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AlcoZone: An Adaptive Hypermedia based Personalized Alcohol Education

In our knowledge based economy, demand for better and effective learning has led to innovative instructional technologies. However, the one-size-fit-all approach taken by many e-Learning systems is not adequate to the different requirements of people who have different goals, preferences, and previous knowledge about a subject. Many e-Learning systems have approached this problem with personalized and customized content. However, many of these systems are closely tied to one particular subject that they are trying to teach; authoring of courses on different subjects using the same framework is a difficult process. Adaptive Hypermedia is an approach in which content presentation and navigation assistance is personalized depending on the requirements of the user. The user requirements are represented using a user model, while the content is represented using a content model. By using a set of algorithms, an Adaptive Hypermedia based system is able to select the most appropriate content to be presented, as the user interacts with the system. The objective of AlcoZone is to educate all of the 5,000 freshman students of Virginia Tech about alcohol education using Adaptive Hypermedia technology, as part of the mandatory university requirement. The course presents different content to different students based on their drinking pattern. AlcoZone integrates Curriculum Sequencing, Multimedia and Interactivity, Alternate Content Explanation, and Navigational Assistance to make the course interesting for students. This research investigates the design & implementation of AlcoZone and its Adaptive Hypermedia based reusable framework for course creation and delivery. / Master of Science

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/32913
Date14 June 2006
CreatorsBhosale, Devdutta
ContributorsElectrical and Computer Engineering, Shukla, Sandeep K., Martin, Thomas L., Fox, Edward A.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/
RelationDevdutta_Thesisv2.pdf

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