Machine-learning applications often suffer bottlenecks due to inefficiency in the human-machine interface. A novel architecture design has been developed to allow expert supervisors to collaborate and cooperate in real-time to alleviate the effects of the bottleneck. Replacing supervisors with students, this architecture also allows for supervised training and collaborative learning of students as well as machine learners. Our attempts to provide Web-based courses to distance learners have highlighted the need for more effective use of the medium for education and appropriate tools to provide the necessary richness of experience. We present our design and an example application to demonstrate how we address some of the shortfalls present in Web-based, distance education.

Item Type:	Research Book Chapter
Keywords:	web-based education, distance education, machine learning
Research Division:	Language, Communication and Culture
Research Group:	Communication and media studies
Research Field:	Communication technology and digital media studies
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in the information and computing sciences
UTAS Author:	Drew, S (Dr Steve Drew)
ID Code:	111941
Year Published:	2003
Deposited By:	Curriculum and Academic Development
Deposited On:	2016-10-17
Last Modified:	2016-11-03
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