A Conceptual Design of MultiAgent based Personalized Quiz

A Conceptual Design of Multi-Agent based Personalized Quiz Game Martin Weng, Fuhua Lin, Timothy K. Shih, Maiga Chang, Ireti Fakinlede http: //kinshuk. athabascau. ca

Outline • • • Introduction Game and Assessment Multi-Agent based Quiz-Master Scenario Conclusion

Introduction • Motivation – Quiz-game is easy to develop – Quiz game has no restriction of specific subject – Multi-agent based system is flexible and saving resource • Objectives – Develop a framework to build personalized assessment game • Multi-agent based quiz game

Introduction • Contribution – Instructor • Realize student’s playing situation and experience – Student • Personalized assessment game – Similar level of competitor and subject – The sense of achievement • Tasks – The flow of personalized assessment game – The structure design of multi-agent based Quiz. MASter

Game and Assessment • • Game genre Assessment methods Educational game for assessment Multi-agent systems

Game and Assessment • Game genre – Action games – Adventure games – Fighting games – RPG – Simulations – Sports. games. – Strategy games.

Game and Assessment • Assessment methods – Single choice – Multiple choice – True and false – Inline Choice – Match – Short essay – Fill in. . blank. – Hot spot

Game and Assessment • Educational game for assessment – Quiz-MASter – Function Machine • Multi-agent systems – A system composed of multiple interacting intelligent agents – Agent-oriented system are reliable and secure – Flexible & Saving Resource

Multi-Agent based Quiz-Master

Multi-Agent based Quiz-Master • Host Agent – Ask player questions – Arrange matches (similar level) • Designated computer player (NPC) • Put human players together • User Agent – Distribute the appropriate user model – Ask and collect the information • Behaviour agent • Knowledge agent • Game agent – Send the information to host agent • Preference content type • Student level

Multi-Agent based Quiz-Master • Behaviour Agent – Detect the user information during the game • Response time • Answer that student selected in quiz • Test score • Game Agent – Game ranking – Game playing history – Mechanism of rewards and penalties in the game

Multi-Agent based Quiz-Master • Instructor Agent – Send request from host agent • Subject • Quiz difficulty • Content type • Knowledge Agent – Provide the user’s knowledge background • What subject, quiz difficulty have user learn? – Analyze knowledge background situation by user’s learning • Which subject has good test performance in the game ?

Multi-Agent based Quiz-Master • What personalized in Quiz-Master? – Similar level of NPC or human competitor – Subjects are necessary for user

Conclusion Summary • Flow of personalized assessment quiz game • Quiz-Master Adaptive multi-agent system – Framework of personalized Quiz-MASter assessment game Future Work • Personalized content type for quiz game • Develop a multi-player multi-agent based Quiz-Master Adaptive Learning Intelligent Agents 3 D Immersive

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