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.
이 강좌는 Survey Data Collection and Analytics 전문 분야의 일부입니다.
Data Collection: Online, Telephone and Face-to-face
제공자:
- Researchers
- Professors
- Data Analysts
- Medical Doctors
- Data Scientists
강의 계획 - 이 강좌에서 배울 내용
Module 1: Introduction, Classic Modes of Survey Data Collection
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.
Module 2: Self-administration, Online Data Collection
This second lesson focuses on modes in which survey respondents self-administer questions and provide their responses directly to researchers. By the end of Lesson 2, you will understand the pros and cons of self-administered modes from the TSE perspective.
Module 3: Interviewers and Interviewing
In this lesson, we explore the various roles interviewers take on beside asking questions and collecting answers, as well as some of the different approaches to interviewing that have been proposed and how they affect the accuracy of responses. By the end of Lesson 3, you will appreciate the benefits and costs of collecting data in interviews and will be able to contrast them with the costs and benefits of self-administration.
Module 4: Emerging modes, new data sources
In this lesson, we focus on some new data collection modes such as mobile web surveys and SMS text interviews, as well as alternative data sources such as sensor data, administrative data, and social media. By the end of this lesson, you will have a sense of the issues to which survey methodologists and survey researchers are devoting much of their attention these days. You will be able to weigh the pros and cons of these new methods and data sources.
50%
50%
Data Collection: Online, Telephone and Face-to-face의 최상위 리뷰
-\n\nthe difference between mobile survey and web survey\n\ndifference between online and face to face interviews\n\ndifference between telephone interviews and computer interviws
There is one word for this Course "Amazing". No matter if you are a undergrad student or a seasoned researcher, you'll feel that you have learned a lot from this course.
강사
Frederick Conrad, Ph.D.
Research Professor, Survey Methodology미시건 대학교 정보
Survey Data Collection and Analytics 전문 분야 정보
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.
환불 규정은 어떻게 되나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
