Finding gender differences in end-user debugging: A data mining approach

被引：0
|
作者：
Grigoreanu, Valentina [1 ]
机构：
[1] Oregon State Univ, Corvallis, OR 97331 USA
来源：
VL/HCC 2007: IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/VLHCC.2007.39
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We are currently investigating what types of end user personas (or homogeneous groups in the population) exist and what works for or hinders each in end-user debugging. These personas will be determined using data mining methods such as cluster analysis to see how static (background and self-efficacy), behavioral, and success variables interact for each cluster of users. This research will help provide a better understanding of the needs of end users and the tools that are necessary for supporting both male and females in debugging tasks.
引用
收藏
页码：258 / 259
页数：2
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