that a student has after the course, but it

10


cannot be used if the structure of the tests are as different as chalk and cheese
between classes, lecturers with various teaching styles ... In order to have unbiased
evaluation about economics performance, all observations must have similar
characteristics, studying in almost the same class size or have the same
homogenous class organization, studying with a common teaching style which has
been totally agreed among lecturers or approved by scientific and training council
and they have to answer the same questions at the final examination. Course grade
is not only a final score of examination but the score of progression student

achieved during studying principles of economics by doing mid-term test,
assignments or homework.
Final examination usually consists of constructed response or multiple-choice
questions. Each type of exam measure has its advantages along with disadvantages
and students would have their own learning and consolidation style in order to
respond to it. Multiple-choice pay much attention to memorization of information
rather than the understanding of concepts (Kreig and Uyar, 200 I) and it can not
measure some educational objectives (Yates 1978, cited in Becker 1983a). A
combination of constructed response and multiple-choice questions could almost
meet the requirement of economics education.

2.2.2 Aptitude

Human capital or student abilities variables are a measure of a student's aptitude
for learning. Another way to approach this is using previous GPA or SAT. Most
studies used SAT/ACT scores and GPA to measure student's ability and fmd a
positive and significant relationship between such variables and student learning.
An earlier work shows strongly significant positive links between high school
GPA and test score and success of undergraduates (Morell, 1999). Prince, Kipps,
Wilhem and Wetzel (1981) found that pre-score of TUCE is an appropriate
measure of economic knowledge or as a proxy for student aptitude. Siegfried and
Fels (1979) reviewed in some studies and find that mathematics scores could be an
instrument to present aptitude and to seems to be positive and significantly

11


associated with economics test performance. A hypothesis could be withdrawn for
the study, as
H 1: Aptitude has a positive impact on performance of studying macroeconomics

2.2.3 Efforts
The utilization rate or effort is time spent on studying in a course. It can be
measured by the percentage of class attendance (Devadoss and Foltz, 1996), hours
per week working on the course outside the classroom (King, 1999) ... Developing
a model of inventory study time, Becker (1983b) concluded that increasing time
spent studying economics resulted in positive outcomes in student learning. This
finding is supported by many studies such as King (1999) and Schmidt (1983).
However, not all students who attend class regularly pay high attention to lectures.
That's why some researches didn't fmd any impact of study time on performance
(Siegfried and Fels 1979). Ow (2005) suggested using a survey questionnaire to
investigate student's effort and attitude towards their studies to determine the
importance of taking notes or review the lesson after class, discussion, reading,
preparation for the exam, etc. So is it reasonable to propose a hypothesis about
efforts on studying macroeconomics for the study like this
H2 : Efforts has an impact on performance of studying macroeconomics

2.2.4 Attitude
When attending a class of economics, students usually face 2 possible options:
either collect as much information as they can to master the nature of economics
(via lectures and readings) or just only enough to comprehend the subject (via
passing examination scores). Then attitudes and grade expectations are likely to be
modified (Hodgin 1984). Of course any student always wants to achieve the best
score as they can, but the different attitude toward the subject would change the
way they study.

Walstad and Soper (1981) had reviewed some previous researches and found that
former methods of economic attitude measurement were poorly developed and

12

report limited information on instrument reliability or validity, or too complex to
measure. Based on instrument previously developed by Hodgin and Manahan
(1979, cited in Walstad and Soper 1981), the National Committee on Economic
Attitude Measurement conducted a new attitude measure named Survey on
Economics Attitude (SEA). SEA, which has been considered by provide a
measurement tool about Attitude Toward Economics (ATE) with good validity,
reliability and known characteristics. A more positive ATE maybe an intended
outcome for a course in economics. Base on that, there is a suggestion about the
following hypothesis for the study:
H3 : Attitude toward economics has an impact on performance of studying
macroeconomics
In the other angle about variables of research models, many researchers whose
goals are to compare one teaching method with others use a dummy variable to
represent technology (Davisson and Bonello 1976; Paden, Dalgaard and Barr
1977). "However, it appears that different teaching methods have little impact on
student learning" (Siegfried and Fels, p.927, 1979). One reasonable explanation

for this result is that the instructor's teaching style affects different students
differently (Wetzel, Potter and O'Toole, 1982). Using the Grash - Reichmann
Learning Styles Questionnaire, Charkins, O'Toole and Wetzel (1985) conducted
researches at Purdue University to test the effect of the link between teacher and
student learning styles on student achievement. The difference between teaching
and learning style scores from the dependent questions was used to obtain a
numerical score that reflected the divergence between a student's learning style
and the teacher's teaching style. Their findings only suggest that the larger the
divergence between teaching styles and learning styles, the lower the student's
gain in achievement in economics.

2.3 Empirical studies

To estimate the production function, many researches have used an OLS model.
Moreover, qualitative response analysis in place of quantitative analysis has been

13


suggested (Becker 1983c). Spector and Mazzeo (1980) used a probit model in
analyzing the probability of getting a grade in intermediate macroeconomics.
Leppel (1984) used a Tobit model in comparing the academic performance of
returning and continuing students. Park and Kerr (1990) used multinomial logit
analysis to identify those variables that determine a student's grade in
undergraduate money and banking course while Hodgin (1984), Manahan (1983),
used simultaneous models with two-stage least square (TSLS) method.

Some economic education researches were developed based on theory of school
learning by Bloom was published in "Human Characteristics and School

Learning". Bloom's target is attempts to explain, to predict and to modify
individual differences in school learning (Rennie, 1979). His model has three main
parts: "(I) characteristics that the student brings to the learning situation, namely,

cognitive entry behaviors and affective entry characteristics; (2) quality of
instruction (i.e., cues provided to the learner, participation of the learner,
reinforcement of the learner, and feedback and correction) in relation to a
particular learning task; and (3) learning outcomes, including level and type of
achievement, rate of learning, and affective outcomes"

Manahan (1983) based on Bloom's theory of learning with the modification and

contributions of Allison (1977) and Hanushek (1979) to suggest another type of
production function, in which outcome of the studying process is described by 2
aspects: achievement and attitude toward course.

Achievement= /(ability, attitude, effort, quality of instructor) [2. 7]
And

Attitude

=

g(achievement, ability, effort, socio, quality of instructor) [2.8]

Bloom in his book Human Characteristics and School Learning (Manahan 1983)
argued that under favorable learning conditions, student has the knowledge that is
prerequisite and positive affect toward the learning task and when the instruction is
appropriate, it offers feedback and correction to the learner. Ramsett, Johnson, and

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Adams (1973) (in Siegfried and Fels, 1979) found that those students who were
more favorably disposed toward the subject of economics did better on the postcourse TUCE, holding pre-TUCE and socio-demographic factors constant. As
Manahan's expectation (Manahan 1983), two factors have casual influence. The
result when using TSLS method showed that attitude and achievement don't have
any mutual effect, and attitude was established before starting study, with a little
bit change during class, and suggested that all estimations must consider
socioeconomic variables or student background characteristics. Moreover, he also
mentioned that using a comparison of the OLS and TSLS estimates had showed
that some coefficients in the attitude equation change depending upon the

estimating technique.

In another viewpoint based on theory of information, in the same purpose when
paying attention to two-way causation between attitude and performance, Hodgin
(1984) also suggested to use TSLS method to test it. In a paper about information
theory and attitude formation in economic education, he built a model with the
bidirectional causality between attitude and economics learning using the
economics of information theory. He argued that, during studying economtcs
course, two things are simultaneously and interactively occurring: attitudes are
being modified due to information concerning economics and relative
performance, and vice-versus, performance is altered by attitude toward
economics. Specifically, let ATE be the attitude toward economics, a function of
the expected utility from the course would be
ATE= /(Performance, Prior Attitude, Age, Sex) [2.9]

Then
Performance= /(Attitude, Ability, Prior Knowledge, Effort)

[2.10]

Student's attitude towards the course is another factor which needs to be concerned
as an important measurement. With the high attitude toward its subjects, students
will tend to spend more time on reading, discussion as well as finding extra

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materials prepare for class. It could be considered as another factor instead of
utilization previously.

Attitudes
Toward Economics

Performance on
Economics & Examinations

Intention to
Comprehend Economics

Figure 2.1: Circular flow of influence from attitude through intention to performance
as a feedback influence on attitude
Source: Hodgin, Robert F. (1984). Information Theory and Attitude Formation in Economic
Education. The Journal ofEconomic Education, 15(3), 191 - 196

The diagram above described the relation ships of influence from attitude through
intention to performance and then a feedback to attitude (Hodgin 1984). As student
collects information ·about nature of economics, and his or her ability to
comprehend the course, attitude and grade expectation seemed to be modified.
And once new information is received, student will make a prediction about
chance of success or failure in the course. It means grade expectation and attitude
toward economics may be changed.

Hodgin collected the data from 500 students which had been studying at the
Illinois State University in 1978, which was then reduced to 190 due to lack of
information from a number of given students. In the attitude expression, the
performance coefficient was found to be significant, but the attitude coefficient in
the performance expression was not while remaining exogenous variables were
significant at the 0.05 level or higher (except age, at 0.10) although they are
selected to reflect only those argumentatively necessary to keep the model
specification simple and efficient. These results support that informational signal

about performance in economics affect attitude (Hodgin, 1984).

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