Andrea Bunt

Probabilistic Student Modelling to Improve Exploratory Behaviour

This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learners exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learners exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation.

Supporting interface customization using a mixed-initiative approach

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 users 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 systems suggestions help improve task performance.

Matching attentional draw with utility in interruption

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 interruptions 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.

Adaptive content presentation for the web

In this chapter we describe techniques for adaptive presentation of content on the Web. We first describe techniques to select and structure the content deemed to be most relevant for the current user in the current interaction context. We then illustrate approaches that deal with the problem of how to adaptively deliver this content.

Improving command selection with CommandMaps

Designers of GUI applications typically arrange commands in hierarchical structures, such as menus, due to screen space limitations. However, hierarchical organisations are known to slow down expert users. This paper proposes the use of spatial memory in combination with hierarchy flattening as a means of improving GUI performance. We demonstrate these concepts through the design of a command selection interface, called CommandMaps, and analyse its theoretical performance characteristics. We then describe two studies evaluating CommandMaps against menus and Microsofts Ribbon interface for both novice and experienced users. Results show that for novice users, there is no significant performance difference between CommandMaps and traditional interfaces -- but for experienced users, CommandMaps are significantly faster than both menus and the Ribbon.

AdaptableGIMP: designing a socially-adaptable interface

We introduce the concept of a socially-adaptable interface, an interface that provides instant access to task-specific interface customizations created, edited, and documented by the applications user community. We demonstrate this concept in AdaptableGIMP, a modified version of the GIMP image editor that we have developed.

Involving children in content control: a collaborative and education-oriented content filtering approach

We present an approach to content control where parents and children collaboratively configure restrictions and filters, an approach that focuses on education rather than simple rule setting. We conducted an initial exploratory qualitative study with results highlighting the importance that parents place on avoiding inappropriate content. Building on these findings, we designed an initial prototype which allows parents and children to work together to select appropriate applications, providing an opportunity for parents to educate their children on what is appropriate. A second qualitative study with parents and children in the six to eight year-old age group revealed a favorable response to this approach. Our results suggest that parents felt that this approach helped facilitate discussions with their children and made the education more enjoyable and approachable, and that children may have also learned from the interaction. In addition, the approach provided some parents with insights into their childrens interests and understanding of their notions of appropriate and inappropriate content.

Assessing Effective Exploration in Open Learning Environments Using Bayesian Networks

Open learning environments provide a large amount of freedom and control, which can be beneficial for students who are able to explore the environment effectively, but can also be problematic for those who are not. To address this problem, we have designed a student model that allows an open learning environment to provide the students with tailored feedback on the effectiveness of their exploration. The model, which uses Bayesian Networks, was created by an iterative design and evaluation process. The successive evaluations were used to improve the model and to provide initial support for its accuracy and usefulness.

MathBrush: a case study for pen-based interactive mathematics

Current generations of computer algebra systems require users to transform two dimensional math expressions into one dimensional strings, to master complex sets of commands, and to analyze lengthy output strings for relevant information. MathBrush is a system, designed based on research in education pedagogy, that provides a pen-based interface to many of the features of computer algebra systems. We describe relevant work in education pedagogy as a motivation for MathBrushs design. We highlight aspects of MathBrush that are unique from other contemporary pen-math systems. Finally, we present the results of a thinkaloud evaluation of the MathBrush system. Together, these observations validate aspects of the current design of MathBrush, suggest areas for refinement, and inform the design of future pen-math systems.

An interface for remote robotic manipulator control that reduces task load and fatigue

Remote control robots are being found in an increasing number of application domains, including search and rescue, exploration, and reconnaissance. There is a large body of HRI research that investigates interface design for remote navigation, control, and sensor monitoring, while aiming for interface enhancements that benefit the remote operator such as improving ease of use, reducing operator mental load, and maximizing awareness of a robots state and remote environment. Even though many remote control robots have multi-degree-of-freedom robotic manipulator arms for interacting with the environment, there is only limited research into easy-to-use remote control interfaces for such manipulators, and many commercial robotic products are still using simplistic interface technologies such as keypads or gamepads with arbitrary mappings to arm morphology. In this paper, we present an original interface for the remote control of a multi-degree of freedom robotic arm. We conducted a controlled experiment to compare our interface to an existing commercial keypad interface and detail our results that indicate our interface was easier to use, required less cognitive task load, and enabled people to complete tasks more quickly. In this paper, we present an original interface for the remote control of a multi-degree of freedom robotic arm. We conducted a controlled experiment to compare our interface to an existing commercial keypad interface and detail our results that indicate our interface was easier to use, required less cognitive task load, and enabled people to complete tasks more quickly.