Split menus: effectively using selection frequency to organize menus
ACM Transactions on Computer-Human Interaction (TOCHI)
Designing visual interfaces: communication oriented techniques
Designing visual interfaces: communication oriented techniques
Design of Man-Computer Dialogues
Design of Man-Computer Dialogues
A Machine-Learning Apprentice for the Completion of Repetitive Forms
IEEE Expert: Intelligent Systems and Their Applications
Mediface: Anticipative Data Entry Interface for General Practitioners
OZCHI '98 Proceedings of the Australasian Conference on Computer Human Interaction
ScentTrails: Integrating browsing and searching on the Web
ACM Transactions on Computer-Human Interaction (TOCHI)
Intelligent data entry assistant for XML using ensemble learning
Proceedings of the 10th international conference on Intelligent user interfaces
Exploring the design space for adaptive graphical user interfaces
Proceedings of the working conference on Advanced visual interfaces
EcoPod: a mobile tool for community based biodiversity collection building
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
A predictive model of menu performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Scented Widgets: Improving Navigation Cues with Embedded Visualizations
IEEE Transactions on Visualization and Computer Graphics
Predictability and accuracy in adaptive user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing an architecture for delivering mobile information services to the rural developing world
Designing an architecture for delivering mobile information services to the rural developing world
Ephemeral adaptation: the use of gradual onset to improve menu selection performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Journal of Artificial Intelligence Research
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
Automated quality control for mobile data collection
Proceedings of the 2nd ACM Symposium on Computing for Development
Shreddr: pipelined paper digitization for low-resource organizations
Proceedings of the 2nd ACM Symposium on Computing for Development
Data Quality of Query Results with Generalized Selection Conditions
Operations Research
Patina: dynamic heatmaps for visualizing application usage
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using Checksums to Detect Number Entry Error
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. Usher provides a theoretical, data-driven foundation for improving data quality during entry. Based on prior data, Usher learns a probabilistic model of the dependencies between form questions and values. Using this information, Usher maximizes information gain. By asking the most unpredictable questions first, Usher is better able to predict answers for the remaining questions. In this paper, we use Usher's predictive ability to design a number of intelligent user interface adaptations that improve data entry accuracy and efficiency. Based on an underlying cognitive model of data entry, we apply these modifications before, during and after committing an answer. We evaluated these mechanisms with professional data entry clerks working with real patient data from six clinics in rural Uganda. The results show that our adaptations have the potential to reduce error (by up to 78%), with limited effect on entry time (varying between -14% and +6%). We believe this approach has wide applicability for improving the quality and availability of data, which is increasingly important for decision-making and resource allocation.