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Weebee on a Mission: A Serious Game for Better Understanding the Behavior Differences Between Children

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Weebee on a Mission: A Serious Game for Better Understanding the Behavior Differences Between Children. Designed and Implemented by: Rawan Al-Omari, Walaa Baghdadi and Zeina Al-Helwani. Supervised by me (Mohammad Shaker), Dr. Noor Shaker and Dr. Mohamed Abu-Zleikha.

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Weebee on a Mission: A Serious Game for Better Understanding the Behavior Differences Between Children

  1. 1. Supervised by Dr. Noor ShakerEng. Mohammad Shaker Designed, Implemented and Tested by RawanAl-OmariWalaaBaghdadiZeinaAl-Helwani F.I.T.E of Damascus, Syria –AI Department 2014
  2. 2. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  3. 3. Introduction Motivation and Work Scope
  4. 4. We should put children in an environment where they want to learnand where we can naturally discovertheir true passions The Element, Ken Robinson
  5. 5. 18-35 39% >36 31% Gamer Age Hours Spent Daily 7 5 3 30% <18 Hours Spent Playing (By Age Segment)
  6. 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. 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%
  8. 8. On a Mission
  9. 9. Similar Studies Conflict resolution Village Game Anti-bullying FearNotGame
  10. 10. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  11. 11. Psychologists and Parents Opinions Assessments Reference Measuring violence-related attitudes, behaviors and Influences among youths 170 assessments Social Fantasy Conduct Problems
  12. 12. Questionnaire to Game Scenario Question Answer
  13. 13. Questionnaire to Game Scenario Question Game Scenario
  14. 14. Questionnaire to Game Scenario “Do you help other kids in need?”
  15. 15. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  16. 16. The Game Design (Artist) Mechanism (Programmer)
  17. 17. Game Environments Park School Kitchen
  18. 18. Player Interaction
  19. 19. Player Goal (2 Models) With (green)positive/ (red)negative score Goal: solve all cases Goal: solve all cases Without score
  20. 20. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  21. 21. System Diagram Game Player
  22. 22. System Diagram Game Player Data Collection
  23. 23. System Diagram Game Player Data Collection Statistical Features
  24. 24. System Diagram Game Player Data Collection Statistical Features Feature Selection
  25. 25. System Diagram Game Player Data Collection Statistical Features Feature Selection Models (Decision Trees, Clustering)
  26. 26. KhubaraaAl-MustakbalInstitute Data Collection 8-12 years old children 100 players [50 males, 50 females]
  27. 27. 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.
  28. 28. 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
  29. 29. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  30. 30. Eight-Model Comparison
  31. 31. Eight-Model Comparison
  32. 32. Eight-Model Comparison
  33. 33. Feature Selection Data Analysis Decision Tree Data Clustering
  34. 34. 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
  35. 35. Decision Tree(Conduct Problems) Males & Females With/ Without Score Without Score With Score
  36. 36. Clustering (Conduct Problems) Males & Females With Score
  37. 37. (Males & Females Without Score) Model -Microsoft Clustering Clustering (Conduct Problems) Males & Females Without Score
  38. 38. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Males & Females With Score
  39. 39. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Males & Females With Score
  40. 40. Clustering (Conduct Problems) Males & Females Without Score Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(4 child) Revisited2 =0 , Kitchen2 Avg>= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 HighSolve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TTSolve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg<= Playing Hours LowTTSolve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTTSolve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTTSolve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTTSolve10 Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Males & Females With Score
  41. 41. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(4 child) Revisited2 =0 , Kitchen2 Avg>= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 HighSolve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TTSolve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg<= Playing Hours LowTTSolve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTTSolve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTTSolve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTTSolve10 Males & Females Without Score Males & Females With Score
  42. 42. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(4 child) Revisited2 =0 , Kitchen2 Avg>= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 HighSolve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TTSolve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg<= Playing Hours LowTTSolve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTTSolve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTTSolve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTTSolve10 Males & Females Without Score Males & Females With Score
  43. 43. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(4 child) Revisited2 =0 , Kitchen2 Avg>= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 HighSolve10 1/3<=Social Fantasy WrongItemsCase7=0 Revisited10=0 Mid Social Fantasy Kitchen2 Revisited2=0 Revisited9=0 Avg>=Playing Hours Avg>=TTSolve10 Avg>=TT Solve5 1/3 <=TT Solve10 Kitchen2 Revisited2=0 Avg<= Playing Hours LowTTSolve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTTSolve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTTSolve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTTSolve10 Males & Females Without Score Males & Females With Score
  44. 44. Clustering (Conduct Problems) Cluster1 (22 child) Cluster2 (11 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(3 child) WrongItemsCase1=0 High Schoolscore Direct game playing(no revisited) TT Solve9, Revisited10=0 School3 1/3>= Social Fantasy AvgPlaying 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 LowTTSolve9 WrongItemsCase1=0 LowPlaying Hours School3 Cluster1 (17 child) Cluster2 (10 child) Cluster3 (8 child) Cluster4 (8child) Cluster5(4 child) Revisited2 =0 , Kitchen2 Avg>= Solve5 Max Playing Hours WrongItemsCase7=0 Revisited9=0 Revisited10=0 HighSolve10 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 LowTTSolve5 Revisited9=0 1/3>=Social Fantasy Revisited10=0 WrongItemsCase7=0 WrongItemsCase7=0 , Revisited2=0 Kitchen2 LowTTSolve10 TT Solve5=0 Avg>=Playing Hours Revisited9=moreThan1 1/3>=Social Fantasy Revisited10=0 Revisited10=0 Revisited2=0 Revisited9=moreThan1 low<=Playing Hours LowTTSolve5 Kitchen2 1/3<=Social Fantasy WrongItemsCase7=0 LowTTSolve10 Males & Females Without Score Males & Females With Score
  45. 45. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  46. 46. Correlations Female Male
  47. 47. Social Fantasy (without score) 1.2x Female Male
  48. 48. Social Fantasy (with score) 1.4x Female Male
  49. 49. Females, 3D Histogram Without score With score
  50. 50. Males, 3D Histogram Without score With score
  51. 51. 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
  52. 52. T-test Social Fantasy Femalesvs. Males 0.006 < 0.05 Femalesvs. Males 0.074 > 0.05 Conduct Problems Femalesvs. Males 0.002< 0.05 Femalesvs. Males 0.100> 0.05
  53. 53. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  54. 54. Unity3D Game Engine, scripting with C# Implementation Tools WEKA, Machine Learning Software Microsoft Business Intelligence Suite Matlabfor Analysis
  55. 55. Content •Motivation and Work scope •This Study •Psychology Study •The Game •Data Collection •Data Analysis •Result Analysis •Implementation Tools •Future Perspectives •Demo
  56. 56. 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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