A Learning
Achievement in the Quantitative analysis in business
Using Computer Package for Teaching
and Learning
Poranee Laotong
Rajamangala University of Technology Isan, Surin
Campus
Abstract
The
objectives of this research are to compare the student’s learning achievement
in business quantitative analysis subject, linear programming unit using
computer package for teaching and learning. Additionally, to compare the
attitude toward business quantitative analysis subject before and after applied
computer package for teaching and learning.
There are six research processes including
first, choose the instruction unit. Second, design the teaching plan. Third,
create and develop research tools. Forth, test the tools’ quality. Fifth,
conduct the study and sixth, analyze the data and report the result.
The tools of the research including 1) teaching plan using
computer package for teaching and learning and normal teaching plan. 2) The 40
items multiple choices test for evaluate the leaning achievement in business
quantitative analysis subject, linear programming unit. The test difficulty
index (p) are between 0.2 -0.8, the discrimination power (r) are between 0.20
-0.8, and the reliability is 0.94. 3) the attitude evaluation form to analyze
the attitude toward the business quantitative analysis subject in four aspects
including content, teacher, learning achievement, and teaching and learning
supporting factors totally 30 items. The accuracy of the attitude evaluation
form is 0.73. The result of the study shows are describe as follow.
1) The
learning achievement in business quantitative analysis, linear programming
unit, of bachelor student who applied the computer package for teaching and
learning is higher than the students using normal plan. The significance
statistic is .05. 2) The attitude of the student who applied the computer
package for teaching and learning is higher than the students using normal
plan. The significance statistic is .05.
Keywords:
Learning Achievement, quantitative analysis in business, computer package for
teaching and learning
Introduction
Instruction
is the process of providing knowledge and experience for learners to change
their behavior to the expected goal. Therefore, the instructional package is used
for increasing the learning effectiveness. The individual difference, readiness
and environment were considered. There are different instructional packages
used for instructional process and one of these is the computer package for
teaching and learning. The instructors put in the content into the instruction
package so that the learners can acquire the knowledge by self-learning and
adapt the knowledge in their daily life. Due to the development of the computer
system, the instructors are able to create various instructional packages to
meet the need of the learners and learning environment. The interesting and
motivating presentation via computer multimedia learning package made the
lessons easy and understandable. The computer learning package is an effective
innovation which help learner to understand the content and able to apply Information
technology for their learning.
In undergraduate class, the number of
the student are mostly too many in same class and it is found that they have
different experience, knowledge acquiring ability and the effectiveness of the
learner especially with the abstract
lesson, therefore, the instructor need to use effective teaching tools to help
study achieve the learning goal effectively.
The quantitative analysis in business
subject is the professional subject and it is also the vocational choice
subject for undergraduate study which contains 3 unit (3-0-6). The objectives
of the course are to make students understand the techniques of mathematical
models for decision making and theoretical understanding of the various businesses.
The students need to understand problems, principle and restriction for
decision making in business. Furthermore, the students need to understand how
to calculate and use different model to solve problems in business decision
making. The students must be able to analysis and evaluation the projects in
order to make effective decision for the business. The ability of adapting information
technology such as software operating systems is required.
Some part of
the course description focuses on the analysis and evaluation of various
technologies used in the business to promote the learning of the students to
meet the objective of Quantitative analysis in business subject. In linear
programming unit, the students needed to calculate the parameters determined by
the calculation with graphical method which is simple and easy to understand.
However, the limitation of the linear programming including 2 variables mean while
the Simplex method can be used more diverse and able to solve more complex linear
with more variables and restriction. Because of the difficulty accordingly, the
students tend to have low learning achievement and motivation which consistent
with the results of the research of Atipong Petsut (2007) who have studied the
satisfaction of the undergraduate students, faculty of Business Administration,
Prathum Thani University toward quantitative analysis in business subject. The
result of the study showed that the students have medium satisfaction toward benefits
of the subject to a career, meets the needs of the students, appropriate teaching
materials, and the assistance both in and outside the classroom. The result of the study also pointed out that the
students have low satisfaction toward the teacher assessment method. The
researchers noted that the instructors should applied information technology in
the teaching process for more convenient and fast calculation such as Excel,
QM, QSB, MS, etc. Furthermore, the LINDO is an effective choice.
Due to the
rational and concept accordingly, the researcher is interested in the learning
achievement of quantitative analysis in business subject. The use of the
computer package for teaching and learning is compared with the original
instruction: a case study of learning
achievement in the quantitative analysis in business subject using computer
package for teaching and learning of undergraduate students, faculty of
Technology Management, Rajamangala University of Technology Isan, Surin Campus.
Objectives of
the Study
1.
To
compare the academic achievement of quantitative analysis in business subject,
linear program content using computer package for teaching and learning with
the original instruction.
2.
To
compare the attitudes of the students toward quantitative analysis in business subject
before and after using the computer package for teaching and learning.
Research
Methodology
1.
Research Method
In this
study, the researcher has divided the researching method into the following
steps.
1.1
Selection of the content unit.
1)
Analysis of the curricular of Bachelor of Business Administration, Rajamangala
University of Technology Isan.
2)
The quantitative analysis in business subject, linear program unit, for
undergraduate students was selected from the textbooks and other related books.
3)
Regulate the instruction unit. At this stage of the study, the researcher
analyzed the curriculum, the documents and texts which are related to the
quantitative analysis. Then, the researcher analyzed and conducted the content
analysis for linear programming unit.
4)
The researcher defined the purpose of the study which consistent with course
objective.
1.2 Design the instruction using computer
package for teaching and the original instruction methods. The researcher
prepared the teaching materials and documents for teachers and students.
1.3 Create and develop the research tools.
1)
The two teaching plans, the computer package for teaching and the original
instruction.
2)
The test to evaluate the achievement in Quantitative analysis in business subject.
3)
The attitude toward the Quantitative analysis in business subject evaluation.
1.4
Monitoring the tools’ quality.
1.5
Experiment the tools.
2. The
Sample of the Study
The samples of the study were 50 undergraduates, faculty of
Technology Management, Rajamangala University of Technology Isan, Surin campus,
who enrolled for Quantitative analysis in business subject in the semester 3/2010.
The samples were randomly selected and were divided into two groups, control
group and experimental group, 25 students each.
3. Tools of
the Study
There
are 3 issues of the study’s tools.
3.1
The teaching plans, the computer package for teaching and the original
instruction lesson plans for 4 weeks. The lessons take 3 hours per week,
totally 12 hours. . In the 3/2010 semester, experiment was conducted in 2 week,
3 hours each, totally 6 hours.
3.2 The test to evaluate the achievement in
quantitative analysis in business subject, liner programming unit which consist
of:
1)
The 20 items of 4 choices multiple-choice test which take 60 minutes.
2)
The scoring is 1 point for the correct item and 0 for the incorrect item.
3)
To determine the quality of the achievement test. The research was conducted to
determine the quality of the tools as follows.
3.1)
The result of the achievement tests was monitoring by 3 expertise from
Management of Technology faculty, Rajamangala University of Technology Isan,
Surin campus to examine the consistency between the test and the purpose. Then,
the result was determined by the IOC index, if the index corresponds to a value
at least 0.5 indicates that the test is consistent with the purpose. The result
of the study pointed out that the IOC of the Multiple-choice test are between
0.67 to 1.
3.2)
The tests was conducted with 25 students who never learn about linear
programming. The results of the study were calculated to fine the difficulty
(p) and the discrimination (r) by 50% techniques. Then, the item which have the
difficulty (p) of the test between 0.40 to 0.80 and the discrimination (r)
ranging from 0.2 up were choose. The
results pointed out that 20 items of multiple-choices question, the difficulty
(p) are between 0.2 to. 0.8 and the discrimination (r) ranging from 0.20 to
0.8.
3.3)
The selected test was conducted with 25 students who had studied the linear
number. In order to fine the reliability, the researcher used Kuder - Richarson
20 or KR - 20 to analyze and found that the reliability is 0.94.
3.3 The attitude towards the quantitative
analysis in business subject test
This research
has developed the test evaluate the attitude towards quantitative analysis in
business subject from the test of Atipong Petsut (2007) to cover all elements
of attitude which consists of fourth elements: content, instructor, learning
achievement and learning assistant. The expertise gave the suggestion and
opinion and finally 30 items remains.
1)
The attitude towards the Quantitative
analysis in business subject test
There are 30
items of the attitude towards the quantitative analysis in business subject
test. The students need to take 30 minutes to complete the test. The test
covers the behavioral response, the awareness of the importance of the Quantitative
analysis in business subject and the participation in this class according to rating
scale. The score level as follows. The highest level attitude = 5, The high level
attitude = 4, The medium level attitude = 3, The less level attitude = 2, The
lowest level attitude = 1
2) To create the attitude towards the quantitative analysis in business
subject test , the researcher constructed as follows.
2.1) The
researcher studied the documents which related to the quantitative analysis in
business instruction, including Business Administration course (Revised 2010),
the document which related to the problems of quantitative analysis in business subject and
the attitude evaluation test design and creation book (Patara Nickmanon. 1994).
2.2) The researcher develop the items to
evaluated the attitude towards
the quantitative analysis in business
subject test by Likert's Scale
(Luan Saiyot et al. 2000) using a five-level scale.
2.3) Then, the researcher creates the
attitude towards the Quantitative analysis in business subject test.
3) Monitoring the quality of create
the attitude towards the Quantitative analysis in business subject test
The researcher determined the quality
of the attitude towards the Quantitative analysis in business subject test as
follows.
3.1) The 3 expertise examine the
appropriateness of the attitude towards the quantitative analysis in business subject
test to find the average (
) and standard deviation (S.D.) to fine if the average
value from 3.51 or above and a standard deviation less than 1.00, it is
regarded as appropriate (Nuansi Chamnangit. 2001, Kanjana Watayu. 2001). The
results pointed out that the average value is 4.52 and the standard deviation
is .52. The expertise agree that the attitude has construct validity.
) and standard deviation (S.D.) to fine if the average
value from 3.51 or above and a standard deviation less than 1.00, it is
regarded as appropriate (Nuansi Chamnangit. 2001, Kanjana Watayu. 2001). The
results pointed out that the average value is 4.52 and the standard deviation
is .52. The expertise agree that the attitude has construct validity.
3.2) The researcher fine the
reliability of the attitude towards the quantitative analysis in business
subject test according to Cronbach’s µ-coefficient
by using a statistical software package for social science research. The
reliability of the whole attitude test was 0.73.
4) A collection of data.
To collect the data, the research
was carried out as follows.
4.1) Divided students into two
groups, an experimental group and a control group, 25 people each.
4.2) Both groups of students did
the attitude towards the Quantitative analysis in business subject test before
the experiment conducted.
4.3) The experiment was carried
out, both group conducted the self-learning for six hours in the 3 semester of
2010, but following a different approach.
1) The experimental group was
taught using a LINDO.
2) The control group was
taught by the original instruction.
4.4) After the experiment, the
researcher had the students did the learning achievement test and the attitude
towards the quantitative analysis in business subject test and then record the
scores as the post test for the data analysis
4.5) The achievement test scores
of and the attitude scales towards the Quantitative analysis in business subject
to analyzed using statistical process for the hypothesis testing and research
conclusion.
5) Data
Analysis.
The researcher analyzed the data
as follows.
5.1) Compare the Learning
Achievement in Quantitative analysis in business subject after the experiment
between the experimental group and the control group. The samples are
independently test (t-test for independent samples) using the statistical
software package for social science research.
5.2) Compare of attitudes towards
the Quantitative analysis in business subject by analysis of covariance using
the statistical software package for social science research to find the
attitude towards the Quantitative analysis in business subject
6) Statistics
used for data analysis.
The data analysis was conducted as
follows.
6.1) Basic statistics including
the Mean and the standard deviation of the evaluation were conducted.
6.2) The statistic for tools’
quality monitoring.
1) Find the IOC index between
the test and the purpose of learning (Kasem Sarai. 1997)
2) Find the difficulty and
the discrimination of the learning achievement tests
3) Find the discrimination of
the attitudes towards the Quantitative analysis in business subject using T-distribution.
4) Find the validity of the learning
achievement using the formula KR-20 of Kuder Richardson.
5) Find the reliability of
the attitudes towards the Quantitative analysis in business subject test using µ-coefficient of Cronbach (Luan Saiyot and Ankana Saiyot. 1995)
6.3) Statistic for the hypothesis
testing.
1) Compare the learning
achievement of quantitative analysis in business subject, linear programming unit,
after the experiment by t-test in independent groups using the statistical
software package for social science research.
2) Compare the attitude
towards the Quantitative analysis in business subject after the experiment
using analysis of covariance (F-test) using the statistical software package
for social science research.
Result of the
Study
Part 1. The Quantitative
analysis in business subject learning achievement of undergraduate students
comparing between the group which used computer package teaching program and
the group which taught by the original instruction. As shown in Table 1.
Table 1 The
comparison of the Quantitative analysis in business subject, linear programming,
learning achievement after the experiment
between the experimental group and
the control group.
|
Sample
|
N
|
|
S.D.
|
t
|
p
|
|
Experimental Group
Control Group
|
25
25
|
14.28
11.68
|
2.66
1.79
|
5.235
|
.000*
|
*
p
< .05
Table 1 shows
that the learning achievement of the experimental group is= 14.28 which
is higher than the control group which is = 11.68. The significant difference between two groups
is at the .05 which shows that the learning achievement of students who learnt
by computer package for teaching and learning is higher than the students who
learn by original instruction which taught by regular teachers.
= 14.28 which
is higher than the control group which is = 11.68. The significant difference between two groups
is at the .05 which shows that the learning achievement of students who learnt
by computer package for teaching and learning is higher than the students who
learn by original instruction which taught by regular teachers.
Part 2. The
comparison of the attitude towards the Quantitative analysis in business subject
of undergraduate students between the group which used computer package
teaching program and the group which taught by the original could be summarized
in Table 2.
Table 2 Results
of the covariance analysis of the attitude toward the Quantitative analysis
in business subject after the
experiment between the experimental group and the
control group. The scores of the
attitude before the experiment of the
experimental group and the control
group were use as the covariate.
|
Sources of variability
|
SS
|
df
|
MS
|
F
|
p
|
|
The attitude scores toward
quantitative analysis business Between groups
Within group
|
860.647
54.673
72.993
|
1
1
23
|
860.647
54.673
3.174
|
271.187
17.227
|
.000*
.000*
|
|
Total
|
933.640
|
25
|
|
|
|
*
p
< .05
Table 2 shows
that Attitude scores of the quantitative analysis in business subjects
before the experiment and after the experiment is significance at .05.
Therefore, to use the attitude score of the experimental and the control group
to use as the covariate lead to the more accurate attitude score after the
experiment. To consider the different attitude score between groups found that
the different teaching method leads to different attitude score, statistically
significant at the .05 level as shown in Table 3.
Table
3
Average value based on the attitudes
toward the quantitative analysis in business
subjects
of the experimental group and the control group.
|
Group
|
Scores before the Experimental
|
Scores after the Experimental
|
Average Score
|
||
|
|
S.D.
|
|
S.D.
|
||
|
Experimental Group
Control Group
|
131.76
121.32
|
7.25
12.19
|
133.00
123.24
|
5.52
11.33
|
132.38
122.28
|
Table 3 shows that the average
attitude score toward the quantitative analysis in business subjects before the
experiment is =131.76 which is higher than the control group, =121.32. Therefore, to compare the attitude score
toward the quantitative analysis in business subjects after the experiment of
the experimental group and the control group, the attitude scores before the
experiment of both groups were used as the covariate to average the post test
score. The resulted showed that the attitude score after the experiment of the
experimental group, =133.00, is higher than the control group, =123.24. It is implied that the students who use the
computer package for teaching and learning have higher attitude toward the quantitative
analysis in business subject.
=131.76 which is higher than the control group, =121.32. Therefore, to compare the attitude score
toward the quantitative analysis in business subjects after the experiment of
the experimental group and the control group, the attitude scores before the
experiment of both groups were used as the covariate to average the post test
score. The resulted showed that the attitude score after the experiment of the
experimental group, =133.00, is higher than the control group, =123.24. It is implied that the students who use the
computer package for teaching and learning have higher attitude toward the quantitative
analysis in business subject.
Conclusion
and discussion of the findings
Conclusion
1.
The students who learn from the quantitative analysis in business subject
using computer package for teaching and learning had higher learning
achievement, statistically significant level at .05.
2.
The students who learn from the Quantitative analysis in business subject using
computer package for teaching and learning have higher attitude scores, statistically
significant level at .05.
Discussion
The findings
on the learning achievement of quantitative analysis in business subject, linear
programming unit shows that could be discuss as follows.
1. The
students who learned from the quantitative analysis in business subject
using computer package for teaching and learning had higher learning
achievement, statistically significant level at .05 which consistent with the
hypothesis. It is possible that the computer package program encourages
students to learn in group and offer more chances to discuss, exchange idea and
do group work. In addition, the students have chances to use the computer
package and increase their critical thinking, aim to get higher scores because
they can compare their own scores and most of all they can use these knowledge
in their daily life which consistent with Aadtanad (2009) who found that the
post-test score of learning achievement and the attitude scores of the student
who learn Microsoft Power Point via the internet media got higher scores than
the original instruction, statistically significant level at .05.
2. The
students who learn from the Quantitative analysis in business subject using
computer package for teaching and learning got higher attitude scores, statistically
significant level at .05 which consistent with the hypothesis. It is possible
that the computer package for teaching and learning offer more chances for
student to do the collaborative learning and support one another. The students
who understand the lesson better can help other students and lead to group
success. The students would feel proud, motivated and active with the lesson
and lead to better attitude toward the Quantitative analysis in business subject.
The result of the study consistent with the study of Pichet Jamoratanyawat
(2003) who found that the student who used learning package got higher learning
achievement than the student who taught by original instruction, statistically
significant at .05.
Suggestion
The researcher
suggests for further research as follows.
1. General suggestion
1.1 The
teachers who plan to teach linear programming unit by LINDO package, for the
maximum achievement teachers need to learn in advance about the specific
vocabulary, instruction, teaching and learning activities using computer
technology in order to provide instructional materials and facilities etc.
1.2 The
researcher has conducted the study to create the activities of teaching and
learning process in order to complete the research work. For those who would
like to adapt teaching and learning activities to teach the students should
consider the appropriateness of the content, time, course objective and interactive
teaching and learning environment in their institutions.
1.3 Some learning
and teaching activities need to take time to understand before using the
program. In order to understand in a linear programming better, the researcher
s can add instruction into LINDO software.
1.4 Teachers should
motivate students to exchange their ideas and do group discussion to increase
students understanding of the content.
1.5 The teachers
should record the problems found during the teaching and learning activities
for improving the teaching in the further.
2.
Suggestions for further research
2.1 The
programs which is related to the linear programming such as study of Microsoft
Excel, QM, QSB, MS program should be studied.
2.2 The
researchers should conduct the classroom research to find the result of the study
while using the program.
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