Assignment 3 - Report on STELLA Simulation

FACULTY OF SCIENCE AND MATHEMATICS
SULTAN IDRIS EDUCATION UNIVERSITY
INFORMATION AND COMMUNICATION TECHNOLOGY IN SCIENCE
SSI 3013
TITLE: SIMULATION MODEL: STELLA SIMULATOR
PREPARED BY: NAME STUDENT ID
SITI FATIMAH BINTI ZULKIFLI D20152072027
NAZIHAH BINTI RAMLI D20152072030
NURFARHANA BINTI ROSLI D20152072035
LECTURER’S NAME: ENCIK AZMI BIN IBRAHIM
LECTURE GROUP: B

Table of Contents
1.0 Introduction…………………………………………………………………………..1
2.0 STELLA®
Graph Simulation Analysis……………………………………………..2
3.0 Benefits of simulation in student’s learning
3.1. Can manipulate the parameter…………………………………………….…4
3.2. Increase the motivation of students………………………………………….5
3.3. To make the prediction of the data………………………………………......6
4.0 Conclusion…………………………………………………………………………..7
5.0 Reference………………………………………………………………………......8

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1.0 Introduction
Humphreys (1991) defined that a computer simulation is any computer-implemented method
for exploring the properties of mathematical models where analytic methods are unavailable
(p. 501). In other words, simulation is the creation of a model that can be manipulated
logically to decide how the physical world works and in some cases you actually can make a
conclusion from that.
Building a simulation sounds like a lot of effort, and it often is. There are two
important reasons to construct a computer simulation. The first reason is to solve a problem
for which normal mathematical methods won’t work or are too complex, or when trying it in
real life is not an option. The second reason to build a simulation and one more important to
educators is as a learning object. It is to provide a realistic object or environment with which
to interact. Through it, this is experiential learning at its best. And, as educators we also
know that as well as answering questions about how things might work (those wonderful
“What if?” questions), they can also be used as educational tools to help provide learners
with the next-best things to hands-on experience. In simulations, for the most part, failure is
free, but allowing mistakes takes time and this is runs opposite to the goal that many
educators support, namely to make education more efficient.
There are many functions of simulations in science. According to Hartmann (1996),
some of the main motives to run simulations in a science-teaching context are simulations as
a technique to investigate the detailed dynamics of a system, simulations as a heuristic tool
to develop hypotheses, models and theories, simulations as a substitute for an experiment to
perform numerical experiments, simulations as a tool for experimentalists to support
experiments and simulations as a pedagogical tool to gain understanding of a process.
One of the popular simulations is STELLA®
software. STELLA stands for Systems
Thinking, Experimental Learning Laboratory with Animation. It was introduced by Barry
Richmond, an American systems scientist, in 1985. It is a software which allow any users
that own the software to run the software as graphical representations of a system. From the
example given, the experiment is conducted to investigate the effect of biological control
(owls) on the production of palm oils and the population of mice in a palm ecosystem.

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2.0 Graph Analysis of STELLA®
Simulation
Systems Thinking, Experimental Learning Laboratory with Animation (STELLA®
) is one of
the modelling systems that used the concepts of simulation with the diagrams and graph
package provided. Here are the examples of results obtained from the STELLA®
software.
This simulation is involving the observation of palm oil production due to the presence of rat
and owl. From this graph that automatically plotted, we can see the relationship between the
presence of rat and owl to the number of palm oil production. There are some variables that
are involved in this simulation. Based on the graph that been observed, the three variable
involved are constant variable, manipulated variables and responding variables. For the
constant variables, it is represents by the rat’s population which it is being constant for
20000 populations. While owls population act as the manipulated variables as can be seen
through this simulation, the population is being adjust form 12 to 18 for the second graph,
and then to 16 for the third graph. For the last variable which is responding variable where it
is the important data for being obtained is related to the palm oil population.
a) Normal Graph

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The graph above shows the normal graph to observe the relationship between
presence of rat and owl with the palm oil production. In this simulation, it can be seen that
there are three line, blue, pink and red representing owl, rat and palm oil respectively. As
what can be observed through the graph, the palm oil production is constantly increasing
when the number of owl present with the increase number of rat. This graph shown that
when the number of owl increases, the number of rat presence will decrease hence cause
the increasing of palm oil production. This is due to the food chain phenomenon where palm
oil plays role as producer, rat as the primary consumer that eat palm oil and owl as the
secondary consumer that eat rat as their food source
b) Adjusted Graph A
The second graph shows the different graph result compared to the normal graph.
What can be seen from this graph is there are the drastic changes of the number of owl from
18 to totally absence which is 0. From the graph, the number of rat present is in a small
number hence cause the palm oil production increase drastically. However, at the state
where the number of rat increases to the large number, it causes the worst production of
palm oil as rats are the primary consumer that eats the palm oil. Reduce of palm oil
production then cause the planter having a big loss in the palm oil planting. This is due to the
chance decrease for the palm oil to produce as there are increasing numbers of rat that eat
and bother the palm oil growth at the farm.

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c) Adjusted Graph B
For the third graph, the manipulation of the graph is different from the second graph.
There is the adjustment of owl population where the number is remain constant. The
constant population of owls, give the same graph pattern of rats population and palm oil
production. What can be seen through the graph for the initial state, the presence of owls
cause the population of rats increasing in slow rate. However, as the population of owls are
remain constant till the terminal state, therefore it cannot overcome the population of rats
and cause the increasing number in rats population. Hence, rats as the primary consumer to
the palm oil cause the palm oil production become slower and the population of palm oil then
decrease drastically. At the terminal state of palm oil production line graph, it can be seen
that, the production is totally decrease as the presence of high population of rat at the farm.
3.0 Benefits of STELLA® simulation for student’s learning
3.1. Can manipulate the parameter
In education, a simulation like Stella® software offers the teacher the possibility of
placing their students into real situations in order to better learn the material.
Manipulating and observing are additional values coming from simulation. When the
learning objective is to explore the relationship between variables and their impact on a
whole system, a simulation is recommended. A simulation differs from others kind of
models by its dynamic nature. It allows an observer to view not only a single point in time
in the model but also how it changes under different parameters. It is through

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experimenting with the numerous variables that control the models that a simulation can
provide a variety of outcomes.
In doing an experiment on the palm ecosystem, the students can manipulate the
parameter of the palm ecosystem and observe how the simulated outcomes changes.
The manipulation included the input such as knobs, sliders, switches, buttons and
outputs such as text, graph, table and report. Through that, the student will have higher
intrinsic motivation to understand the topic compared to traditional learning and relate the
content knowledge with the real life situations. On top of that, Stella® simulation gives an
advantage to students who are visual learners to ‘see’ a process, rather than only hear
about how it is done or how it works. Simulation provides visual stimulation and feedback
of an actual object, even when that object is a virtual representation of an object in the
real world.
3.2. Increase the motivation of students
The next benefit on how simulation helps in Science Education is related to the students’
motivation. When they run the simulation repeatedly then they will see the pattern of the
experiment so that, this will encourage them to become more motivate and curious on
what will happen next. From what they have viewed through the simulation, students will
be eager to know deeply about the topic related to the simulation. As we know, students
nowadays are being exposed to the technologies and simulation is one of the technology
usages that undergo the operation of a model that show the real situation. The main
point of simulation is to attract students in learning and teaching process. Education
system nowadays are concerning about the 21st
century learning process that are
referring to the student-centred, collaborative, cooperative, critical thinking, technology
and digital literacy, problem solving and any skills that focusing on students’ soft skills
and self-development that will guide them to thrive in today’s world.
The increase of motivation can occur through the increase of communication skills
of students. When they run the simulation, it needs the much communications during the
session between students and teachers or among students themselves. Simulations
process needs an active communication as they need guide from the teacher if there are
anything that they are not understand. This will encourage them to ask teachers and
during the learning process it will stimulate their brain to think on what they have been
done and this will form a discussion session among students as they are notified that the
real practice is interesting and help them to understand certain topic easily. Besides
verbal communication, simulation also helps in increasing written communication in

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composing reports or answering questionnaires of the topic related. For sure, after the
process of running simulation, students are required to do a report on what they have
observed. So, it will increase student’s communication skills on writing communication
besides on verbal communication.
Besides, simulation technique in Science Education will increase the students’
motivation on the group work and work ethics. Sometimes, they need to do the
simulations in group because of the limit of computer provided in school computer lab.
So, this will increase their motivation when they are working on group. At the age of
students, they are prefer to do something with their friends as at this age, they are enjoy
in making friends and usually are closer and believe friends more than others. When
they are working as a team, the presence of friends around them will improve their
motivation and they will be more eager to explore and learn deeply on the stimulation. In
the other hand, when they work on simulation, then it will improve their work ethics such
as the self-concerning on doing work by referring to the right procedure and learn to
listen well to the instructions given. This will lead them to be more responsible on their
team goal and as well as develop their self-responsibility.
The increase of motivation also can be seen from the aspects of students’
determination during running process of the simulation. When they run the simulation, it
will teach them how to be determined and never give up. For example, when they run
the simulation wrongly for the several times, the way they overcome and their
determination to run it again and again until they obtained the required result shows how
high their self-motivation in doing their works. This is how simulation helps in increase
students’ motivation through the learning and teaching process. Besides, it will increase
their self-confidence on what they have do hence the simulation will give the result
directly to them and make them believe and confident on the result that been obtained
from their own effort on running the simulation. Other than that, simulation skills in
learning process teach students for being honest and responsible on their own result and
they should not cheating on the result obtained during the report presentation either in
verbal presentation or writing presentation.

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3.3. To make the prediction of the data
Anyone can perform a simple analysis manually. However, the computer-based tools
were needed as the complexity of the analysis increases. Simulation is the best method
to analyse complex and large practical problem when it is not possible to solve them
through a mathematical method. When we run the experiment, the accuracy of the result
obtained was the important one. As we know, the traditional experimentation starts with
the collection of data. If these data points were plotted on an x and y graph, a common
way to assume what measurements would be collected between the two points would be
assume an average or linear relationship between them. However, if the actual
behaviour of the system between the two points was not linear, predicting the
measurements that would be poor. Therefore, when we are using the simulation in
education, we can avoid the false predictions that always happens especially when
involved big data or by reality-based checks. The students can make the prediction of
the experiment with more accurate using simulation.
By using STELLA®
simulation, the students learn to analyse and explore
themselves. The usages of the simulation in learning and teaching process gave a new
vibe and different environment for the student to learn something new. Since the learning
styles nowadays are more to student-centred, the students will not depend on their
teachers to achieve the information. This also can be one of the ways for the students to
understand more about the experiment. Besides, when the simulation is run for several
times, the students can see the trend of the change in the graph pattern. If the students
understand about the experiment, they can easily predict the result of the experiment.
Therefore, analysing and predicting data by using simulation can enhance students’
thinking and problem solving skills.
4.0 Conclusion
As the conclusion, the merits of digital simulation in education can be summarized into
cognitive benefits such as ‘knowledge’ and ‘skill’, and also into pedagogical benefits such as
‘individualized learning’. There are important reasons to construct a computer simulation
which are to solve the complex problem and to build a simulation as a learning object. We
can see the relationship between the presence of rats and owls to the number of palm oil
production based on the example of results obtained from the STELLA®
software. The
STELLA®
simulation benefits to student’s learning because they can manipulate the
parameter, increases the motivation in learning process and also they can explore and make
prediction of the experiment using simulation.

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5.0 References
Banks, Carson, Nelson & Nicol. (n.d). Introduction to simulation. Retrieved from
https://cs.wmich.edu/alfuqaha/Spring10/cs6910/lectures/Chapter1.pdf on 28 April
2018
Gibson, D. & Baek, Y. (2009). Digital Simulations for Improving Education: Learning Through
Artificial Teaching Environment. Hershey, PA: Information Science Reference (an
imprint of IG Global)
Hartmann, S. (1996). The world as a process: Simulations in the natural and social sciences,
in R. Hegselmann et al (Eds.), Modelling and simulation in the social sciences from
the philosophy of science point of view. Theory and decision library (pp. 77-100),
Dordrecht: Kluwer.
Humpreys, P. (1991). Computer simulations. In Fine, M. Forbes & L. Wessel (Eds.), PSA, 2,
497-506. East Lansing: Philosophy of Science Association.
Kopf, S., Scheele, N., Winschel, L. & Effelsberg, W. (2005). Improving activity and
motivation of students with innovative teaching and learning technologies. Retrieved
from
https://pdfs.semanticscholar.org/e408/79f7741c2d1eee9089eb0095ae997d29f49e.pd
f on 28 April 2018
Sviridova, T. (2012). Project simulation game as way to increase motivation in education
process. Retrieved from https://library.iated.org/view/SVIRIDOVA2012PRO on 29
April 2018

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