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Designing adaptive feedback for improving data entry accuracy

Published: 03 October 2010 Publication History

Abstract

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.

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    cover image ACM Conferences
    UIST '10: Proceedings of the 23nd annual ACM symposium on User interface software and technology
    October 2010
    476 pages
    ISBN:9781450302715
    DOI:10.1145/1866029
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 03 October 2010

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    Author Tags

    1. adaptive interface
    2. data entry
    3. data quality
    4. form design
    5. repetitive task

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    • (2019)Comparing the accuracy and speed of four data-checking methodsBehavior Research Methods10.3758/s13428-019-01207-3Online publication date: 11-Mar-2019
    • (2018)User preferences for adaptive user interfaces in health information systemsUniversal Access in the Information Society10.5555/3288381.328839917:4(875-883)Online publication date: 1-Nov-2018
    • (2017)A Systematic Mapping Study for Intelligent User Interfaces - IUI2017 International Conference on Information Systems and Computer Science (INCISCOS)10.1109/INCISCOS.2017.34(361-368)Online publication date: Nov-2017
    • (2017)User preferences for adaptive user interfaces in health information systemsUniversal Access in the Information Society10.1007/s10209-017-0569-117:4(875-883)Online publication date: 5-Aug-2017
    • (2017)‘Quantitative Probabilistic Widgets’: Method to Improve Usability Performance of Data Entry TaskErgonomics in Caring for People10.1007/978-981-10-4980-4_35(281-287)Online publication date: 6-Oct-2017
    • (2013)Data Quality of Query Results with Generalized Selection ConditionsOperations Research10.1287/opre.1120.112861:1(17-31)Online publication date: 1-Jan-2013
    • (2013)Using Checksums to Detect Number Entry ErrorProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2470654.2481332(2403-2406)Online publication date: 27-Apr-2013
    • (2013)PatinaProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2470654.2466442(3227-3236)Online publication date: 27-Apr-2013
    • (2013)An error detecting and tagging framework for reducing data entry errors in electronic medical records (EMR) system2013 IEEE International Conference on Bioinformatics and Biomedicine10.1109/BIBM.2013.6732498(249-254)Online publication date: Dec-2013
    • (2012)ShreddrProceedings of the 2nd ACM Symposium on Computing for Development10.1145/2160601.2160605(1-10)Online publication date: 11-Mar-2012
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