Since it is able to combine so many different facts and concepts, the theory of descent with modifications is considered to be the key to biology ( Dobanski, 1973). A more important explanation of how to decline with modifications is the theory of natural selection (Darwin, 1890). Although these theories are important, students may leave biology classrooms at all levels without proper understanding ( See Brumby, 1979; Demastes et al. , 1995; Fahrenwald, 1999; Ferrari and Chi, 1998; Tatina, 1989; Zimmerman, 1987). In response to the importance of evolutionary teaching, many authors have published articles providing activities designed to help students understand evolution. McComas (1991) List 18 items in non Textbook/laboratory manual literature. I found 16 other articles in my search for the ERIC database, using \"natural selection\" as a keyword, and found three other articles in recent literature. These citations are listed in the appendix. Several of these articles describe the activities of using simulations to clarify concepts related to natural selection. However, none studied the interaction between the two species at the time of interaction. Darwin (1890) The consequences of the interaction between the two species are described in these words :\". . . If any species is not modified and improved to a corresponding extent with its competitors, it will be extinct. \" Van Valen (1973) In studying the rate of extinction of species, the co-evolution of the two species is mathematically interpreted as a \"zero-sum game\" and called it the assumption of the Red Queen. Later Dawkins (1996) The analogy of an \"arms race\" describes co-evolution in which the two superpowers constantly improve their weapons, only to find that neither has a greater advantage over the other. Similar relative gains do not exist for co-existing species that compete with each other or act as predators/prey or parasite/host interactions. In this article, I describe the simulation of an \"arms race\" of co-evolution and introduce a teaching method for students to use the theory of natural selection to explain the results of the simulation. Simulate the use of digital cards from UNO [R] Playing Cards ( Marketing by international games 1551 Pinfield Road, IL 60435; Most large department stores have) Represents the speed of individuals in predators and their prey populations. ( Alternatively, a numbered index card or regular playing card can be replaced. ) Simple descriptive statistics are then used to illustrate the changes in both groups. Material * two UNO [R] A card game or four decks for three pairs of teams, 16 for each team. Card distribution for each team is shown in Table 1. * 12 envelopes, each marked with the name \"predator\" or \"prey\" and the code letter showing the predator/prey pair (e. g. Predator A with prey A, Predator B with prey B, etc). In the simulation of my mixing professional introductory biology class, I have several individuals working as a team in one unit. To launch the simulation, each of these teams receives an envelope with 16 numbers UNO [s]R] Cards and labels that indicate whether they represent prey or predator populations, and which species they have a predator or prey relationship. Each card in the envelope represents an individual and how fast it is running. In the predator/prey pair envelope, the card forms a frequency distribution of the speed of operation, making the average speed of the prey population slightly higher than that of the predator population. In order to put the game in the context of a true co-evolutionary relationship, I introduce the behavior of predators and prey through verbal descriptions or videos. My most commonly used example is about the cheetah and the gazelle, where the cheetah tracks the Gazelle until it is close enough to one and starts chasing. Since then, it has become 1 feet games for gazelles and cheetahs, with more winners ( And the usual maneuver)the loser. I then instruct the class that its envelope contains a set of numbered cards representing the Gazelle or cheetah group that students follow when playing games: game rule 1. Each team is a group of predators or prey, getting 16 character cards, each with a running speed. So each card represents a different individual in the population. See the material section for the value of the card. 2. Each team calculates the average running speed of the population based on the digital secret on the card, shuffle, and then place the deck face down between its team members and the opponent team members. 3. At the beginning of the game, each team will have a card facing up at the same time, representing the interaction between the predator and the prey. 4. The result of the interaction depends on the speed of the predator and prey. If a predator is faster than a prey ( Everything else is equal) The predator catches the prey and eats it; Otherwise, the prey will overtake the predator and run away, while the predator will starve to death. ( In nature, the interaction of predators/prey is not that simple, as predators may not starve to death for failing to capture a particular prey. ) If a draw occurs, a coin toss will be used to determine the result. 5. At the end of the encounter, the winner ( The team with higher point values displayed on the card) Keep the winning face A new pile; The loser faces the cards down in a separate new pile. 6. The game continues and each team presents a card at a time, the winner of the predator -- Prey interaction puts its winning card on the face Until all 16 interactions are decided, up pile and the loser put the cards in a pile of their own. 7. Each team then calculates the average speed of the survivors (face-up cards). 8. Based on the average speed of the last round of survivors, additional simulations may be performed after the formation of a new group. To do this, each team multiplied the average speed of the survivors by 16 and then selected 16 cards with a value of 16 times the average speed of the survivors. These 16 cards become the next generation, and the game continues in steps 3 to 7. Post- After the game, I asked the group about the previous content. and- After the average speed of their population, I show it to everyone. Table 2 shows examples of 12 simulation results generated by my two classes. It should be noted that the average speed of most populations has increased, and in general the relative change between the predator population and its prey is small. Then I asked the group to discuss the following: 1. What happens to the average speed of predators and prey in your game? In all games? ( Due to the randomness of the encounter in the game, not all the people will increase; However, most people will have the deck because of the \"stacking. If some do not, I ask for an explanation, hoping to hear about the impact of the opportunity. )2. Use the assumption of natural selection theory to explain your results if the card represents a real crowd that behaves like a card in the game. Here I am looking for them to apply the following assumptions: * individuals are different in the population ( In the simulation, they have different speeds. e. , Different speeds are different phenotypes) * There is a survival struggle between different phenotypes, resulting in * differential survival ( And breeding) These phenotypes. 3. If the population at the end of the game represents the remastered, what about the next generation compared to the generation at the beginning of the game? Why? ( They should point out that if the speed is inherited, the average speed of the population should increase because survivors are usually faster individuals and become producers. )4. In order to strengthen the premise that the average speed of the population is changing, I ask the group to consider whether the speed of the individual will increase. If they only think in the context of the simulation, they should realize that the numbers on the cards that represent the speed of the individual cannot be changed. However, as slower individuals disappear from the crowd, their average speed increases. So is the role of natural selection. Due to unequal survival and reproduction of different genotypes, a population changes over time. If they consider increasing the speed of the body through physical training, they may say that the speed will increase. This leads to a discussion of whether this acquisition is genetic or not, as well as consideration for the inheritance of acquired features. If you play more than one round, let the students draw the average speed of the predator and prey as a function of the number of generations. Then ask the whole class to describe what the chart depicts. They should see some parallel growth in the speed of both groups, which is the assumption of the Red Queen (Van Valen, 1973) Real interaction groups can be predicted. A round of simulation, and then discussion, can be in 50- Minutes of class If done in grade 9 12. The activities will meet the following content standards of the National Research Committee (1996): \"A. Understanding of scientific inquiry \"( Specifically, explain the observation results with theory)and \"C. Understanding of biological evolution\" Appendix. Provide articles that help students understand the activities of evolution. Easton, C. M. (1997). Laboratory of population genetics simulation practice card. American Biology Teacher, 59 years old (8), 518-521. Fifield, S. & Fall, B. (1992). A hands- A simulation of natural selection in an imaginary organism. American Biology Teacher, 54 years old (4), 230-235. Fiero, B. & Mackie, S. (1997). Laboratory of natural selection of Environmental Biology. American Biology Teacher, 59 years old (6), 354-359. Goff, C. (1995). Survival of the fittest. Science teacher, 62 (6), 24-25. Hazard, E. B. (1998). Teaching in intermediate form. American Biology Teacher, 60 years old (5), 359-361. Heim, W. G. (2002). Natural choice when playing cards. American Biology Teacher, 64 years old (4), 276-278. Hinds, D. S. & Amundson, J. C. (1975). Show natural selection. American Biology Teacher, 37 years old (1), 47-48. Knapp, P. A. & Thompson, J. M. (1994). Geography course: simulation of evolution with playing cards Journal of Geography, 93 (2), 96-100. Kuhn, D. J. (1969). Simulation game about natural selection. Science teacher, 36 years old (1), 68. Lauer, T. E. (2000). Jelly Belly[R] Jelly beans and evolutionary principles in the classroom: the stomach that attracts students. American Biology Teacher, 62 years old (1), 42-45. Leonard, W. H. & Edmondson, E. (2003). Teaching Evolution through founder effect: a standard-based activity. American Biology Teacher, 657), 538-541. McCarty, R. V. & Marek, E. A. (1997). Natural selection in a petri dish. Science teacher, 64 (8), 36-39. Maret, T. J. & Rissing, S. W. (1998). Explore genetic drift and natural selection through simulation activities. American Biology Teacher, 60 years old (9), 681-683. Nolan, M. J. & Ostrovsky, D. S. (1996). The natural choice of a Gambler American Biology Teacher, 58 (5), 300-301. Silverman, J. (1998). Study the genetics of behavior and evolution through adaptation and natural selection. American Biology Teacher, 60 years old (5), 356-358. Tashiro, M. E. (1984). Natural selection game. American Biology Teacher, 46 years old (1), 52-53. Vogt, K. D. (2002). Demonstrate exercises on adaptive landscape concepts & Simulation of Complex Systems. American Biology Teacher, 64 years old (8), 605-607. Welch, L. A. (1993). A micro-evolutionary model in action. American Biology Teacher, 55 years old (6), 362-365. Young, H. J. & Young, T. P. (2003). A hands- Demonstrate the practice of evolution through natural selection and genetic drift. American Biology Teacher, 656), 444-448. Two reviewers suggested significant improvements to the changes in this article. Special thanks to the commenters who suggested adding game rounds. Reference Brumby, M. (1979). Learn about the concept of natural selection. Journal of Biological Education, 13 (2), 119-122. Darwin, C. (1890). About the Origin of Species that preserve favorable races through natural selection or in the struggle for life, Edition 6. New York, NY: D. Appleton CompanyDawkins, R. (1996). Blind Watchmaker New York, NY: W. W. Norton CompanyDemastes, S. S. , Settlage, Jr. , J. & Good, R. (1995). The student\'s concept of natural selection and its role in evolution: a case of replication and comparison. Journal of Scientific teaching Research, 32 (5), 535-550. Dobzhansky, T. (1973). Nothing in Biology Makes Sense Except evolution. American Biology Teacher, 35 years old (3), 125-129. Fahrenwald, C. R. (1999). Biology teacher\'s acceptance and understanding of the nature of evolution and science. Ph. D. PhD thesis, University of South DakotaFerrari, M. & Chi, M. T. H. (1998). The nature of the naive interpretation of natural selection. International Journal of Science Education, 20 (10), 1231-1256. McComas, W. F. (1991). Analysis of teaching resources in evolutionary biology laboratory. American Biology Teacher, 53 years old (4), 205-209. National Research Council(1996). National standards for science education. Washington: National Academy of Sciences Press. Stebbins, R. C. & Allen, B. (1975). Simulated Evolution American Biology Teacher, 37 years old (4), 206-211. Tatina, R. (1989). Biology teachers and teaching of evolution and creation theory in Nada Kota high school. American Biology Teacher, 51 (5), 275-280. Van Valen, L. (1973). New laws of evolution 1, 1-evolutionary theory30. Zimmerman, M. (1987). The evolution- Creative controversy: Opinions of biology teachers at Ohio high school. Journal of Ohio Science, 87 (4), 115-125. Robert tatina is a professor of biology at the University of Wesleyan, Dakota, Mitchell, SD 57301; e- Mail: rotatina @ dwuedu.