Pervasive and ubiquitous computing offers significant potential for improving our lives. 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, including augmented cognition and life-long memories: 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. 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. There is an essential trade-off between the benefits of capturing and using personal data and the risk to privacy. Whatever the outcome of the debate on this 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.
Validation of a designer Australian smartphone app to replace written weighed food records in nutrition research. Journal Article
Australasian Epidemiologist, 32 (3), pp. 80-81, 2014.
Viewing and Controlling Personal Sensor Data: What Do Users Want? Inproceedings
PERSUASIVE 2013, LNCS 7822, pp. 15-26, Springer, Heidelberg, 2013.
Proceedings of the 43rd ACM technical symposium on Computer Science Education, pp. 147–152, 2012.
ACE, Australasian Computing Education Conference, pp. 147-156, 2012.
Lifelong learner modeling Book Chapter
Durlach, Paula J; Lesgold, Alan (Ed.): Adaptive Technologies for Training and Education, Cambridge University Press, 2011.
Theoretical Foundations for User-Controlled Forgetting in Scrutable Long Term User Models Inproceedings
OZCHI, pp. 40-49, 2011.
An architecture for systematic tracking of skill and competence level progression in Computer Science Inproceedings
Computer Science Education: Innovation and Technology CSEIT 2011, pp. 65-69, 2011.
Modeling long term learning of generic skills Inproceedings
Aleven, Vincent; Kay, Judy; Mostow, Jack (Ed.): ITS2010, Proceedings of the Tenth International Conference on Intelligent Tutoring Systems, pp. 85-94, Springer, 2010.
PersonisJ: mobile, client-side user modelling Inproceedings
UMAP 2010, LNCS 6075, pp. 111-122, Springer-Verlag Berlin Heidelberg, 2010.
Lifelong Personalized Museum Experiences Inproceedings
Pervasive User Modeling and Personalization (PUMP'10) at UMAP2010, pp. 9-16, 2010.
Personalized Cultural Heritage GeoNotes Inproceedings
Pervasive Personalisation Workshop held in conjunction with Pervasive 2010, pp. 1-9, 2010.
Mobile personalisation: new challenges for privacy Inproceedings
Ubiquitous User Modeling, at UMAP 2009, pp. 37-40, 2009.
Lifelong User Modelling Goals, Issues and Challenges Inproceedings
Proceeding of the Lifelong User Modelling Workshop at UMAP'09 User Modeling Adaptation, and Personalization, pp. 27-34, 2009.
Personal Lifelong User Model Clouds Inproceedings
Proceeding of the Lifelong User Modelling Workshop at UMAP'09 User Modeling Adaptation, and Personalization, pp. 1-8, 2009.
Proceedings of the Workshop on Scalability Issues in AIED, held in conjunction with AIED2009, pp. 10-19, 2009.
IEEE Trans on Learning Technologies, 1 (4), pp. 215-228, 2008.
Student Models that Invite the Learner In: The SMILI Open Learner Modelling Framework Journal Article
IJAIED, International Journal of Artificial Intelligence, 17 (2), pp. 89-120, 2007.
Scrutable adaptation: because we can and must Inproceedings
Wade, V; Ashman, H; B.Smyth, (Ed.): Proceedings of Adaptive Hypermedia and Adaptive Web-Based Systems, 4th International Conference, AH2006, pp. 11-19, Springer, Dublin, Ireland, 2006.
MetaView: Dynamic metadata based views of user files Inproceedings
McArthur, Rob; Thomas, Paul; Turpin, Andrew; Wu, Mingfang (Ed.): Australian Document Computing Symposium, pp. 11-19, Hobart, Australia, 0000.