Electronic
Teaching involves computational systems that communicate and cooperate
with learners at many levels. These systems might use the World Wide
Web or CD/DVD-ROM and asynchronous learning environments to provide lectures
outside the classroom. They might provide customized responses and on-demand
advice through intelligent interfaces, inference mechanisms and cognitive
models of the learner. Much of the machine teaching research in the department
is multi-disciplinary, with strong ties to research in cognitive science,
education, engineering, and to other computer science researchers in
artificial intelligence, networking, machine learning, information retrieval
and multimedia. Target applications include undergraduate and K-12 curricula,
as well as industrial and medical training. Dozens of systems and courses
have been deployed and evaluated, with tens of thousands of users across
dozens of universities.
Advanced Computer
Networking Research Group Research in the Computer Networking Research Group
focuses on communication protocols (particularly for multimedia servers,
live multimedia, and multicast), quality of service issues including
call admission, and performance modeling.
Center for Knowledge Communication The Center for Knowledge Communication (CKC) investigates
knowledge-based educational systems, integrating theoretical principles
into research systems for empirical evaluation and theoretical analysis.
RIPPLES The Research in Presentation Production for Learning Electronically
(RIPPLES) project is investigating how to most effectively use the
World Wide Web and CD/DVD-ROM to deliver lectures and course materials
outside of the classroom. Its focus is on asynchronous learning environments
in which students proceed at their own pace and are not assumed to
be accessing the same material at the same time. Students can access
lectures as digital audio or video, synchronized with slides, overheads
or other materials.
Electronic
Teaching involves computational systems that communicate and cooperate
with learners at many levels. These systems might use the World Wide
Web or CD/DVD-ROM and asynchronous learning environments to provide lectures
outside the classroom. They might provide customized responses and on-demand
advice through intelligent interfaces, inference mechanisms and cognitive
models of the learner. Much of the machine teaching research in the department
is multi-disciplinary, with strong ties to research in cognitive science,
education, engineering, and to other computer science researchers in
artificial intelligence, networking, machine learning, information retrieval
and multimedia. Target applications include undergraduate and K-12 curricula,
as well as industrial and medical training. Dozens of systems and courses
have been deployed and evaluated, with tens of thousands of users across
dozens of universities.