Andrea Bunt
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Publications by Andrea Bunt (bibliography)
» 2009 «
Bunt, Andrea, Terry, Michael and Lank, Edward (2009): Friend or foe?: examining CAS use in mathematics research. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 229-238. Available online
“Computer Algebra Systems (CAS) provide sophisticated functionality to assist with mathematical problem solving. Despite their widespread adoption, however, little work in the HCI community has examined the extent to which these computational tools support domain experts. In this paper, we report findings from a qualitative study investigating the work practices and tools of nine mathematicians in a research setting. Counter to our expectations, our data suggests that computational tools play only a minor role in their workflow, with the limited use of CAS owing primarily to four factors: (1) the need for transparency in CAS's reasoning to explain computed results; (2) the problem of rigidity and formality in CAS's input/output style dialogue; (3) the need for 2D input to support a wide range of annotations, diagrams, and in-place manipulation of objects of interest; and (4) the need for collaboration, particularly in early stages of problem solving. While grounded in the study of mathematicians, these findings (particularly the first) have implications for the design of computational systems intended to support complex problem solving.”
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Spaulding, Aaron, Gajos, Krzysztof Z., Jameson, Anthony, Kristensson, Per Ola, Bunt, Andrea and Haines, Will (2009): Usable intelligent interactive systems: CHI 2009 special interest group meeting. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 2743-2746. Available online
“The AI and HCI communities have often been characterized as having opposing views of how humans and computers should interact" observes Winograd in Shifting Viewpoints. It is time to narrow this gap. What was once considered the forefront of artificial intelligence (AI) research can now be found in commercial products. While some have failed, others, such as face detection in digital cameras or product recommendation systems, have become so mainstream they are no longer thought of as artificial intelligence. This special interest group provides a forum to examine the apparent gap between HCI and AI communities, to explore how intelligent technologies can enable novel interaction with computation, and to investigate the challenges associated with understanding human abilities, limitations, and preferences in order to drive the design of intelligent interactive systems.”
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» 2008 «
Ruiz, Jaime, Bunt, Andrea and Lank, Edward (2008): A Model of Non-Preferred Hand Mode Switching. In: Proceedings of the 2008 Conference on Graphics Interface May 28-30, 2008, Windsor, Ontario, Canada. pp. 49-56.
“Effective mode-switching techniques provide users of tablet interfaces with access to a rich set of behaviors. While many researchers have studied the relative performance of mode-switching techniques in these interfaces, these metrics tell us little about the behavior of one technique in the absence of a competitor. Differing from past comparison-based research, this paper describes a temporal model of the behavior of a common mode switching technique, non-preferred hand mode switching. Using the Hick-Hyman Law, we claim that the asymptotic cost of adding additional nonpreferred hand modes to an interface is a logarithmic function of the number of modes. We validate the model experimentally, and show a strong correlation between experimental data and values predicted by the model. Implications of this research for the design of mode-based interfaces are highlighted.”
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Ruiz, Jaime, Tausky, David, Bunt, Andrea, Lank, Edward and Mann, Richard (2008): Analyzing the Kinematics of Bivariate Pointing. In: Proceedings of the 2008 Conference on Graphics Interface May 28-30, 2008, Windsor, Ontario, Canada. pp. 251-258.
“Despite the importance of pointing-device movement to efficiency in interfaces, little is known on how target shape impacts speed, acceleration, and other kinematic properties of motion. In this paper, we examine which kinematic characteristics of motion are impacted by amplitude and directional target constraints in Fitts-style pointing tasks. Our results show that instantaneous speed, acceleration, and jerk are most affected by target constraint. Results also show that the effects of target constraint are concentrated in the first 70% of movement distance. We demonstrate that we can discriminate between the two classes of target constraint using Machine Learning with accuracy greater than chance. Finally, we highlight future work in designing techniques that make use of target constraint to improve pointing efficiency in computer interfaces.”
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» 2007 «
Gluck, Jennifer, Bunt, Andrea and McGrenere, Joanna (2007): Matching attentional draw with utility in interruption. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 41-50. Available online
“This research examines a design guideline that aims to increase the positive perception of interruptions. The guideline advocates matching the amount of attention attracted by an interruption's notification method (attentional draw) to the utility of the interruption content. Our first experiment examined a set of 10 visual notification signals in terms of their detection times and established a set of three significantly different signals along the spectrum of attentional draw. Our second experiment investigated matching these different signals to interruption content with different levels of utility. Results indicate that the matching strategy decreases annoyance and increases perception of benefit compared to a strategy that uses the same signal regardless of interruption utility, with no significant impact on workload or performance. Design implications arising from the second experiment as well as recommendations for future work are discussed.”
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Bunt, Andrea, Conati, Cristina and McGrenere, Joanna (2007): Supporting interface customization using a mixed-initiative approach. In: Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. pp. 92-101. Available online
“We describe a mixed-initiative framework designed to support the customization of complex graphical user interfaces. The framework uses an innovative form of online GOMS analysis to provide the user with tailored customization suggestions aimed at maximizing the user's performance with the interface. The suggestions are presented non-intrusively, minimizing disruption and allowing the user to maintain full control. The framework has been applied to a general user-productivity application. A formal user evaluation of the system provides encouraging evidence that this mixed-initiative approach is preferred to a purely adaptable alternative and that the system's suggestions help improve task performance.”
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Bunt, Andrea, McGrenere, Joanna and Conati, Cristina (2007): Understanding the Utility of Rationale in a Mixed-Initiative System for GUI Customization. In: Conati, Cristina, McCoy, Kathleen F. and Paliouras, Georgios (eds.) User Modeling 2007 - 11th International Conference - UM 2007 June 25-29, 2007, Corfu, Greece. pp. 147-156. Available online
» 2005 «
Bunt, Andrea (2005): User Modelling to Support User Customization. In: Ardissono, Liliana, Brna, Paul and Mitrovic, Antonija (eds.) User Modeling 2005 - 10th International Conference - UM 2005 July 24-29, 2005, Edinburgh, Scotland, UK. pp. 499-501. Available online
» 2004 «
Bunt, Andrea, Conati, Cristina and McGrenere, Joanna (2004): What role can adaptive support play in an adaptable system?. In: Nunes, Nuno Jardim and Rich, Charles (eds.) International Conference on Intelligent User Interfaces 2004 January 13-16, 2004, Funchal, Madeira, Portugal. pp. 117-124. Available online
“As computer applications become larger with every new version, there is a growing need to provide some way for users to manage the interface complexity. There are three different potential solutions to this problem: 1) an adaptable interface that allows users to customize the application to suit their needs; 2) an adaptive interface that performs the adaptation for the users; or 3) a combination of the adaptive and adaptable solutions, an approach that would be suitable in situations where users are not customizing effectively on their own. In this paper we examine what it means for users to engage in effective customization of a menu-based graphical user interface. We examine one aspect of effective customization, which is how characteristics of the users' tasks and customization behaviour affect their performance on those tasks. We do so by using a process model simulation based on cognitive modelling that generates quantitative predictions of user performance. Our results show that users can engage in customization behaviours that vary in efficiency. We use these results to suggest how adaptive support could be added to an adaptable interface to improve the effectiveness of the users' customization.”
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» 2001 «
Bunt, Andrea and Conati, Cristina (2001): Modeling Exploratory Behaviour. In: Bauer, Mathias, Gmytrasiewicz, Piotr J. and Vassileva, Julita (eds.) User Modeling 2001 - 8th International Conference - UM 2001 July 13-17, 2001, Sonthofen, Germany. pp. 219-221. Available online
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Mar 21st, 2010
Changes to this page (author)
22 Feb 2010: Enabled abstracts to be shown on Andrea Bunt's author page.30 May 2009: Author was edited 30 May 2009: Author was edited
30 May 2009: Author was edited
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28 Apr 2003: Added the author to the bibliography
