The design of guided learner-adaptable scaffolding in interactive learning environments
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Adaptive interfaces and agents
The human-computer interaction handbook
What role can adaptive support play in an adaptable system?
Proceedings of the 9th international conference on Intelligent user interfaces
The Sandbox for analysis: concepts and methods
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
AutoTutor: A simulation of a human tutor
Cognitive Systems Research
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Scaffolding techniques allow human instructors to support novice learners in critical early stages, and to remove that support as expertise grows. This paper describes nAble, an adaptive scaffolding agent designed to guide new users through the use of an analytic software tool in the ‘nSpace Sandbox’ for visual sense-making. nAble adapts the interface and instructional content based on user expertise, learning style and subtask. Bayesian Networks and Hidden Markov task models provide the agent reasoning engine. An experiment was conducted in which participants were provided with one of: an adaptive scaffold, an indexed help file or a human guide. Users of the adaptive scaffold outperformed users of the indexed help and more quickly converged with the performance of users with the human guide.