Using Personality Factors to Predict Interface Learning Performance
Using Personality Factors to Predict Interface Learning Performance
复制标题
使用个性因素来预测界面学习表现
DOI：
10.1109/hicss.2010.431
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Brian D. Fisher
中科院分区：
文献类型：
--
作者：
T. M. Green;D. Jeong;Brian D. Fisher
本研究探讨了在交互式可视化和菜单驱动的网络应用程序中，个性因素的个体差异对界面交互和学习绩效的影响。参与者接受了6项心理测量，旨在评估特质焦虑、控制点和其他人格特征。然后，参与者被要求在每个界面上完成3个程序性任务和3个推理任务。结果表明，具有外部控制源的参与者比具有内部控制源的参与者完成推理任务的速度更快。对6个心理测量量表的条目进行因素分析，分离出9个条目的短量表，该量表与程序性分数呈趋势性。此外，数据还表明，可视化界面对于推理任务的完成更为有效和高效。对于这两种类型的任务，参与者也更喜欢可视化而不是网络界面。最后，对本研究的意义和未来发展方向进行了讨论。
This current study explored the impact of individual differences in personality factors on interface interaction and learning performance in both an interactive visualization and a menu-driven web application. Participants were administered 6 psychometric measures designed to assess trait anxiety, locus of control, and other personality traits. Participants were then asked to complete 3 procedural tasks and 3 inferential tasks in each interface. Results demonstrated that participants with an external locus of control completed inferential tasks more quickly than those with an internal locus. Factor analysis of items from the 6 psychometric scales isolated a 9-item short measure, which showed trending with procedural scores. Additionally, data demonstrated that the visualization interface was more effective and efficient for the completion of the inferential tasks. Participants also preferred the visualization to the web interface for both types of task. Implications and future directions of this research are also discussed.
影响因子：
5.9
作者：
BECK, AT;BROWN, G;STEER, RA
通讯作者：
STEER, RA