Lifelong User Modelling
Judy Kay, Bob Kummerfeld
School of Information Technologies, University of Sydney
Contact Person
Judy Kay
judy@it.usyd.edu.au
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Project Description
Pervasive and ubiquitous computing offers significant potential for improving our lives.
There is a fast and growing rate of pervasive computing, in which computational power
is embedded in our environment (in such locations as smarter cars, buildings and devices)
and we carry around increasingly powerful tools for computation and device-to-device
communication.
Conventional computers are cheap and widely available, and many people make use
of several in their daily lives.
This computational power has the potential to enable intellectual development and learning,
and to improve our physical health and social well-being,
particularly when used as a lifelong resource.
A feature of pervasive and ubiquitous computing is that it collects and moves
huge amounts of data that are about us or belong to us.
This huge and fast-growing collection of personal data offers great potential benefits.
Augmented cognition and life-long memories are two of these:
providing people with ready access to pertinent information about themselves
from their own data stores will enable them to expand their effective
cognition and knowledge beyond what they would otherwise remember.
Such augmented cognition tools will be of particular value for people who suffer
cognitive loss, as is common with ageing.
Life-long learning is another potential benefit, with the possibility
that we can learn precisely when and where we need to, with learning
resources delivered just for us, taking account of our existing knowledge
and preferred ways of learning. While these benefits are significant,
they will be accompanied by the issue of how individuals’ privacy will be safeguarded.
The extent of concern about privacy is reflected in the ongoing debates in this area,
such as the proposed Australian biometric benefits card.
There is an essential trade-off between the benefits of capturing and
using personal data and the risk to privacy.
People vary in their attitude
to this trade-off, which will inevitably be governed on the basis of personal
and societal decisions.
Whatever the outcome of the debate on the trade-off,
people need to be empowered technically to determine their own preferences for
storing, accessing and using their personal information.
This project aims to create the science and technology that will allow
people to control their personal information and its use in pervasive
computing environments.
Key Publications
S. Bull and J. Kay. Student models that invite the learner in: The SMILI open learner modelling framework. IJAIED, International Journal of Artificial Intelligence, 17(2):89-120, 2007. [View Details]
S. Bull and J. Kay. Student models that invite the learner in: The SMILI open learner modelling framework. Technical Report 580, School of IT, The University of Sydney, January 2006. [View Details]
J. Kay. Scrutable adaptation: because we can and must. In V. Wade, H. Ashman, and B.Smyth, editors, Proceedings of Adaptive Hypermedia and Adaptive Web-Based Systems, 4th International Conference, AH2006, pages 11-19. Springer, 2006. [View Details]
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