Maria Vicente Bonto-Kane
ABSTRACT
In this paper, we describe the innovative approach of using formal computational models to guide design efforts and evaluate software interfaces for usability. Decades of work in the field of HCI looked to using task analyses, live user testing and GOMS modeling techniques to help design for usability. While these methods proved helpful, guidance came after the fact. Only after the prototype interface had been designed were the traditional techniques useful in evaluating the interface. This research seeks to be innovative in two ways. First, it seeks to examine techniques that can directly impact design at the very first stages where it is most critical. Second, it demonstrates the utility of a not so often used approach, that of using formal computational models to impact design. In this research, formal computational models were used to map sequences of operations of an activity or task. A candidate interface was then designed around the formal model's recommendations for what would be most facilitative for this activity. The result was an interface that performed optimally per model predictions. Additionally, live user testing was employed and empirical observations verified and reinforced the model predictions.
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Digital Library
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Index Terms
- Computational modeling approaches help guide early design efforts for usability
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Reviews
Constantin S Chassapis
Through a short analysis of a specific model, this paper shows that activity-centered software design, as opposed to human-centered design, produces more task-effective software tools. The paper does not show formal task analysis and decomposition prior to the design of the software interface, although it does discuss such an approach. Instead, it examines Fitts' law [1] in a nice analysis of an existing interface of a specific software program used in chemical screening laboratories-a palette tool. Bonto-Kane and St. Amant measure the frequency of access of particular functions in the palette-represented by icons in a two-dimensional (2D) arrangement. Then, using Fitts' law, they calculate an index of difficulty for each function location and redesign the palette to reposition frequent functions in less difficult locations. The authors empirically corroborate that the new design is more effective, stating "significant differences in mean response latencies clicking the two icon locations." While Bonto-Kane and St. Amant employ a nice interplay of ideas and methodologies, they present weak empirical evidence. Their findings are surely commensurate with the proposal, but I would have liked to see the analysis of a more complex setup-a more complex interface-with a broader evidence base. Online Computing Reviews Service
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