Paper m schembri_17-11

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Paper m schembri_17-11

  1. 1. Di Ferdinando, M. Schembri, M.L. Nigrelli, O. Miglino Institute of Cognitive Sciences and Technologies C.N.R GACET’11 Rome, Italy 17-18 november 2011
  2. 2. Outline The Learn To Lead project: design of a game for training leadership skills Introduction to the Learn to Lead Game Serious game desing: doing it the right way How agent-based modeling helped ? Conclusion
  3. 3. Learn to lead project EU project (Leonardo da Vinci programme) goal of Learn to Lead: design, implement, and test a novel, online approach to training in team leadership
  4. 4. Why the Full Range Leadership theory Knowledge structured into a logical system Easly “translatable” into behavioral patterns Empirical evidence Leadership style Assessment tools available (MLQ questionnaire)
  5. 5. Introduction to the Game
  6. 6. Serious game desing: doing it the right way When setting out to build an educational game there is very little guidance on how to ensure that the game has the desired effect on learning ….but entertainment games are excellent at motivating people to learn skills that are necessary to advance in the game Learning should be intrinsic to the game play Make the mechanics of the game mapping directly to the learning outcomes (Habgood, 2007)
  7. 7. Example If a game is intended to teach multiplication, the core mechanic of the game should involve the players engaging in multiplication
  8. 8. How agent-based modeling helped
  9. 9. Conclusion Agent-based simulation helps incorporating complex knowledge into educatioinal games in a way that makes learning intrisic to the gameplay The game mechanics and learning programme become much more difficult to design Acknowledgements This work was carried out as part of the “Leonardo” project “Learn to Lead” Funded by the EU Lifelong Learning Program

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