A Liquid Narrative Group System
FixIt is a game designed especially for research on the effectiveness·of the Annie system to guide students through exploratory learning·environments. ·Because Annie specializes in task-based learning, it is·optimally suited for domains where the key learning challenges·involve processes that involve the composition of a sequence·of causally related actions. ·FixIt uses the Unreal Tournament 3·engine to create a 3-D visual representation of a computer·system to teach concepts in computer security.
The game features four progressively more difficult missions that·require the student/player to identify and remove increasingly complex·forms of computer malware. The learning goal is for the user·to gain a deep understanding of the mechanism by which·computers can become infected and the procedures security·software uses to disinfect operating systems.
Team members
- R. Michael Young (faculty contact)
- Jim Thomas (lead developer)
Fixit publications
Thomas, James and Young, R. Michael, Annie: Automated Generation of Adaptive Learner Guidance For Fun Serious Games, to appear in the IEEE Transactions on Learning Technologies special issue on Learning in Games. [PDF]
Thomas, James and Young, R. Michael, Annie: A Tutor that Works in Digital Games, to appear in the Proceedings of the Tenth International Conference on Intelligent Tutoring Systems, Pittsburgh, PA, 2010. [PDF available soon]
Thomas, James M. and Young, R. Michael. Guiding discovery learning with an extensible representation of actions in digital games. Technical Report DGRC-2009-01, Digital Games Research Center, North Carolina State University, Raleigh, North Carolina, 2009.
Thomas, James and Young, R. Michael, Using Task-Based Modeling to Generate Scaffolding in Narrative-Guided Exploratory Learning Environments, in the Proceedings of the International Conference on Artificial Intelligence and Education (AIED 09), Brighton, UK, July, 2009. [PDF]
Thomas, James and Young, R. Michael, Dynamic Guidance in Digital Games: Using an Extensible Plan-Based Representation of Exploratory Games to Model Student Knowledge and Guide Discovery Learning, in the Working Notes of the Intelligent Educational Games Workshop at the International Conference on Artificial Intelligence and Education (AIED 09), Brighton, UK, July, 2009. [PDF]
Thomas, Jim and Young, R. Michael, A Domain-Independent Framework to Automate Scaffolding of Task-Based Learning in Digital Games, in the Proceedings of the International Conference on the Foundations of Digital Games (ICFDG 09), Orlando, FL, April 26 – 30, 2009. [PDF]
Fixit video or image files
fixit sponsors
The US National Science Foundation, through CAREER Award #0092586 and Gradaute Research Fellowship Award #05xxxxx.