Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs
Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs
复制标题
用于准确预测网站导航问题、非问题、问题严重性和修复有效性的工具
DOI：
10.1145/1054972.1054978
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
P. Polson
中科院分区：
文献类型：
--
作者：
M. H. Blackmon;M. Kitajima;P. Polson
Web认知漫游（Cognitive Walkthrough for the Web，CWW）是一种部分自动化的可用性评估方法，用于识别和修复网站导航问题。在五个早期实验的基础上[3，4]，我们首先进行了两个新的实验，以创建一个足够大的数据集进行多元回归分析。然后，我们设计了可自动化的问题识别规则，并在该大型数据集上使用多元回归分析来开发一个新的CWW公式，以准确预测问题的严重程度。然后，我们进行了第三个实验来测试预测公式，并针对独立数据集改进CWW，从而对公式进行了全面的交叉验证。我们的结论是，CWW具有较高的心理效度，因为CWW为我们提供了（a）问题严重性的准确度量，（B）对已识别问题的修复成功率高，（c）识别问题的命中率高，误报率低，（d）识别非问题的正确拒绝率高，失误率低。
The Cognitive Walkthrough for the Web (CWW) is a partially automated usability evaluation method for identifying and repairing website navigation problems. Building on five earlier experiments [3,4], we first conducted two new experiments to create a sufficiently large dataset for multiple regression analysis. Then we devised automatable problem-identification rules and used multiple regression analysis on that large dataset to develop a new CWW formula for accurately predicting problem severity. We then conducted a third experiment to test the prediction formula and refined CWW against an independent dataset, resulting in full cross-validation of the formula. We conclude that CWW has high psychological validity, because CWW gives us (a) accurate measures of problem severity, (b) high success rates for repairs of identified problems (c) high hit rates and low false alarms for identifying problems, and (d) high rates of correct rejections and low rates of misses for identifying non-problems.
影响因子：
2.2
作者：
Landauer, TK;Foltz, PW;Laham, D
通讯作者：
Laham, D