Abstract
M.Ing.
Virtual classrooms and online-learning are growing in popularity, but there are still some
factors limiting the potential. Limited bandwidth for audio and video, the resultant
transmission quality and limited feedback during virtual classroom sessions are some of the
problems that need to be addressed. This thesis presents information on the design and
implementation of various components of a virtual classroom system for researching methods
of student feedback with a focus on bandwidth conservation. A facial feature technique is
implemented and used within the system to determine the viability of using facial feature
extraction to provide and prioritise feedback from students to teacher while conserving
bandwidth. This allows a teacher to estimate the comprehension level of the class and
individual students based on student images. A server determines which student terminal
transmits its images to the teacher using data obtained from the facial feature extraction
process. Feedback is improved as teachers adapt to class circumstances using experience
gained in traditional classrooms. Feedback is also less reliant on intentional student
participation. New page-turner, page suggestion and class activity components are
presented as possible methods for improving student feedback. In particular, the effect of
virtual classroom system parameters on feedback delays and bandwidth usage is
investigated. In general, delays are increased as bandwidth requirements decrease. The
system shows promise for future use in research on facial feature extraction, student
feedback and bandwidth conservation in virtual classrooms.