Title :
Annie: Automated Generation of Adaptive Learner Guidance for Fun Serious Games
Author :
Thomas, James M. ; Young, R. Michael
Author_Institution :
Dept. of Comput. Sci., North Carolina State Univ., Raleigh, NC, USA
Abstract :
This paper describes some of the difficulties inherent in building intelligent educational games, specifically the challenge of integrating pedagogy with core game play. We introduce a plan-based knowledge representation that provides a novel framework for infusing the core mechanics of a game with pedagogical content. We describe, in detail, a system that leverages this framework to dynamically adapt a game to individual learners at runtime.
Keywords :
computer aided instruction; computer games; adaptive learner guidance; automated generation; fun serious games; intelligent educational games; pedagogy; plan-based knowledge representation; Adaptation model; Artificial intelligence; Computational modeling; Computer aided instruction; Games; Knowledge representation; Artificial intelligence; computer-managed instruction.; games; intelligent tutoring; plan generation;
Journal_Title :
Learning Technologies, IEEE Transactions on
DOI :
10.1109/TLT.2010.32