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Sergio Gutiérrez, Abelardo Pardo, Carlos Delgado Kloos Department of Telematic Engineering Carlos III University of Madrid, Spain gradient.it.uc3m.es. Personalized resource sequencing in digital libraries. Access at no cost. Before How do I have access to a resource? Now
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Sergio Gutiérrez, Abelardo Pardo, Carlos Delgado Kloos Department of Telematic Engineering Carlos III University of Madrid, Spain gradient.it.uc3m.es Personalized resource sequencing in digital libraries
Access at no cost Before How do I have access to a resource? Now How do I select the proper resource?
Consequences • Prepare learning material in a different manner • Re-search with different strategies • New tools • New methodologies
Effective filtering • “Searching” is no longer effective. • Additional filtering is required • User profiles need to be considered to improve effectiveness Adaptation!
Adaptation • Well known research area • Two strategies • Adapt the learning content • Adapt the sequence of resources offered to the learner
Capture relevant resource sequences • Resources are related. • Sequences of resources are captured. • Sequences are dynamically updated
Hierarchical transition graphs • Graphs capture relations between nodes. • Sequences are intuitively defined. • Difficult to handle a large number of nodes.
Graph Definition • Nodes represent resources • Edges represent a transition to another resource • Conditions “enable” the transitions
Conditions/Actions • Condition is stated in terms of any environment variable • If condition holds true, resource is visible • If resource is selected, actions are executed • Resources may use the environment
Hierarchical organization • Graphs with large number of nodes are not feasible • Hierarchy is already present in resources
Example of hierarchy • Transition structures defined between closely related resources. • Transitions among related topics
How is the graph created? • Initial structure derived from relevance • Built-in adaptive structures • Dynamic changes derived from observations
Capturing relevance • Derive graph from high level content organization • Include possibly related items
Built-in adaptive structures • If learner visits more than n resources, offer deeper content • If learner barely uses a resource, force alternatives
Dynamic changes in the graph • Observe behavior of a set of learners. • Give higher priority to “most useful” sequences. • Learner valuation of resources. • Ant colony optimization strategies.
Conclusions • Need “intelligent” resource management • Adapt sequences • Hierarchical graphs to capture sequences • Static and dynamic graph update