Data Collection: Online, Telephone and Face-to-face
- Offered byCoursera
Data Collection: Online, Telephone and Face-to-face at Coursera Overview
Duration | 21 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Collection: Online, Telephone and Face-to-face at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 7 in the Survey Data Collection and Analytics Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 21 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Data Collection: Online, Telephone and Face-to-face at Coursera Course details
- 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.
Data Collection: Online, Telephone and Face-to-face at Coursera Curriculum
Module 1: Introduction, Classic Modes of Survey Data Collection
1.1 What this course is ? and is not
1.2.1 Introduction to Survey Errors
1.2.2 Variable Error and Bias
1.2.3 Total Survey Error
1.3.1 What do we mean by ?mode??
1.3.2 Mode Choice (by respondent)
1.4.1 Mixed Mode Design
1.4.2 Concurrent Mixed Mode
1.4.3 Sequential (Follow-up) Mixed Mode
1.4.4 Interview with David Weir (U. Michigan) on Mixed Mode Designs
1.5.1 Response Rates
1.5.2 Nonresponse Error
Module 1 Overview
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Module 1 Required Readings
Module 1 Lecture Slides
Notice for Auditing Learners: Assignment Submission
Module 1: Classic Modes of Data Collection
Module 2: Self-administration, Online Data Collection
2.1.1 Modes (interviewer- and self-administered), CASI, ACASI
2.1.2 ACASI continued
2.2.1 Coverage
2.2.2 Nonresponse
2.2.3 Measurement
2.3.1 Progress Indicators, Running Tallies
2.3.2 Online Definitions
2.3.3 Speeding Interventions
2.4 Reg Baker (MRII) about web surveys in market research
Module 2 Overview
Module 2 Required Readings
Module 2 Lecture Slides
Quiz Two
Module 3: Interviewers and Interviewing
3.1.1 Interviewer Roles, Obtaining Interviews
3.1.2 Respondent selection, Within Household Sampling
3.1.3 Proxy Responding
3.2.1 Standardization Debate: Wording vs. Meaning
3.2.2 Different approaches to standardized interviewing
3.2.3 Personal vs. Formal Style, I-R Rapport
3.3.1 Variance: Interviewer Behavior
3.3.2 Bias: Interviewers? Fixed Attributes
3.4 Interview with Nora Cate Schaeffer (UW) about recruitment and interviewing
Module 3 Overview
Module 3 Required Readings
Module 3 Lecture Slides
Quiz Three
Module 4: Emerging modes, new data sources
4.1.1 New Modes, New Data
4.1.2 Mobile Web Surveys
4.1.3 Text Message Surveys
4.1.4 Text vs. Voice Interviews
4.2.1 Record linkage: statistical issues
4.2.2 Record linkage: Techniques
4.2.3 Record linkage: informed consent and ethical issues
4.3.1 Uses of Big Data, Sensing Technology, Social Media Content as Data
4.3.2 Social media applications: Measuring Mood and Depression
4.3.3 Social Media and Population Estimates: Successes
4.3.4 Why does social media content align with surveys data sometimes and not other times?
4.4 Interview with Aigul Mavletova (National Research University Higher School of Economics, Mosow) on mobile web surveys
Module 4 Overview
Module 4 Required Readings
Module 4 Lecture Slides
Post-course Survey
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Module 4: Emerging modes, new data sources
Final Exam
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