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

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

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About this course: 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 hybr…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Created by:  University of Michigan
  • Taught by:  Frederick Conrad, Ph.D., Research Professor, Survey Methodology

    Institute for Social Research
Basic Info Course 2 of 7 in the Survey Data Collection and Analytics Specialization Level Beginner Commitment 4 weeks of study, 2-4 hours/weeks Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.6 stars Average User Rating 4.6See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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University of Michigan The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.

Syllabus


WEEK 1


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.


12 videos, 4 readings expand


  1. Reading: Module 1 Overview
  2. Reading: Help us learn more about you!
  3. Reading: Module 1 Required Readings
  4. Video: 1.1 What this course is … and is not
  5. Reading: Module 1 Lecture Slides
  6. Video: 1.2.1 Introduction to Survey Errors
  7. Video: 1.2.2 Variable Error and Bias
  8. Video: 1.2.3 Total Survey Error
  9. Discussion Prompt: Survey Error
  10. Video: 1.3.1 What do we mean by “mode?”
  11. Video: 1.3.2 Mode Choice (by respondent)
  12. Video: 1.4.1 Mixed Mode Design
  13. Video: 1.4.2 Concurrent Mixed Mode
  14. Video: 1.4.3 Sequential (Follow-up) Mixed Mode
  15. Video: 1.4.4 Interview with David Weir (U. Michigan) on Mixed Mode Designs
  16. Video: 1.5.1 Response Rates
  17. Video: 1.5.2 Nonresponse Error

Graded: Module 1: Classic Modes of Data Collection

WEEK 2


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.


9 videos, 3 readings expand


  1. Reading: Module 2 Overview
  2. Reading: Module 2 Required Readings
  3. Video: 2.1.1 Modes (interviewer- and self-administered), CASI, ACASI
  4. Video: 2.1.2 ACASI continued
  5. Reading: Module 2 Lecture Slides
  6. Video: 2.2.1 Coverage
  7. Video: 2.2.2 Nonresponse
  8. Video: 2.2.3 Measurement
  9. Video: 2.3.1 Progress Indicators, Running Tallies
  10. Video: 2.3.2 Online Definitions
  11. Video: 2.3.3 Speeding Interventions
  12. Video: 2.4 Reg Baker (MRII) about web surveys in market research
  13. Discussion Prompt: Modes

Graded: Quiz Two

WEEK 3


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.


9 videos, 3 readings expand


  1. Reading: Module 3 Overview
  2. Reading: Module 3 Required Readings
  3. Video: 3.1.1 Interviewer Roles, Obtaining Interviews
  4. Video: 3.1.2 Respondent selection, Within Household Sampling
  5. Video: 3.1.3 Proxy Responding
  6. Reading: Module 3 Lecture Slides
  7. Video: 3.2.1 Standardization Debate: Wording vs. Meaning
  8. Video: 3.2.2 Different approaches to standardized interviewing
  9. Discussion Prompt: Standardization Debate
  10. Video: 3.2.3 Personal vs. Formal Style, I-R Rapport
  11. Video: 3.3.1 Variance: Interviewer Behavior
  12. Video: 3.3.2 Bias: Interviewers’ Fixed Attributes
  13. Video: 3.4 Interview with Nora Cate Schaeffer (UW) about recruitment and interviewing

Graded: Quiz Three

WEEK 4


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.


12 videos, 4 readings expand


  1. Reading: Module 4 Overview
  2. Reading: Module 4 Required Readings
  3. Video: 4.1.1 New Modes, New Data
  4. Video: 4.1.2 Mobile Web Surveys
  5. Video: 4.1.3 Text Message Surveys
  6. Video: 4.1.4 Text vs. Voice Interviews
  7. Reading: Module 4 Lecture Slides
  8. Video: 4.2.1 Record linkage: statistical issues
  9. Video: 4.2.2 Record linkage: Techniques
  10. Video: 4.2.3 Record linkage: informed consent and ethical issues
  11. Video: 4.3.1 Uses of Big Data, Sensing Technology, Social Media Content as Data
  12. Video: 4.3.2 Social media applications: Measuring Mood and Depression
  13. Video: 4.3.3 Social Media and Population Estimates: Successes
  14. Video: 4.3.4 Why does social media content align with surveys data sometimes and not other times?
  15. Discussion Prompt: Social Media and Survey Methods
  16. Video: 4.4 Interview with Aigul Mavletova (National Research University Higher School of Economics, Mosow) on mobile web surveys
  17. Reading: Post-course Survey

Graded: Module 4: Emerging modes, new data sources
Graded: Final Exam
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