The visual knowledge builder: a second generation spatial hypertext
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
Introduction to Digital Logic Design
Introduction to Digital Logic Design
Machine Learning
Machine Learning
Automatic Ontology-Based Knowledge Extraction from Web Documents
IEEE Intelligent Systems
Finding the story: broader applicability of semantics and discourse for hypermedia generation
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Template-based authoring of educational artifacts
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
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Inquiry learning involves the learner acquiring new concepts and skills by means of carrying out an investigation. Some previous studies have looked into how these learning activities can be carried out on source materials, such as web documents, and the provision of appropriate scaffolding to guide the learning process. Here we consider how intelligent support can be provided to guide the learner in analysing source materials and building knowledge from their interpretation. An important feature of our case study is that the source materials are images, potentially having greater variation in how they are interpreted and therefore increasing the need for intelligent support. Intelligent support provided by our system can identify patterns and inconsistencies in the learner's interpretation and knowledge building, and offer recommendations based on comparison with a reference model. The recommendations derived from a reference model aim to guide the learner in reviewing and revising their interpretation of the images and the implications of these for their inferences, rather than directly providing a “right” or “wrong” evaluation of their answer.