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Is vague valid? The comparative predictive validity of vague quantifiers and numeric response options

机译:模糊有效吗?模糊量词和数值响应选项的比较预测效度

摘要

© European Survey Research Association. A number of surveys, including many student surveys, rely on vague quantifiers to measure behaviors important in evaluation. The ability of vague quantifiers to provide valid information, particularly compared to other measures of behaviors, has been questioned within both survey research generally and educational research specifically. Still, there is a dearth of research on whether vague quantifiers or numeric responses perform better in regards to validity. This study examines measurement properties of frequency estimation questions through the assessment of predictive validity, which has been shown to indicate performance of competing question formats. Data from the National Survey of Student Engagement (NSSE), a preeminent survey of university students, is analyzed in which two psychometrically tested benchmark scales, active and collaborative learning and student-faculty interaction, are measured through both vague quantifier and numeric responses. Predictive validity is assessed through correlations and regression models relating both vague and numeric scales to grades in school and two education experience satisfaction measures. Results support the view that the predictive validity is higher for vague quantifier scales, and hence better measurement properties, compared to numeric responses. These results are discussed in light of other findings on measurement properties of vague quantifiers and numeric responses, suggesting that vague quantifiers may be a useful measurement tool for behavioral data, particularly when it is the relationship between variables that are of interest.
机译:©欧洲调查研究协会。许多调查(包括许多学生调查)依靠模糊的量词来衡量对评估很重要的行为。总体上,调查研究和教育研究都质疑模糊量词提供有效信息的能力,特别是与其他行为量度相比。然而,关于模糊性的量词或数字响应在有效性方面是否表现更好,尚缺乏研究。这项研究通过评估预测有效性来检验频率估计问题的测量属性,这已显示出竞争性问题格式的表现。分析了来自全国优秀学生调查的国家学生参与度调查(NSSE)的数据,其中通过模糊的量词和数字响应来测量两个经过心理计量测试的基准量表,即主动和协作学习以及学生与教职员工的互动。通过将模糊和数字量表与学校成绩相关的相关性和回归模型以及两种教育经验满意度测评来评估预测有效性。结果支持这样一种观点,即与数字响应相比,模糊量表的预测有效性更高,因此测量性能更好。将根据模糊量词和数值响应的测量属性的其他发现讨论这些结果,这表明模糊量词可​​能是行为数据的有用测量工具,尤其是当变量之间的关系很重要时。

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    Baghal TA;

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  • 年度 2014
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