1. DEPARTMENT OF BIOLOGY
FACULTY OF SCIENCE & MATHEMATICS
UNIVERSITI PENDIDIKAN SULTAN IDRIS
ASSIGNMENT 3
INFORMATION AND COMMUNICATION TECHNOLOGY IN BIOLOGY
SBI3013
GROUP A
STUDENT’S NAME AND
MATRIC NUMBERS
MOHAMAD AZRIN BIN MOHAMMAD KUDUS (D20152071983)
NUR HIDAYAH BINTI ABDUL HAMID (D20152071979)
NURULATIKAH BINTI ABDUL KHALID (D20152071971)
LECTURE’S NAME ENCIK AZMI BIN IBRAHIM
TITLE SIMULATION ON STELLA
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Table of Content
Content Page
1.0 INTRODUCTION
1.1 Simulation Theory 1
1.2 Stella Software 1-2
1.3 Experiment Theory 2-3
2.0 SIMULATION IN INDUSTRY 3-5
3.0 SIMULATION IN EDUCATION
3.1 Advantages 6
3.2 Limitation 7
4.0 CONCLUSION 8
REFERENCES
3. 1
1.0 INTRODUCTION
1.1 Simulation Theory
Simulation, in a glance this word is may thought be the most familiar among those who
work with the computers. What is simulation actually? According to the Oxford English
Dictionary, simulation is “the technique of imitating the behavior of some situation or
system, by means of an analogous model, situation or apparatus either to gain information
more conveniently or to train personal”. Hartmann (1996) define simulation as “a process
in which mimics the relevant features of a target process”. From the educational
perspective, Diana Laurilard in “Rethinking University Teaching” states, “a computer-
based simulation is a program that embodies some aspect of the world, which allows the
user to make inputs to the model and display the results”.
As we know, model will represent as an object, a system or an idea in some form
other than that of the entity itself(Shannon). Types of model are divided into two which are
physical and mathematical model. Physical model is like a scale models and prototype
plants while mathematical model is like analytical queuing model, linear programs and
simulations.
In the other words, simulation is indeed a method to represent a complex relation
in an easier way and in a lesser time consume. Simulation can be performed by anyone in
many areas. They just need the software or tools to run it. In educational purpose,
commercial, financial, logistics, health or even research purpose, simulation can be applied
and used. Even children can perform simulation as their tools of learning.
1.2 Stella Software
STELLA is a new software program that has been developed to enable very broad, non-
technical audiences to conceptualize, construct and analyze system dynamic models. One
of the goals of the development of STELLA is to enhance the learning process. This
software offers a practical way to visualize and communicate how complex and ideas really
work. It consists of endless questions, which make the users more attracted to use it. As
this software is easy to use, it has been used widely in education from economics to physics,
chemistry to public policy and literature to calculus. This model allows the user to
communicate how a system works. Generally, STELLA software is really useful for the
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visual learners because the animation, diagram and charts in this software can help them to
discover the relationship between variables in an equation. While for verbal learners, visual
models with words are more suitable for them.
STELLA is being used to stimulate a system over time, jump the gap between the
theory and the real world as the simulation is closely like the real one, enable students to
creatively change the systems by changing the value or variables. Moreover, to teach the
students to look for the relationships by seeing a big picture and clearly communicate
system inputs and outputs and demonstrate outcomes.
1.3 Experiment Theory
STELLA has been used in the experiment of Predator-prey Dynamics. Predator-prey
theory is traced from its origin in the Malthus-Verhulst logistic equation, thorugh the
Lotka-Volterra equations, logistic modification to prey and predator equations,
incorporation of the Michaelis-Menten-Holling functional response into the predator and
prey equations and the recnt development of ratio-dependent functional responses and per
capita rate of change functions.
In the study of the dynamics of a single population, we always take into
consideration such as factors of natural growth rate and the carrying capacity of the
environment. In this experiment, we study an interaction between two species, which are
prey and predators. Prey is the species that has been eaten while predator is the species that
eats the others.
Predation is only one of several agents that cause population cycles. Other factors
that contributed in the population cycles are mass emigration, genetic changes in the
population and physiological stress due to overcrowding. Population cycles are difficult to
achieve in the laboratory. usually, the predators search out every one of the prey and then
they go to extinction due to lack of food.
The predators- prey model may be stabilized by making two assumptions about the
growth rates of the prey and also about the growth rates of the predator. If the preys or
predators are destroyed at the same rate by some outside agent, the prey will proportionally
increase and the predators will proportionally decrease. This is because the birth rate of the
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prey is not affected, the death rate of the prey is reduced and the birth rate of the predator
is reduced.
2.0 SIMULATION IN INDUSTRY
In this simulation is focusing on a development of simulation model that portrays the relationship
of prey predator in biological control technique in palm plantation ecosystem. The presence of pest
especially rats however can cause a great damage and negative impact to the production of national
palm-oil resource. This more concentrates to the usage of biological control method specifically
owl to ascertain that the rat population in palm oil plantation is under control and in minimal rate.
A simulation method is applied. A model prototype is developed using Stella 8 simulation
software. This will be observed on the relationship of palm-oil resources and rat as well as the
relationships of rat and owl. Through this simulation we will identify the equilibrium of the
relationships from these three entities in order to assist the decision in using biological control
method for certain period.
GRAPH 1
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From the graph above, the relationship of rats and owls produced showed a positive result. We do
fix the population of rat at 13000 and the population of owl at 10. By referring to the graph pattern,
the population of owl decline as the population of rat deteriorates. This may due to the lack of food
supply. Next, the population of rat at the peak while the increasing line of the palm-oil resources.
Not long than that, the population of rat drop again and also the owl population as less number of
rat that serve as their source of food after few years ahead.
GRAPH 2
In this next graph, we do manipulate the number of population of rat where increased the amount
up to 40000 and remain the population of owl at the same amount. The pattern of this graph is
most likely to be as the first graph. 18.75 year after, the population of rat decreases as the
population of owl increases. However, the line of palm-oil resources is increasing rapidly.
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GRAPH 3
From this third graph, we do adjust the population number of rat back to 13000 while owl increased
to 20. The population of owl increased slightly in the beginning. Then it drops drastically to zero
after few hours as the population of rat was very low. From the graph, the population of rat
increased up to 3 million after 25 years and above as there is no one can threaten their life anymore.
While the palm-oil produced increased at the first 18.75 years but slightly drop as at the end the
population of rats start to increased rapidly.
Based from these three graph, what can be concluded is the simulation performed proves us that
the equilibrium of relationship among the palm-oil, rat and owl. Thus, the method of biological
control can be planned in order to control the rat’s population not even for now but also for long
25-year period ahead.
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3.0 SIMULATION IN EDUCATION
3.1 Advantages in using STELLA
Simulations can be powerful active learning experiences. Finding suitable simulation
exercises is a challenge in some fields and integrating them into the content and objectives
of the courses required a careful planning and execution. However, this extra work is
justified given what a good simulation can accomplish in class.
STELLA has generated many benefits to their users. As an example, the language
increases the accuracy and clarity of verbal descriptions, ambiguities diminishing and
communication becomes much more efficient and effective. Thus this can motivate the
students in purpose of an educational simulation. This can motivate the learner to engage
in the problem solving, hypothesis testing, experiential learning and so on. Using
simulation in teaching and learning is really an effective method in order to motivate the
students and to gain their interest toward learning. Besides, it includes the ability of the
simulation to create a risk free environment and allow students to explore more.
Simple analysis to predict something can be done by anyone. However, as the
complexity of the analysis increases, so does the need to employ computer-based tools.
One of the tool is simulation. With all the necessary study data, simulation can be useful
in predicting the future outcome. In a real life, no one can predict the future accurately, but
we still can study the pattern for the highest probability that it will occur. By using
simulation, student can study the trend of the outcome whenever they manipulate any
variables. The outcome for an example form a graph is usually observed over time. When
the simulation is run in several times, students can see the trend of the change in the graph.
Beside, this software more provides a check on intuition, and also provides a vehicle for
building an understanding. To make the data in easier transform, this tools also putting
together in an organized and clear way to the qualitative and quantitative approaches
present in form of the CIR-DSS framework. Analyzing and predicting data using
simulation can enhance students’ thinking skills and also problem solving skill. Other than
that, this process also can give student the introduction on how to do a research, which they
will do it in their higher level of education later.
Lastly, STELLA is a tool that enables an easier operation, demonstration and
replication of the CIRDSS. Sometimes, students are hard to understand science concept
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that literally cannot be seen through the lens of their eyes. Therefore, they need some
visualization to help them see and understand the phenomenon or process occurs. That is
why simulation is integrated in teaching and learning science. To help students visualize
and get a big picture of what they are learning.
3.2 Limitation in Using STELLA
Although that simulation is seen having a good potential to be integrated in school in the
future, right now there are still some limitation in it. First, not every teacher is familiar with
simulation. To use simulations in class could be burden to them as they need a long time
to explore the simulation. When the teachers do not really know how to use the simulation,
they tend to spend more time trying to explore it. Thus, this could lead to an environment
of unsure teacher and confused students. Therefore, without expertise in using simulation,
it can be rather wasting than saving times as it should be. (Korb, 2012)
Other limitation of simulation is that simulation can cause students to lack in
manual science process skill which is also important in real life. If learning process depends
too much on simulations, then students will not be able to handle the manual process
experiment successfully. In science experiment, the way of measuring substances, how to
handle the apparatus, how to use microscope, correct way of taking reading are all these
essential as a basic scientific skill. Lacking of these skills can cause difficulty to students
when they need to do in real scientific experiment or research later.
Simulation can give result, analyze data and mimic into the real world process. But,
simulation cannot develop students’ emotional and intuitive awareness of the importance
of what they have learned. Since simulation can simplify many of the students’ work,
students tend to not appreciate the knowledge and the value they gain.
Other limitation is computer simulation cannot react to unexpected ‘subgoals’
which the student may develop during a learning process. These sub-goals would be
brought up during a teacher-student interaction but they remain unsaid during the
individual student use of a simulation.
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4.0 CONCLUSION
Simulation is suitable to be used in the school because it can motivate students in learning process.
Simulation can motivate students by keeping them actively engaged in the learning process
through requiring that problem solving and decision making skills be used to make the simulation
run. As the simulation runs, it is modelling a dynamic system in which the learning is involved.
Thus, participation in simulations enables students to engage in systems thinking and enhances
their understanding of systems as well as science concepts (Berryman, 1992)
Actually, simulation can be considered as a powerful tool in active learning experiences. It
can provide a kind of lab-like experience. So the students will become more exciting and inspiring
in study because most of the students will become more exciting and inspiring in study as most of
them more prefer to do something new rather than just sit and hear. Finding a good simulation in
teaching is a challenges for the teacher in order to integrate them into the content and objectives
of the course chosen. However, if the teachers know what their students need, it will be easier for
them to choose a right simulation for their students. STELLA is suitable to be launched in
Malaysia’s school as it is one of the simulations that give benefits to the users whether the user is
a student or a teacher.
REFERENCES:
Berryman, A. A. (1992, October 5th ). The Orgins and Evolution of Predator-Prey Theory.
Retrieved from Ecology:
http://www.jstor.org/stable/1940005?seq=1#page_scan_tab_contents
Korb, K. B. (2012, november 11). The Philosophy of Computer Simulation. Retrieved from
Clayton School of Info Tech Monash: http://www.csse.monash.edu.au/-korb/lmps.pdf
