Determinants of student's learning case study in macroeconomics at the university of econommics-Ho Chi Minh city Luận văn thạc sĩ

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
TRliONG
HQC
KINH
TE
TP.HCM
THU'VIEN
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
1
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.
11
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.
111
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
-

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

___
-
Chapter 5: Conclusions, Policy recommendation and limitations
41
5.1 Conclusions
41
5.2 Recommendations 43
5.
3 Limitations
of
the research 44
REFERENCES 45
APPENDICES 50
v
- ACT:
- ATE:
- GPA:
-
MOET:
- NUEE:
- OLS:
- SAT:
- SEA:
- TSLS:
- TUCE:
- UEH:
- UTSS:
-
WTO:
ABBREVIATIONS

American College Testing
Attitude Toward Economics
Grade Point Average
Ministry
of
Education and Training
National University Entrance Examination
Ordinary Least Squares
Scholastic Aptitude Test
Survey Economic Attitude
Two-Stage Least Squares
Test
of
Understanding
of
College Economics
University
of
Economics, Ho Chi Minh City
Undergraduate Training and Student Services
World Trade
Organization
vi
LIST
OFT
ABLES
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:
ANOV
A 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
vii
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
I
\
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
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
2
(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.
3
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
4
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.
5
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
of
studying 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
6
(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)]
[2.2]
7
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.
3 J
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
GP
A 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
8
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]
9
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
GP
A 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
H
2
:
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:
H
3
:
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
14
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 post-
course
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
15
materials prepare for class. It could be considered
as
another factor instead
of
utilization previously.
Performance on
Economics
& Examinations

Attitudes
Toward Economics
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
of
Economic 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).
16