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Outputs (3)

Teaching the next generation of universal access designers: a case study (2011)
Presentation / Conference Contribution
Keates, S. (2011). Teaching the next generation of universal access designers: a case study. In C. Stephanidis (Ed.), Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Proceedings, Par

This paper describes the development of the ?Usability and Accessibility? course for M.Sc. students at the IT University of Copenhagen. The aim is to examine whether this course provides an effective and useful method for raising the issues around Un... Read More about Teaching the next generation of universal access designers: a case study.

Using motion sensing remote controls with older adults (2011)
Presentation / Conference Contribution
von Bruhn Hinné, T., & Keates, S. (2011). Using motion sensing remote controls with older adults. In C. Stephanidis (Ed.), Universal Access in Human-Computer Interaction. Design for All and eInclusion: 6th International Conference, UAHCI 2011, Proceedin

This paper examines how motion sensitive remote control devices can improve the usability of television sets for older adults. It investigates the use of a pointing remote control where the actions are read and selected on the TV screen by a group of... Read More about Using motion sensing remote controls with older adults.

Human-machine design considerations in advanced machine-learning systems (2011)
Journal Article
Keates, S., Varker, P., & Spowart, F. (2011). Human-machine design considerations in advanced machine-learning systems. IBM Journal of Research and Development, 55(5), 4:1-4:10. https://doi.org/10.1147/JRD.2011.2163274

This paper explores issues related to human–computer interaction with the new class of machine-learning systems that represent an exciting development on the frontiers of information technology. These systems represent a significant breakthrough in h... Read More about Human-machine design considerations in advanced machine-learning systems.