1.0 Introduction
The history of simulation has
started quite a long time ago. Yet, the philosophers at time have been arguing
about the effectiveness of simulation against conventional theory in
educational psychology. According to Perner & Howes (1992), simulation is
an old idea in developmental psychology circles which has great importance in
Piaget’s psychology. In particular, simulation is known as “role taking” or
“perspective taking” in Piaget’s theory which may able to helps young children to
overcome their egocentric views. The philosophers have been arguing that,
simulation can be used as a great device or method to suggest predictive and
explanatory hypotheses, but it cannot be used to justify these hypotheses.
Fortunately, simulation theory today has a strong influence on the philosophy
of mind debate. Simulation theory suggests that we do not understand others
through the use of folk psychological theory. Rather we use our own mental
apparatus to form predictions and explanations.
1.1 What is Simulation?
The
term simulation is used in different ways by different people. Modeling and
simulation are interrelated and both are discipline and method used for
developing a level of understanding of the interaction of the parts of system,
and of the system as a whole which exists and operates in time and spaces. This
method is very suitable to be used in teaching and learning because the level
of understanding which is developed when applying this method is achievable to
be compared from other method. A system is understood to be an entity which
maintains its existence through the interaction of its parts. A model is a
simplified representation of the actual system that is used to promote
understanding among students. The effectiveness of a model is depend on the
extent which it promotes understanding. A good model is always a trade-off as
to what level of detail is included in it since all models are simplifications
of reality. If either too little or too much details is included in the model
will give affections to the level of understanding.
A simulation generally refers to a
computerized version of the model which is run over time and used to study the
implications of a defined interaction. One develops a model, simulates it,
learns from the simulation, revises the model, and continues the iterations
until an adequate level of understanding is developed. Modeling and simulation
follows much the same reality. One can learn about riding a bicycle from
reading a book, but in order to really learn to ride a bicycle, one must become
actively engaged with a bicycle.
There are many types of simulation
that have been created and developed by people. Mostly used by people in many
areas or field works is the computer simulation. Computer simulation is the
discipline of designing a model of an actual or theoretical physical system,
executing the model the model on a digital computer, and analyzing the
execution output. This type of simulation is very suitable to be used in
teaching and learning process in schools. Simulation embodies the principle of
‘learning by doing’ because in order to learn about the system, one must first
build a model of some sort and then operate the models. Computer simulation is
the electronic equivalent of this type of role playing and it serves to drive
synthetic environments and virtual worlds. Within the overall task of
simulation, there are three primary sub-fields which are model design, model
execution and model analysis. Fortunately, today there are various model
samples that have been designed, so students just have to choose any model
sample and simulate it.
According to Winn & Snyder
(1996), the purpose of an educational simulation is to motivate the learner to
engage in problem solving, hypothesis testing, experiential learning, schema
construction, and development of mental models. An educational simulation is
based on an internal model of a real-world system or phemomenon in which some
elements have been simplified in order to facilitate learning. The models on
which educational simulations are built tend to be of three general types which
are continuous, discrete, and logical. Generally, educational simulations are
grouped into four categories. Physical simulations allow the learner to
manipulate variables in an open-ended scenario and observe the results.
Iterative simulations tend to focus on discovery learning by the student with
opportunities to conduct scientific research. In a procedural simulations, the
students manipulates simulated objects with the goal of mastering the skills required
to correctly and accurately manipulate physical objects in a real-world
settings. While situational simulations generally model human behavior focusing
on attitude of individuals or groups in specific settings.
Simulations can be used to provide a
fertile learning environment for students. The use of simulated activities in
education is widely becoming recognized as an important tool in schools.
Simulations promote concept of attainment through experiential practice. They
are effective at helping students understand the indication of a concept or
circumstance. Students are often more deeply involved in simulations than other
activities. In science class, the process itself educates the students and can
be more appreciated through simulations. Simulation can reinforce other skills
indirectly including debating and research skills.
Learning by simulation can increase
student motivation. One way to make concepts meaningful for student is to
introduce the topics using simulations. Simulations can help students see
things from a different perspective or allow them to feel connected to the topic.
Learning by stimulating the models, offer students the opportunity to
manipulate content knowledge in an active context that engages a variety of
learning styles and offers the opportunity to experience the subject matter in
a dynamic way. Simulations motivate students to get involved and do well
because the simulation fell like a “real” world situation and because they are
interacting directly with their peers. These experiences give students a taste
of how professionals confront and resolve problems. Students will get more
knowledge and understanding if they experience more. Thus, they will be more
motivated and eager to learn and investigate more models or situations.
Students often use simulations to
make predictions about the social, economic, or natural world. Regardless of
whether the simulation is based on concrete materials, or a computer program,
simulation can be used to make the students predict and enhance their learning.
Teacher can give the students a problem to discuss, ask them to make a
prediction about the answer, then, simulate data to test their prediction. The
students also can be asked to predict what will happen under certain
conditions, then, they will test it out. Example condition is what will happen
to the shape of the sampling distribution if the sample size is increased.
Indirectly, learning with simulations can developed the prediction skills of
students.
Simulation can be valuable aids in
student learning because it offers several benefits. Simulations are often
cheaper to create than the real life counterparts. Installing a flight
simulation software is cheaper than buying a practice jet for each school. Furthermore,
they are easier to construct. Simulations also remove the element of danger
from the situation. For example, if students want to conduct the prey and
predator issues, they can interact with the predator in a simulation quite
safely than going to their habitat. In addition, simulations can be paused,
whereas real life cannot. Pausing allows more time for students to assess the
situation occurs. Simulations are enjoyable and motivating learning aids.
Simulations also enhance appreciation of the more subtle aspects of a concept
or principles and promote critical thinking among students. The bad side of
simulation is just from the aspects of preparation time and assessment is more
complex than some traditional teaching methods.
1.2 Simulation in Malaysia’s
Education
Malaysia intends to transform its
educational system, in line with and in support of the nation’s drive to
fulfill Vision 2020. The Smart Schools initiative is one the programme in order
to achieve the government aims to capitalize on the presence of leading-edge
technologies. Smart schools need teaching-learning materials designed for the
new teaching strategies. Thus, in order to fulfill the need, the modeling and
simulation software is used in teaching and learning process in Malaysia’s
Smart School. These materials will accommodate students differing needs and
abilities, resulting in fuller realization of their capabilities and potential,
and allow students to take greater responsibility for managing and directing
their own learning. The use of these technology materials is in order to
prepare the students for the Information Age as well as produce a
technologically literate work force, enhance learning and democratize
education.
1.3
STELLA software
2.0 Discussion
Teacher
guide the students to learn the topic of natural selective pressure using
STELLA software. Teacher will explain thoroughly to the students the core model
structure of the natural selection to engage their knowledge about the topic.
So that, students will understand what are they going to test. The following
model structure will be used by teacher.
From the core model and the
explanation from teacher, students will understand that the simple natural
selection that they are going to examine and test involve the rabbits and foxes
population. The attribute of the rabbit population that will undergo selective
pressure is their average speeds which are their running speeds. Each newly
born rabbit carries with them an average speed, which reflects the current
average speed of the population. This situation shows that rabbits ‘pass on’
their speed genes to their offspring, adding to the total speed of the
population. Average speed per rabbit is calculated by dividing the Total Speed
by the number of rabbits in the population.
Normal
Graph of average speed per rabbit over years
The
above graph shows the normal graph of simple natural selection, whereas the
x-axis represents by the years while the y-axis represents the average speed
per rabbit. The left box is the parameters used to simulate the software. The
parameters can be change by double-clicking on the box. The list of allowable
parameters will show on, and we just have to use the appropriate parameters to
be investigated.
Effect
of change in bias to the average speed per rabbit over years
First,
the effect of change in speed bias to the average speed per rabbit over years
is investigated. In this part, the change in speed bias is manipulated. Four
trials were conducted to get varies graph. The change in speed bias is
manipulated with the value of 20, 30, 40, and 50. From the graph, we can see
the variation of the graph when we adjusting the value of change in speed bias.
The effect to the average speed per rabbit started at year 5 for all graphs.
The slope of the graph is increasing with increasing speed in bias.
Effect
of the size of the rabbit population to the average speed per rabbit over years
Second,
the effect of the size of rabbit population to the average speed per rabbit
over years is investigated. In this part, the value for the rabbit population
is manipulated. Three trials were conducted to get varies graph. The size of
rabbit population is manipulated with the value of 400, 450, and 500. From the
graph, we can see the variation of the graph when we adjusting the value of the
size of rabbit population. The effect to the average speed per rabbit started
at year 5 for all graphs. The slope of the graph is increasing with increasing
size of rabbit population.
Effect
of the size of the fox population to the average speed per rabbit over years
Lastly,
the effect of the size of the fox population to the average speed per rabbit
over years is investigated. In this part, the size of the fox population is
manipulated. Three trials were conducted to get varies graph. The size of the
fox population is manipulated with the value of 24, 25 and 26. From the graph,
we can see the variation of the graph when we adjusting the size of the fox
population. The effect to the average speed per rabbit started at year 5 for
all graphs. The slope of the graph is increasing with increasing size of fox
population.
3.0 Conclusion
Based
on my readings regarding this topic of simulation in education, I think that
the fate of simulations in educational system in Malaysia is good. The future
educational system in Malaysia will practice full function of simulation as
preparation for the Information Age that is full with advance and modern
technologies. Furthermore, learning by using simulations software have been
proved by researchers to give many benefits and advantages to students. Thus,
there is no hesitation to not use simulations as teaching-learning materials.
Students will obviously love to study using simulations. Students are often
find active participation in simulations to be more interesting, intrinsically
motivating and closer to real-world experiences than other learning modalities
(Alessi & Trollip, 2001).
Simulations learning will be a
meaning teaching aids in schools. They can be very flexible in that both
student and teacher can have a full control over the simulation variables.
These method also allow students to experience phenomena which could be
dangerous, expensive or even impossible to observe in the real world. Apart
from that, simulations can accommodate a wide range of instructional
strategies, including micro-worlds, scientific discovery learning, virtual
reality, laboratory simulations, role playing, case-based scenarios and
simulation gaming. Simulations are completely-packaged teaching aids to be used
in education.
In conclusion, I am strictly
recommended the use of simulations in learning process. They are user-friendly
and performed satisfactorily under various input condition. Furthermore, they
are packaged with many benefits to both student and teachers. These simulations
will help the students understand the concept in more detail. These simulations
can be used in conjunction with other teaching aids to enhance student learning
in various courses and will provide truly modern environment in which students
can study engineering, technology, and science at a level of detail.
4.0 References
Hans
Kraml (2002). Retrieved on November 30, 2012 from Simulation theory versus theory theory. University of Innsbruck.
How
to teach using data simulations. Retrieved on November 30, 2012 from http:// serc.carleton.edu/sp/library/datasim/how.html
Modeling
and simulation. Retrieved on November 30, 2012 from http://www.systems-thin king.org/modsim/modsim.htm
Natural
selection pressure. Retrieved on November 12, 2012 from http://www.systems wiki.org/index.php?title=Natural_Selection_Pressure
Simulation
(2012). Retrieved on November 10, 2012 from http://en.wikipedia.org/wiki/ Simulation.
Use
simulations to help students learn (2011). Retrieved on November 10, 2012 from
http:// www.creativeteachingsite.com/edusims.html.
What
is simulation software. Retrieved on November 30, 2012 from http://www.simul8.com/products/what_is_simulation.htm
What
is simulation. Retrieved on November 14, 2012 from http://www.goldsim.com/Web/ Introduction/Simulation/
What
is stella. Retrieved on November 30, 2012 from http://serc.carleton.edu/ introgeo/mathstatmodels/UsingStellaII.html
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