论文标题
四年回顾：人类机器人相互作用研究中李克特量表的统计实践
Four Years in Review: Statistical Practices of Likert Scales in Human-Robot Interaction Studies
论文作者
论文摘要
随着机器人变得越来越普遍，人类机器人相互作用（HRI）领域的重要性也会相应增长。因此，我们应该努力采用最佳的统计实践。李克特量表是HRI中常用的指标，以衡量感知和态度。由于错误的信息或诚实的错误，大多数HRI研究人员在分析Likert数据时不会采用最佳实践。我们对心理测量学文献进行了综述，以确定当前的李克特量表设计和分析标准。接下来，我们对四年的人类机器人互动会议（2016年至2019年）进行了四年的调查，并报告了李克特量表不正确的统计实践和设计。在这些年中，只有110篇论文中只有3篇对正确设计的李克特量表进行了适当的统计测试。我们的分析表明，在李克特量表的设计和测试方面有有意义的改进领域。最后，我们提供建议，以提高李克特数据得出的结论的准确性。
As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practices. Likert scales are commonly used metrics in HRI to measure perceptions and attitudes. Due to misinformation or honest mistakes, most HRI researchers do not adopt best practices when analyzing Likert data. We conduct a review of psychometric literature to determine the current standard for Likert scale design and analysis. Next, we conduct a survey of four years of the International Conference on Human-Robot Interaction (2016 through 2019) and report on incorrect statistical practices and design of Likert scales. During these years, only 3 of the 110 papers applied proper statistical testing to correctly-designed Likert scales. Our analysis suggests there are areas for meaningful improvement in the design and testing of Likert scales. Lastly, we provide recommendations to improve the accuracy of conclusions drawn from Likert data.
