Data Collection: Online, Telephone and Face-to-face

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课程主页: https://www.coursera.org/archive/data-collection-methods

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课程简介

University of Michigan

课程大纲

In this lesson, you will be introduced to some key concepts about survey data collection methods that we will rely on throughout the course. By the end of this lesson, you should be well acquainted with the major sources of survey error and how these are affected -- usually in the form of tradeoffs -- by the particular mode used to administer questions and capture responses.

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This course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions and data quality in order to sensitize learners to how alternative survey designs might impact the data obtained from those surveys. The course reviews a range of survey data collection methods that are both interview-based (face-to-face and telephone) and self-administered (paper questionnaires that are mailed and those that are implemented online, i.e. as web surveys). Mixed mode designs are also covered as well as several hybrid modes for collecting sensitive information e.g., self-administering the sensitive questions in what is otherwise a face-to-face interview. The course also covers newer methods such as mobile web and SMS (text message) interviews, and examines alternative data sources such as social media. It concentrates on the impact these techniques have on the quality of survey data, including error from measurement, nonresponse, and coverage, and assesses the tradeoffs between these error sources when researchers choose a mode or survey design.

数据收集:在线,电话和面对面:本课程介绍了进行的研究,以加深我们对数据收集决策如何影响调查误差的理解。这不是一门关于数据收集的“怎么做”课程,而是回顾有关调查设计决策和数据质量的文献,以使学习者对替代调查设计如何影响从这些调查获得的数据有敏锐的认识。 该课程回顾了一系列调查数据收集方法,这些方法既是基于访谈的(面对面和电话),又是自我管理的(邮寄的纸质问卷和在线实施的纸质问卷,即网络问卷)。还涵盖了混合模式设计以及几种混合模式,这些模式用于收集敏感信息,例如在面对面采访中自行管理敏感问题。该课程还涵盖了更新的方法,例如移动Web和SMS(文本消息)采访,并研究了其他数据源,例如社交媒体。它着重于这些技术对调查数据质量的影响,包括来自测量,无响应和覆盖范围的误差,并在研究人员选择模式或调查设计时评估这些误差源之间的权衡。

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