Student Modeling in an Active Learning Environment
using Bayesian Networks
Learning environments that allow for active (constructivist) learning
lead to different adaptation requirements than environments based on more
conventional teaching strategies. We discuss our approach of building adaptive
hyperbooks (adaptive extendible information resources on the internet).
The adaptation techniques used in our hyperbooks are based on a goal-driven
approach for selecting projects and for generating and presenting prerequisite
knowledge necessary for a student project. The user model underlying the
hyperbook is a kind of overlay model using a Bayesian Network for estimating
user knowledge. We propose a project selection algorithm based on user
goals and previous knowledge and a constructive trail mechanism that generates
guided tours through the hyperbook containing all prerequisites needed
by a particular user to perform a specific project.
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