Unit 3: Game Design Culture and Play Part III of IV

1. Unit 3: Game Design Culture and PlayPart III of IV

2. Overview • The computer skills that you learn as a video game designer can apply to other electronic media as well. Acquiring the knowledge and basic skills behind game play and game culture will increase the technological competence, therefore making one uniquely prepared to perform at a high level in that area of the game design and development arena.

3. Game designers use basic elements when designing games. There are nine elements to understand. Formal game elements

4. Formal Element 1-4 Review • Players • Objectives • Procedures • Rules

5. Review of player patterns • Single player versus game • Multiple individual players versus game. • Player versus player • Unilateral Competition • Multilateral competition • Cooperative Play • Team Competition

6. Formal Elements 5: Probability • Probability is the branch of mathematics that deals with calculating the likelihood an event will occur and is usually expressed as a number between 1 and 0.

7. Formal Elements 5: Probability Game designers use an assortment of ways to provide players with a new game experience each time a game is played.

8. Randomness • Randomness is built into the mechanics of a game, and varies the number and location of obstacles that a player may encounter. For example, in card games it occurs when players “shuffle” the cards. • Randomness, probability, likelihood and chance are all terms that describe how variety and unexpected outcomes are created in games.

9. Non-electronic Game Probability • Board games use dice, spinners and sand timers to add a level of randomness and conflict to games.

10. Probability of an Event • P(A) = The number of Ways an Event can Occur The Total Number of Possible Outcomes

11. Electronic Game Probability • Randomness and chance are built into the software and programming of electronic games. • Electronic games are NOT limited to dice or spinners and therefore can mathematically create random outcomes using random number generators and algorithms.

12. Algorithm • To make a computer do anything you must write a computer program which tells the computer what to do step by step. • The computer then executes the program, following each step mathematically, to accomplish the end goal.

13. Algorithm • The algorithm is the basic technique used to get the job done. • The next four slides will provide different algorithm examples that you might give someone that is arriving at the airport and needs to know how to get to your house.

14. The Taxi Algorithm • Go to the taxi stand. • Get in a taxi. • Give the driver my address.

15. The Call-Me Algorithm • When your plane arrives, call my cell phone. • Meet me outside the baggage claim.

16. The Rent-a-Car Algorithm • Take the shuttle to the rental car place. • Rent a car. • Follow the directions to get to my house.

17. The Bus Algorithm • Outside baggage claim, catch bus number 70. • Transfer to bus 14 on Main Street. • Get off on Elm street. • Walk two blocks north to my house.

18. Explanation • All four of these algorithms accomplish exactly the same goal, but each algorithm does it in completely different way. Each algorithm also has a different cost and a different travel time. Taking a taxi, for example, is probably the fastest way, but also the most expensive. Taking the bus is definitely less expensive, but a whole lot slower. You choose the algorithm based on the circumstances.

19. Spinners • One way to add randomness to play is by having each player use a spinner to determine the number of spaces to move or which item to select. • By varying the size and number of sections of the spinner the game designer can control the possible outcomes.

20. Spinner Probability • Spinner probability can be predicted based on the area within the cirle each section occupies. • What happens if you construct a spinner with only one choice? (What would be the outcome?)

21. Empirical Probability • The empirical probability of an event is an “estimate” that the event will happen based on how often the event occurs after collecting data or running an experiment.

22. Formula for probability of event E • Let’s say that “E” is our occurrence. • How would we calculate the Formula for probability of event “E”?

23. Answer

24. Formula for Theoretical probability of event E • The Theoretical Probability of an event is the number of ways that an event can occur, divided by the total number of outcomes. • It is finding the probability of events that come from a sample space of known equally likely outcomes.

25. Formula for Theoretical probability of sample space S • So how would we calculate the probability of events that come from sample space S? • P (E) = n(E) = # of outcomes in E n(S) = total # of outcomes in S

26. Now You Try • Select the Scratch links near the bottom of your class page (useful links section) and try them. • These three games are designed to teach you about probability. • Next you will select the Probability Math link • http://classroom.jc-schools.net/basic/math-prob.html and select play the spinner, data analysis and probability, probability spinner, Adjustable spinner, dice activity, coin flipping page games. This will reinforce probability concept and its importance in game design and game play.