A Serious Game For Better Understanding of Behaviour Differences Between Children

1. Supervised by Dr. Ammar Joukhadar Dr.Noor Shaker Eng. Mohammed Shaker Designed, Implemented and Tested by Rawan Al-Omari Walaa Baghdadi Zeina Al-Helwani F.I.T.E of Damascus, Syria – AI Department 2014

2. Content • Motivation and Work scope • This Study • Psychology Study • The Game • Data Collection • Data Analysis • Result Analysis • Implementation Tools • Future Perspectives • Demo

3. IntroductionMotivation and Work Scope

4. We should put children in an environment where they want to learn and where we can naturally discover their true passions The Element, Ken Robinson

5. 18-35 39% >36 31% Gamer Age Hours Spent Daily 7 5 3 30% <18 Hours Spent Playing (By Age Segment)

6. A Survey Discuss it Indirect Influence Ignore it 41% 52% 6% If you noticed a problem in your child behavior, what do you do?

7. A Survey In case you want a product to inspect and alter your child behavior, what would it be? Survey Intelligent robot (a bot) Game 6% 11% 83%

9. O n a M i s s i o n

10. Similar Studies Conflict resolution Village Game Anti-bullying FearNot Game

12. Psychologists and Parents Opinions Assessments Reference Measuring violence-related attitudes, behaviors and Influences among youths 170 assessments Social Fantasy Conduct Problems

13. Questionnaire to Game Scenario Question Answer

14. Questionnaire to Game Scenario Question Game Scenario

15. Questionnaire to Game Scenario “Do you help other kids in need?”

17. The Game Design (Artist) Mechanism (Programmer)

18. Game Environments Park School Kitchen

19. Player Interaction

20. Player Goal (2 Models) With (green)positive/ (red)negative score Goal: solve all cases Goal: solve all cases Without score

22. System Diagram Game Player

23. System Diagram Game Player Data Collection

24. System Diagram Game Player Data Collection Statistical Features

25. Analysis Diagram Game Player Data Collection Statistical Features Feature Selection

26. System Diagram Game Player Data Collection Statistical Features Feature Selection Models (Decision Trees, Clustering)

27. Khubaraa Al-Mustakbal Institute Data Collection 8-12 years old children 100 players [50 males, 50 females]

28. Recorded Log (32 features, every 5 seconds) • General • Inventory items • Gameplay areas • Cases in all areas • Wrong tools usage • Time • Current time • Game Time in a specific area • Area-specific • Visible cases (to the player) in current area • Solved cases • Case-specific • Solved or not • Player reaction to the case (the player’s answer) • Wrong items used on the case And more.

29. Recorded Features (37 overall) • Pre-game questionnaire • Name • Age • Gender • Daily playing hours • #Brothers • #Sisters • Post-game questionnaire • Favorite place • Were there missing tools? • Did you find the tools sufficient? • Challenge% • Area-specific features • Order of solved cases in the area • Game Time during the area • Game Time to solve the case • #Revisited • #Used items to solve each case • #Wrong items selected • Game-specific features • Order of solved cases • Answers of solved cases • Game Time during the game

31. Eight-Model Comparison

34. Feature Selection Data Analysis Decision Tree Data Clustering

35. Conduct Problems Selected Features With score • Playing Hours • Game Time • Social Fantasy Score • #Wrong Items Case1 • #Revisited2 • TT Solve3 • TT Solve9 • #Revisited10 • Park3 • School2 • School3 Without score • Playing Hours • Social Fantasy Score • #Revisited2 • TT Solve5 • #Wrong Items Case7 • #Revisited9 • TT Solve10 • #Revisited10 • Kitchen2 • Best-First Feature Selection (BFS) on 8 Models

36. Decision Tree (Conduct Problems) Males & Females With/ Without Score Without Score With Score

37. Clustering (Conduct Problems) Males & Females With Score

38. (Males & Females Without Score) Model - Microsoft Clustering Clustering (Conduct Problems) Males & Females Without Score

39. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (3 child) WrongItemsCase1=0 High School score Direct game playing (no revisited) TT Solve9, Revisited10=0 School3 1/3 >= Social Fantasy Avg Playing Hours Park3 TT Solve3 School2 No WrongItemsCase1 TT Solve9 Revisited10=0 Avg<=Game Time TT Solve3 Revisited2 1/3 <= Social Fantasy Park3 School3 Avg<=Playing Hours Revisited10=0 WrongItemsCase1=0 School2 TT Solve3 Park3 Game Time Avg<=Playing Hours 1/3 <= Social Fantasy Repeated Revisited2 School3 TT Solve9 School2 TT Solve3 WrongItemsCase1=0 Max Playing Hours Avg <= Game Time TT Solve9 0<=Social Fantasy Revisited10=0 Park3 Avg <= Revisited2 Revisited10=0 Mid Social Fantasy Park3 TT Solve3=0 School2 Max Game Time 1 <= Revisited2 LowTT Solve9 WrongItemsCase1=0 Low Playing Hours School3 Males & Females With Score

40. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (3 child) WrongItemsCase1=0 High School score Direct game playing (no revisited) TT Solve9, Revisited10=0 School3 1/3 >= Social Fantasy Avg Playing Hours Park3 TT Solve3 School2 No WrongItemsCase1 TT Solve9 Revisited10=0 Avg<=Game Time TT Solve3 Revisited2 1/3 <= Social Fantasy Park3 School3 Avg<=Playing Hours Revisited10=0 WrongItemsCase1=0 School2 TT Solve3 Park3 Game Time Avg<=Playing Hours 1/3 <= Social Fantasy Repeated Revisited2 School3 TT Solve9 School2 TT Solve3 WrongItemsCase1=0 Max Playing Hours Avg <= Game Time TT Solve9 0<=Social Fantasy Revisited10=0 Park3 Avg <= Revisited2 Revisited10=0 Mid Social Fantasy Park3 TT Solve3=0 School2 Max Game Time 1 <= Revisited2 LowTT Solve9 WrongItemsCase1=0 Low Playing Hours School3 Males & Females With Score

41. Clustering (Conduct Problems) Males & Females Without Score Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (4 child) Revisited2 =0 , Kitchen2 Avg >= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 High Solve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TT Solve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg <= Playing Hours LowTT Solve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTT Solve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTT Solve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTT Solve10 Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (3 child) WrongItemsCase1=0 High School score Direct game playing (no revisited) TT Solve9, Revisited10=0 School3 1/3 >= Social Fantasy Avg Playing Hours Park3 TT Solve3 School2 No WrongItemsCase1 TT Solve9 Revisited10=0 Avg<=Game Time TT Solve3 Revisited2 1/3 <= Social Fantasy Park3 School3 Avg<=Playing Hours Revisited10=0 WrongItemsCase1=0 School2 TT Solve3 Park3 Game Time Avg<=Playing Hours 1/3 <= Social Fantasy Repeated Revisited2 School3 TT Solve9 School2 TT Solve3 WrongItemsCase1=0 Max Playing Hours Avg <= Game Time TT Solve9 0<=Social Fantasy Revisited10=0 Park3 Avg <= Revisited2 Revisited10=0 Mid Social Fantasy Park3 TT Solve3=0 School2 Max Game Time 1 <= Revisited2 LowTT Solve9 WrongItemsCase1=0 Low Playing Hours School3 Males & Females With Score

42. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (3 child) WrongItemsCase1=0 High School score Direct game playing (no revisited) TT Solve9, Revisited10=0 School3 1/3 >= Social Fantasy Avg Playing Hours Park3 TT Solve3 School2 No WrongItemsCase1 TT Solve9 Revisited10=0 Avg<=Game Time TT Solve3 Revisited2 1/3 <= Social Fantasy Park3 School3 Avg<=Playing Hours Revisited10=0 WrongItemsCase1=0 School2 TT Solve3 Park3 Game Time Avg<=Playing Hours 1/3 <= Social Fantasy Repeated Revisited2 School3 TT Solve9 School2 TT Solve3 WrongItemsCase1=0 Max Playing Hours Avg <= Game Time TT Solve9 0<=Social Fantasy Revisited10=0 Park3 Avg <= Revisited2 Revisited10=0 Mid Social Fantasy Park3 TT Solve3=0 School2 Max Game Time 1 <= Revisited2 LowTT Solve9 WrongItemsCase1=0 Low Playing Hours School3 Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8 child) Cluster5 (4 child) Revisited2 =0 , Kitchen2 Avg >= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 High Solve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TT Solve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg <= Playing Hours LowTT Solve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTT Solve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTT Solve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTT Solve10 Males & Females Without Score Males & Females With Score

47. Correlations FemaleMale

48. Social Fantasy (without score) 1.2x FemaleMale

49. Social Fantasy (with score) 1.4x FemaleMale

50. Females, 3D Histogram Without score With score

51. Males, 3D Histogram Without score With score

52. T-test (Females vs. Males, Social Fantasy, With Score) Variable 1 Variable 2 Mean 0.48 0.688 Variance 0.077 0.058 Observations 25 25 Hypothesized Mean Difference 0 df 47 t Stat -2.826 P(T<=t) one-tail 0.003 t Critical one-tail 1.677 P(T<=t) two-tail 0.006 t Critical two-tail 2.011 0.006 < 0.05 We reject the Null hypothesis

53. T-test Social Fantasy Females vs. Males 0.006 < 0.05 Females vs. Males 0.074 > 0.05 Conduct Problems Females vs. Males 0.002 < 0.05 Females vs. Males 0.100 > 0.05

55. Unity3D Game Engine, scripting with C# Implementation Tools WEKA, Machine Learning Software Microsoft Business Intelligence Suite Matlab for Analysis

57. Future Perspectives Personalizing the game content for each player, maximizing his/her social fantasy and conduct problems abilities. Direct the player to change his/her behavior by adding different interaction and influence techniques to the game. Comparing different model for capturing the behavior (recording facial expressions, heart beats, etc.)

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