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  2. 2. Simulation is a particular type of modelling. Building a model is a well recognized way ofunderstanding the world and science processes or any social interactions. Simulations have‘inputs’ entered by researcher or person that is performing the simulation and ‘outputs’ whichare 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 systemwhich would be impossible, too expensive, or too impractical to perform. Simulation is an excellent way of modelling and understanding any processes. This isbecause, there are some interactions or processes that needed a long duration of time tohappened. Therefore by using simulation we can reduce the cost and time to conduct aresearch on any phenomenon or situation. Simulation also introduces the possibilities of anew way of thinking and developing a critical thinking among our society. Steps in simulation and model building are defining an achievable goal, put together acomplete mix of skills, involve end user, choosing an appropriate simulation tools, model theappropriate level of details and then start to collect the necessary input data. If all of thesesteps 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 ofthe interactions and daily phenomena that occurs around us. This is because by usingsimulation we can manipulate our variables. Therefore, this permits us to understand betterabout some parts of the interactions. Furthermore, we can look into some of the features thatmight be hard to explain by only reading books. With simulation we can actually see what isgoing on inside the system. Another classical use of simulation is for prediction. If we can develop a model whichfaithfully reproduces the dynamics of some behaviours, we can then stimulate the passing oftime and thus use the model to ‘look into the future’, Gilbert and Troitzsch (1999). From thisstatement, it describes how simulation can be a powerful model in explaining what wouldhappen in the future. For example, use of simulation in demographic research, where onewants to know how the size and age structures of a country’s population will change over thenext 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. 3. example, we are attracted by a situation and we want to learn or know more about thesystems. The problem is that we are not experts in that field. Therefore, experts systems havebeen constructed to stimulate the expertise of professionals such as geologist, chemists anddoctors. These systems can be used by non-experts to carry out diagnoses which wouldotherwise require human experts. Hence, we can carry out the simulation to know more aboutthe interaction or system that we want to study. As for the education in teaching and learning, simulation can provide the teachers andstudents better understanding of some topics. This will also triggers student interest to learnmore. This is because the student will feel motivated as they can predict and see the resultright in front of their eyes. Using simulation in teaching and learning can help to explain someof 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 constructdynamic models that realistically stimulate biological system or any systems. The STELLAsystem is ideal to interface with students investigative experiences. STELLA models allow usto communicate and to know how a system works, this include what goes in, how the systemis impacted and the outcomes of it. STELLA is used to stimulate a system over time, jump thegap between theory and the real world, enables student to creatively change systems, teachstudents to look for relationship whereby letting them to see the big pictures and clearlycommunicate 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 afundamental dynamic associated with natural selection pressure. The context is a rabbitpopulation whose average speed increases under predation pressure from a fox population. Asthe simulation experiment is conducted, the degree to which the selective forces work againstslower rabbits can be set at various ranges. This simulation focuses mainly on the averagespeed of the rabbits that can be observed changing over the year because of the naturalselection pressure. Before conducting the simulation, let us first understand and get some ideas aboutwhat natural selection is all about. In the 1850s, Darwin proposed natural selection as amechanism for evolutionary change. Natural selection can be defined as differential
  4. 4. reproduction and survival of individuals in a population due to the environment influences onthe population. Organism traits can influence on how well its offspring cope withenvironmental changes. Referring to the simulation model that I’ve conducted, theenvironmental influences referred to the predator of the rabbits which is fox population. Thepredator factor can increase the proportion of favourable traits in a population. Darwin’s theory of natural selection is; first, the members of a population haveinheritable variations. Variation within a population of a species occurs for a multitude oftraits, many which are heritable. In the simulation, the attribute of the Rabbit population thatwill undergo selection pressure is their average speed, or in simpler words the rabbit runningspeed. Therefore the heritable trait that we are studying is the rabbit average speed or runningability. The rabbits pass on their speed genes to their offspring. Hence, using this simulationwe will look into how the average speed of the rabbits will increase after few years as weincrease the change in speed bias. This is because as the traits for speediness of rabbit beingpassed from generations to generations over time, the average speed increase. Second, some individuals have favourable traits that enable them to better compete forlimited resources. The individuals with favourable traits acquire more resources than theindividuals with less favourable traits. Rabbit that runs faster is the favourable traits in thissimulation. Every single one of the rabbit in their population competes for resources such asfood and space. To keep living, the rabbits need to avoid from being eaten by fox. That is whyrunning speed is important to the rabbits. The running speed is to protect them from beingeaten by the fox. The faster they run, the less the fox can eat them. This is because, foxnormally will target on slower rabbits. The numbers of rabbit each fox eat per year depend onthe average speed of the rabbit population. This model does not allow foxes to go fasterbecause of the selective pressure. Third, natural selection can result in a population adapted to the local environment. Anincreasing proportion of individuals in each succeeding generation will have the favourabletraits 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 thenatural selection of the rabbits, what we can expect is that the average speed per rabbit willincrease in time. This is because; they need to survive which survive from being eaten by thefox. In order to survive they need to have greater average speed.
  5. 5. If one learnt about the theory of natural selection, one thing that they have in theirmind is that natural selection is the survival of the fittest. Although we often refer to therelative fitness of a genotype, remember that the entity that is subjected to natural selection isthe whole organism, not the underlying genotype. Only the fit individuals can survive andreproduce. Therefore, by using the STELLA simulation model of natural selection, thestudents can predict what will happen to the average speed of the rabbit population for thenext few years. After knowing basic information and the theory of natural selection by Darwin, we canconduct 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. 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 speedof the rabbit before natural selection occurred. Note that when setting the attribute to zero thisdoes not mean that the speed of the rabbit is zero, because the attribute is for the change inspeed bias. Zero means no change in speed rather than zero speed. When there is no change inspeed, the average speed will remain the same for years. From the graph above, over the yearthe average speed per rabbit is five and constant over the year. This shows that average speedof five is passed from generations to generations. When there is no change in speed, theaverage speed per rabbits will remain the same because no new traits with higher speed can bepassed to the newborn rabbit. Data 2
  7. 7. In the second data, I set the attribute to 15. This means that I increase the averagespeed 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 foxpredation, the rabbit need to run faster to avoid from being eat. We can see the addition to thetotal speed because the values come from new rabbits being born. The new rabbit carries withthem 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 totalspeed by the number of rabbits in the population. This produces an average speed per rabbit. Data 3
  8. 8. In data 3, I set the attribute to 30. Therefore, the change in speed is 30. This graph isabout the same with the graph from data 2. However this graph shows increasing in theaverage speed higher than in data 2. After five years, the average speed increasing over theyears until after 30 years the average speed is about eight. Data 4
  9. 9. In data 4, I set the attributes into the maximum change in speed which is 50. The graphshows higher increment compared to graphs in data 2 and data 3. The average speed perrabbits after 30 years is about nine. From all of the three graphs in data 2, 3 and 4, it showshow the average speed per rabbits is increase if we increase the change in the speed. As statedbefore, the average speed of the rabbits is calculated by dividing total speed by the number ofrabbits in the population. The outflow from the total speed occurs when rabbits die. When therabbits die of natural causes, they take with them the average speed of the population. Bear inmind that the fast rabbit also die of the natural causes at the same rate as the rest of thepopulation. The number of rabbits each fox eat per year depends on the average speed of the rabbitpopulation. As the rabbits get faster, on average, foxes can catch fewer of them. When the
  10. 10. rabbits are eaten by the fox, this will add to the outflow from the total speed. The outflow ofthe rabbits will not be calculated and added to the average speed. This is because the rabbitsthat die are the slower rabbits. So, the slower rabbits that being eaten by fox and die exits thepopulation, taking with them less than the average speed. Therefore, the remaining rabbitsaverage speed increases because only the fast will survive and the traits is passed to theiroffspring. From all of these four graphs, it shows that when we increase the change in speed, theaverage speed per rabbit will also increase after few years. These results proved the theory ofnatural selection. Darwin stated that traits are inherited from parents to offspring, individualswhose inherited traits give them a higher probability of surviving and reproducing in a givenenvironment tend to leave more offspring than other individuals, and this will lead to theaccumulation of favourable traits in the population over generations. By looking into the theory of natural selection to the one that are observed using thesimulation, we can say that the rabbit population follows the theory of natural selection. Thefavourable traits is the high average speed, where rabbits that can run fast. The fox will targetand eat slower rabbit. This will leave the fast runner rabbit to survive. This fast rabbit is fit tothe environment therefore reproduce. As the number of offspring that survive and reproduceis the one that run fast; considering the slower rabbit population is decrease because beingeaten by fox, the traits that are favoured will likely appear at a greater frequency in the nextgeneration. That is why, from graph in data 2, 3, and 4 the average speed will increase overtime. This is because after some times, the faster rabbit is the one that survive better andaccumulation 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 isbecause the theory of natural selection can only be observed occurred in individuals after fewyears. The theory of natural selection is can be used to explained the origin of species orevolution of species. For an evolution to occurred, it needed a long period of time. Same goesto natural selection, the favourable traits or the fittest individuals can only be seen after a longperiod of time. Therefore, it is hard for the students to imagine what would happen the nextfew years. By using simulation, students can predict what will happened to the populationsstudied without waiting for years or maybe decades. They can see the changes in the traitsstudied. From the simulation conducted, students will see that if they increase the change inspeed bias, the trend in average speed per rabbits will also increase. This will be the factors
  11. 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 andlearning have the potential to engage students in deep learning that will empowersunderstanding about the whole topics. Since simulation acquired the students to be theresearchers 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 theywill see clearly the relationship among variables. Simulation offer students the opportunity tomanipulate content knowledge and this will engages a variety of learning styles. This will alsotriggers interest as they explore and use the simulation. Deep learning is a good way to learncompared to surface learning which requires only memorization. With simulation, we can use model to predict outcomes. It is easier for the students tolearn using simulation because as they change the parameters, they can predict what willhappen. Furthermore, simulations help students understand scientific knowledge by testinghypotheses. This is due to the fact that simulations are very good at making clear thecomplexities involved in issues. Some aspects of the worlds can be imitate and replaced by using simulation. Studentsare not only motivated by simulations, but learn by interacting with them in a manner similarto the way they would react in real situations. Students will solve the problem, learnsprocedures and comes to understand the characteristics of phenomena and how to controlthem or learns what actions to take in different situation. Simulations reflect the complexity ofthe real life so that students will struggle and learn higher order cognitive skills such asinquiry. This higher order cognitive skill is essential for science learning. Problem based simulations allow students t monitor experiments, test new models andimprove their understanding of complex phenomena. Simulations are also useful forsimulating labs that are impractical, expensive, impossible or too dangerous to run.Conclusion
  12. 12. After conducting simulation model on natural selection, I would recommend others touse STELLA as well. This is because with simulation I can see clearly the interaction and theresult from the data. From my point of view, I see STELLA as a powerful teaching tool. Itwould be a brilliant idea to use STELLA model to study about relationship and interactionthat occur. Some of the theory learnt in schools cannot be proved using experiment orpractical due to reasons such as the cost and time. Therefore, by using STELLA we will notlimits our students understanding about a topic because we can conduct the simulation at anytime, without high cost and at anywhere. Furthermore, STELLA can increase the student motivation. They can make aprediction about what would happened, because they can change the variable into a certainvalues. This will triggers interest to study more. Does STELLA model suitable to be used inschool? My answer will be yes it is. Why? Basically because of the operation and steps inusing STELLA model is not complicated. It would take time for the student to use it at thefirst time, but as they getting exposed and comfortable with this simulation, it will be easy forthe students to use it. When students are exposed to STELLA model, it will be easy for theteacher to teach as well. This is due to the fact that they can conduct experiment with thesimulation to find out the answer.References
  13. 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 A. (2002). Introduction to Modeling And Simulation. Retrieved December 1st, 2012 from 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, 35-55Sami Sahin (2006): Implications for Distance Education, Turkish Online Journal of Distance Education-TOJDE July 2006 ISSN 1302-6488 Volume: 7 Number: 4 Article: 12Weimer M. (2010). Simulations Deliver Real Benefits. Retrieved December 1st, 2012 from real-benefits