Although most learning occurs outside the classroom, existing research on AIWBES (adaptive and intelligent web-based educational systems - per Brusilovsky) focuses on the textbook or lecture metaphors. We are researching the use of the mentor/protege metaphor for design of AIWBES. Our prototype AIWBES is ACUT (the Adaptive Collaborative Unix Tutorial.)
ACUT is an online Unix meta-tutorial designed to help students understand Unix concepts. Unix is a necessary prerequisite to upper division or graduate study in computer science (CS). Because non-traditional CS students disproportionally lack Unix experience, ACUT is designed with the non-traditional student in mind.
Publications
see also AHAT lab publications
K. Hofmann, "Subsymbolic User Modeling in Adaptive Hypermedia," 12th International Conference on Artificial Intelligence in Education, 2005. (PDF)
R. Farzan, Adaptive Collaborative Unix meta-Tutorial, CSU East Bay Master's Thesis, 2003. (PDF)
R. Farzan, "Adaptive Collaborative Unix Meta-Tutorial for Computer Science Students", Proceedings of SIGCSE 2003. ( PDF, Poster Presentation)
Access
You can now register for ACUT online! Just complete the registration at http://acut.csueastbay.edu/register.