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Computer-based rating method for evaluating multiple visual stimuli on multiple scales

机译:基于计算机的评级方法,用于在多个尺度上评估多个视觉刺激

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摘要

In this research, two joint evaluation rating methods (focus-on-attribute and drag-and-drop) and a separate evaluation rating method (focus-on-stimulus) are proposed for rating multiple visual stimuli with respect to multiple scales. All three interactive methods incorporate a real-time adjusting mechanism, allowing respondents to interactively adjust their ratings. Using the traditional paper-and-pencil method as the basis for comparison, the performance of these computer-based rating methods and the proposed real-time adjusting mechanism were investigated. First, it was found that the computer-based methods not only produced results equivalent to those produced by the paper-and-pencil method, but also improved the data quality by preventing the occurrence of missing values and allowing respondents to adjust their scores. Second, the two joint evaluation methods performed better than the separate evaluation method in terms of usage experience, test-retest reliability, and the likelihood of simulating the daily shopping experience, in which multiple consumer products are often compared simultaneously. Of the two joint evaluation methods, the drag-and-drop method received better subjective evaluations than the focus-on-attribute method. Third, the proposed real-time adjusting mechanism was found to obtain better subjective satisfaction in rating. In summary, for measuring multiple visual stimuli with multiple scales, the computer-based joint evaluation rating methods using a real-time adjusting mechanism were found to be better choices among the measurement tools investigated.
机译:在这项研究中,提出了两种联合评估评级方法(属性集中和拖放)和一种单独的评估评级方法(刺激重点)来针对多个尺度对多个视觉刺激进行评级。这三种互动方法都采用了实时调整机制,允许受访者以互动方式调整自己的评分。以传统的纸笔法为基础进行比较,研究了这些基于计算机的评分方法的性能以及所提出的实时调整机制。首先,人们发现基于计算机的方法不仅产生了与纸笔法相同的结果,而且还通过防止出现遗漏值并允许受访者调整得分来提高数据质量。其次,在经常比较多个消费产品的使用经验,重测可靠性和模拟日常购物体验的可能性方面,两种联合评估方法的性能要优于单独评估方法。在两种联合评估方法中,拖放方法比“关注属性”方法获得更好的主观评估。第三,发现所提出的实时调整机制在评分方面获得了更好的主观满意度。综上所述,为测量具有多个尺度的多个视觉刺激,使用实时调整机制的基于计算机的联合评估评级方法被认为是所研究的测量工具中的更好选择。

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