The document discusses using the STELLA simulation software to model natural selection. It begins with an overview of simulation and modeling. It then discusses using STELLA specifically to model a rabbit population undergoing natural selection from fox predators. The model shows the average rabbit speed increasing over generations as slower rabbits are preyed upon more. The document analyzes the results and shows how they support Darwin's theory of natural selection. It concludes that STELLA is an effective teaching tool that can increase student understanding and motivation by allowing them to predict population changes over time.

1. DEPARTMENT OF BIOLOGY
FACULTY OF SCIENCE AND MATHEMATICS
UNIVERSITI PENDIDIKAN SULTAN IDRIS
SSI3013: INFORMATION AND COMMUNICATION
TECHNOLOGY IN SCIENCE
Semester I Session 2012/2013
MODELLING AND SIMULATION USING STELLA
Title: Natural Selection Pressure
Introduction

2. Simulation is a particular type of modelling. Building a model is a well recognized way of
understanding the world and science processes or any social interactions. Simulations have
‘inputs’ entered by researcher or person that is performing the simulation and ‘outputs’ which
are observed as the simulations run. A simulation of a system is the operation of a model,
which is a representation of that system. This model can be used to manipulate a system
which would be impossible, too expensive, or too impractical to perform.
Simulation is an excellent way of modelling and understanding any processes. This is
because, there are some interactions or processes that needed a long duration of time to
happened. Therefore by using simulation we can reduce the cost and time to conduct a
research on any phenomenon or situation. Simulation also introduces the possibilities of a
new way of thinking and developing a critical thinking among our society.
Steps in simulation and model building are defining an achievable goal, put together a
complete mix of skills, involve end user, choosing an appropriate simulation tools, model the
appropriate level of details and then start to collect the necessary input data. If all of these
steps are met, we can have a powerful simulation model that is benefits to everyone.
One of the uses of simulation is to obtain a better understanding of some features of
the interactions and daily phenomena that occurs around us. This is because by using
simulation we can manipulate our variables. Therefore, this permits us to understand better
about some parts of the interactions. Furthermore, we can look into some of the features that
might be hard to explain by only reading books. With simulation we can actually see what is
going on inside the system.
Another classical use of simulation is for prediction. If we can develop a model which
faithfully reproduces the dynamics of some behaviours, we can then stimulate the passing of
time and thus use the model to ‘look into the future’, Gilbert and Troitzsch (1999). From this
statement, it describes how simulation can be a powerful model in explaining what would
happen in the future. For example, use of simulation in demographic research, where one
wants to know how the size and age structures of a country’s population will change over the
next few years or decade. It is rather hard and complicated to obtain an instant result,
therefore by using simulation we can predict what will happen in the future.
Another use of simulation is to develop new tools to substitute for human capabilities.
We can use simulation to study more complex systems that is out of our capabilities. For

3. example, we are attracted by a situation and we want to learn or know more about the
systems. The problem is that we are not experts in that field. Therefore, experts systems have
been constructed to stimulate the expertise of professionals such as geologist, chemists and
doctors. These systems can be used by non-experts to carry out diagnoses which would
otherwise require human experts. Hence, we can carry out the simulation to know more about
the interaction or system that we want to study.
As for the education in teaching and learning, simulation can provide the teachers and
students better understanding of some topics. This will also triggers student interest to learn
more. This is because the student will feel motivated as they can predict and see the result
right in front of their eyes. Using simulation in teaching and learning can help to explain some
of the theories that were developed years ago.
Using STELLA model to study about natural selection
STELLA is a flexible computer modelling package that allows users to construct
dynamic models that realistically stimulate biological system or any systems. The STELLA
system is ideal to interface with students investigative experiences. STELLA models allow us
to communicate and to know how a system works, this include what goes in, how the system
is impacted and the outcomes of it. STELLA is used to stimulate a system over time, jump the
gap between theory and the real world, enables student to creatively change systems, teach
students to look for relationship whereby letting them to see the big pictures and clearly
communicate systems inputs and outputs and demonstrate outcomes.
I choose to study about the natural selection pressure using the STELLA model.
Natural selection pressure using STELLA is a simple model that begins to address a
fundamental dynamic associated with natural selection pressure. The context is a rabbit
population whose average speed increases under predation pressure from a fox population. As
the simulation experiment is conducted, the degree to which the selective forces work against
slower rabbits can be set at various ranges. This simulation focuses mainly on the average
speed of the rabbits that can be observed changing over the year because of the natural
selection pressure.
Before conducting the simulation, let us first understand and get some ideas about
what natural selection is all about. In the 1850s, Darwin proposed natural selection as a
mechanism for evolutionary change. Natural selection can be defined as differential

4. reproduction and survival of individuals in a population due to the environment influences on
the population. Organism traits can influence on how well its offspring cope with
environmental changes. Referring to the simulation model that I’ve conducted, the
environmental influences referred to the predator of the rabbits which is fox population. The
predator factor can increase the proportion of favourable traits in a population.
Darwin’s theory of natural selection is; first, the members of a population have
inheritable variations. Variation within a population of a species occurs for a multitude of
traits, many which are heritable. In the simulation, the attribute of the Rabbit population that
will undergo selection pressure is their average speed, or in simpler words the rabbit running
speed. Therefore the heritable trait that we are studying is the rabbit average speed or running
ability. The rabbits pass on their speed genes to their offspring. Hence, using this simulation
we will look into how the average speed of the rabbits will increase after few years as we
increase the change in speed bias. This is because as the traits for speediness of rabbit being
passed from generations to generations over time, the average speed increase.
Second, some individuals have favourable traits that enable them to better compete for
limited resources. The individuals with favourable traits acquire more resources than the
individuals with less favourable traits. Rabbit that runs faster is the favourable traits in this
simulation. Every single one of the rabbit in their population competes for resources such as
food and space. To keep living, the rabbits need to avoid from being eaten by fox. That is why
running speed is important to the rabbits. The running speed is to protect them from being
eaten by the fox. The faster they run, the less the fox can eat them. This is because, fox
normally will target on slower rabbits. The numbers of rabbit each fox eat per year depend on
the average speed of the rabbit population. This model does not allow foxes to go faster
because of the selective pressure.
Third, natural selection can result in a population adapted to the local environment. An
increasing proportion of individuals in each succeeding generation will have the favourable
traits which is the characteristics suited to surviving and reproducing in that environment.
Therefore, it is more into the adaptation into the environment. If we run the simulation on the
natural selection of the rabbits, what we can expect is that the average speed per rabbit will
increase in time. This is because; they need to survive which survive from being eaten by the
fox. In order to survive they need to have greater average speed.

5. If one learnt about the theory of natural selection, one thing that they have in their
mind is that natural selection is the survival of the fittest. Although we often refer to the
relative fitness of a genotype, remember that the entity that is subjected to natural selection is
the whole organism, not the underlying genotype. Only the fit individuals can survive and
reproduce. Therefore, by using the STELLA simulation model of natural selection, the
students can predict what will happen to the average speed of the rabbit population for the
next few years.
After knowing basic information and the theory of natural selection by Darwin, we can
conduct the simulation to find out and predict what will happen as we change the attributes.
The results are shown in 4 different type of graph with 4 different value being change.
Result

6. Data 1
For the first data, I set the attribute to zero. The attribute referred to the average speed.
When set to zero, it means that no change in speed. This can be regarded as the initial speed
of the rabbit before natural selection occurred. Note that when setting the attribute to zero this
does not mean that the speed of the rabbit is zero, because the attribute is for the change in
speed bias. Zero means no change in speed rather than zero speed. When there is no change in
speed, the average speed will remain the same for years. From the graph above, over the year
the average speed per rabbit is five and constant over the year. This shows that average speed
of five is passed from generations to generations. When there is no change in speed, the
average speed per rabbits will remain the same because no new traits with higher speed can be
passed to the newborn rabbit.
Data 2

7. In the second data, I set the attribute to 15. This means that I increase the average
speed 15 times higher than the initial. It can be observed from the graph that after five years,
the speed of the rabbits is increasing from five to about seven. To survive from the fox
predation, the rabbit need to run faster to avoid from being eat. We can see the addition to the
total speed because the values come from new rabbits being born. The new rabbit carries with
them an average speed which reflects the current average speed of the population. That is,
rabbits pass on their genes to their offspring. Average speed is calculated by dividing total
speed by the number of rabbits in the population. This produces an average speed per rabbit.
Data 3

8. In data 3, I set the attribute to 30. Therefore, the change in speed is 30. This graph is
about the same with the graph from data 2. However this graph shows increasing in the
average speed higher than in data 2. After five years, the average speed increasing over the
years until after 30 years the average speed is about eight.
Data 4

9. In data 4, I set the attributes into the maximum change in speed which is 50. The graph
shows higher increment compared to graphs in data 2 and data 3. The average speed per
rabbits after 30 years is about nine. From all of the three graphs in data 2, 3 and 4, it shows
how the average speed per rabbits is increase if we increase the change in the speed. As stated
before, the average speed of the rabbits is calculated by dividing total speed by the number of
rabbits in the population. The outflow from the total speed occurs when rabbits die. When the
rabbits die of natural causes, they take with them the average speed of the population. Bear in
mind that the fast rabbit also die of the natural causes at the same rate as the rest of the
population.
The number of rabbits each fox eat per year depends on the average speed of the rabbit
population. As the rabbits get faster, on average, foxes can catch fewer of them. When the

10. rabbits are eaten by the fox, this will add to the outflow from the total speed. The outflow of
the rabbits will not be calculated and added to the average speed. This is because the rabbits
that die are the slower rabbits. So, the slower rabbits that being eaten by fox and die exits the
population, taking with them less than the average speed. Therefore, the remaining rabbits
average speed increases because only the fast will survive and the traits is passed to their
offspring.
From all of these four graphs, it shows that when we increase the change in speed, the
average speed per rabbit will also increase after few years. These results proved the theory of
natural selection. Darwin stated that traits are inherited from parents to offspring, individuals
whose inherited traits give them a higher probability of surviving and reproducing in a given
environment tend to leave more offspring than other individuals, and this will lead to the
accumulation of favourable traits in the population over generations.
By looking into the theory of natural selection to the one that are observed using the
simulation, we can say that the rabbit population follows the theory of natural selection. The
favourable traits is the high average speed, where rabbits that can run fast. The fox will target
and eat slower rabbit. This will leave the fast runner rabbit to survive. This fast rabbit is fit to
the environment therefore reproduce. As the number of offspring that survive and reproduce
is the one that run fast; considering the slower rabbit population is decrease because being
eaten by fox, the traits that are favoured will likely appear at a greater frequency in the next
generation. That is why, from graph in data 2, 3, and 4 the average speed will increase over
time. This is because after some times, the faster rabbit is the one that survive better and
accumulation of this traits occurred leading to high average speed per rabbit.
Studying about natural selection can be a hard topic for some of the student. This is
because the theory of natural selection can only be observed occurred in individuals after few
years. The theory of natural selection is can be used to explained the origin of species or
evolution of species. For an evolution to occurred, it needed a long period of time. Same goes
to natural selection, the favourable traits or the fittest individuals can only be seen after a long
period of time. Therefore, it is hard for the students to imagine what would happen the next
few years. By using simulation, students can predict what will happened to the populations
studied without waiting for years or maybe decades. They can see the changes in the traits
studied. From the simulation conducted, students will see that if they increase the change in
speed bias, the trend in average speed per rabbits will also increase. This will be the factors

11. that can increase their motivation to learn. When they can see the outcomes of the simulation,
it they will feel motivated to study and learn more.
Advantages of using simulation in teaching and learning
Simulation can be a powerful learning experience. Using simulation in teaching and
learning have the potential to engage students in deep learning that will empowers
understanding about the whole topics. Since simulation acquired the students to be the
researchers and conduct the simulation by them this will engage students to their learning.
Simulation allows students to change parameter value and see what happen. Therefore they
will see clearly the relationship among variables. Simulation offer students the opportunity to
manipulate content knowledge and this will engages a variety of learning styles. This will also
triggers interest as they explore and use the simulation. Deep learning is a good way to learn
compared to surface learning which requires only memorization.
With simulation, we can use model to predict outcomes. It is easier for the students to
learn using simulation because as they change the parameters, they can predict what will
happen. Furthermore, simulations help students understand scientific knowledge by testing
hypotheses. This is due to the fact that simulations are very good at making clear the
complexities involved in issues.
Some aspects of the worlds can be imitate and replaced by using simulation. Students
are not only motivated by simulations, but learn by interacting with them in a manner similar
to the way they would react in real situations. Students will solve the problem, learns
procedures and comes to understand the characteristics of phenomena and how to control
them or learns what actions to take in different situation. Simulations reflect the complexity of
the real life so that students will struggle and learn higher order cognitive skills such as
inquiry. This higher order cognitive skill is essential for science learning.
Problem based simulations allow students t monitor experiments, test new models and
improve their understanding of complex phenomena. Simulations are also useful for
simulating labs that are impractical, expensive, impossible or too dangerous to run.
Conclusion

12. After conducting simulation model on natural selection, I would recommend others to
use STELLA as well. This is because with simulation I can see clearly the interaction and the
result from the data. From my point of view, I see STELLA as a powerful teaching tool. It
would be a brilliant idea to use STELLA model to study about relationship and interaction
that occur. Some of the theory learnt in schools cannot be proved using experiment or
practical due to reasons such as the cost and time. Therefore, by using STELLA we will not
limits our students understanding about a topic because we can conduct the simulation at any
time, without high cost and at anywhere.
Furthermore, STELLA can increase the student motivation. They can make a
prediction about what would happened, because they can change the variable into a certain
values. This will triggers interest to study more. Does STELLA model suitable to be used in
school? My answer will be yes it is. Why? Basically because of the operation and steps in
using STELLA model is not complicated. It would take time for the student to use it at the
first time, but as they getting exposed and comfortable with this simulation, it will be easy for
the students to use it. When students are exposed to STELLA model, it will be easy for the
teacher to teach as well. This is due to the fact that they can conduct experiment with the
simulation to find out the answer.
References

13. Gilbert N. & Troitzsch G. (1999). Simulation for the Social Scientist. Open university Press,
Celtic Court, Buckingham.
Gokhale A. (1996). Effectiveness of Computer Simulation for Enhancing Higher Order
Thinking. Retrieved December 1st, 2012 from
http://scholar.lib.vt.edu/ejournals/JITE/v33n4/jite-v33n4.gokhale
Maria A. (2002). Introduction to Modeling And Simulation. Retrieved December 1st, 2012
from http://www.inf.utfsm.cl/~hallende/download/simul-22001/
Patti Soderberg & Frank Price (2003): An examination of problembased teaching and
learning in population genetics and evolution using EVOLVE, a computer simulation,
International Journal of Science Education, 25:1, 35-55
Sami Sahin (2006): Implications for Distance Education, Turkish Online Journal of
Distance Education-TOJDE July 2006 ISSN 1302-6488 Volume: 7 Number: 4 Article:
12
Weimer M. (2010). Simulations Deliver Real Benefits. Retrieved December 1st, 2012 from
http://www.teachingprofessor.com/articles/teaching-and-learning/simulations-deliver-
real-benefits