Calendar

May 27

13th Intl. Conf. on New Interfaces for Musical Expression

May 28

Graphics Interface 2013

May 29

Intl. Workshop on Design and Spontaneity in Computer-Supported Collaborative Learning (DS-CSCL 2013)

May 22

“ User error: replace user and press any key to continue. ”

-- Popular computer one-liner

Share this quote on...
Get more quotes via RSS or by joining our Usability Quote of the Day Facebook Page

Featured chapter

Read the fascinating history of Wearable Computing, told by its father, Steve Mann

Read Steve's chapter !

Help us help you!

Spread the word:
Donate
Other ways to help

Kuang Chen

Add description

← Button will not work: You have not enabled Javascript. How do I enable it?

Rename / change spelling

Add publication

← Button will not work: You have not enabled Javascript. How do I enable it?

Publications by Kuang Chen (bibliography)

2010

Edit | Del

Chen, Kuang, Hellerstein, Joseph M. and Parikh, Tapan S. (2010): Designing adaptive feedback for improving data entry accuracy. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 239-248.

“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.”

Add publication