Welcome to the web site for
Advanced Technologies for Learning,
Semester 1, 2006
Ass Prof Judy Kay
Dr Kalina Yacef
This course covers relevant theories, concepts and methodologies from
Computer Science, Artificial Intelligence, Cognitive Science and
Education and applied in designing, building, and evaluating adaptive
computer-based eucational systems. The aim of these systems is to
provide the learner with ndividualised support in complex learning
reasoning tasks. They try to replicate, at a more affordable cost, one of
the documented benefits of excellent one to one human tutoring where
average performance can be increased by two standard deviations, taking
the average student to the 98-th percentile. They also aim to enrich
classical Education theories with the power and advantages brought by
information technology with (for instance environments using
simulations, video, hypermedia, supporting collaboration and so on).
Such intelligent support implies that quite complex underpinning
knowledge be modelled in the system: the pedagogical (teaching)
knowledge, the beliefs about the student's knowledge and preferences,
the knowledge about the domain taught, how to communicate efficiently
with the learner, as well as assisting teachers efficiently. This course
will present the major theories and studies useful for designing such
systems from both an IT and an Educational perspective.
This course will be jointly taught with the Faculty of Education, and
will be also available to postgraduate Education students. It will offer
the options to focus on an educational, technical or theoretical
perspective and will provide the opportunity to experience working with
students and lecturers with each of these focuses. "Providing a teacher
for every learner" is actually one of the 5 grand research challenges
articulated by the Computing Research Association last year. Students
will get the chance here to apply their skills and knowledge to this
applied research field.
This course is suitable for students with a background in either
Computer Science, Information systems or Education. Students will
approach relevant research being done in the University of Sydney.
There is no final examination: all assessment is based upon the
following tasks around one major project.
Major project, on a topic to be negotiated between
students and the lecturers. Note that students can work in groups of
2-3 on these projects but then each person would be expected to
identify a subset of the work for which they are primarily
Each project should make use of work and tools that have come
from existing research projects so that they give you an
opportunity to learn about an area of ATL and, at the same time,
develop your research skills, in literature searching,
conducting a very small scale investigation into the
technical soundness or validity of an approach
and writing up the results of an evaluation.
The final submission will require clear indications of
individual contributions and although the default is that all
members of a group get the same mark, we reserve the right to review
this as appropriate.
The work will be staged as follows, with partial assessment of
each stage, but the earlier parts being weighted less since they
are intended to be formative and provide an opportunity to
submit superior final work:
|3 ||5 ||
(3 pages - submitted
electronically + hardcopy)
|5-6 ||5 ||Paper review and critique (15 mins)
|6 ||10 ||Draft literature review (3 pages) -
required and submitted for feedback.
|6 ||0 ||paper outline, plan for time and evaluation
(3 pages max)
|12 ||20 ||Draft paper (10 pages including
Use the same
format at AIED papers
|13 ||10 ||Reviews - review process as in normal
conference and journal peer review.
You should use the
|14 ||10 ||Presentation (20 mins + questions)
|14 ||35 ||Final paper
|14 ||5 ||Soft poster