This module introduces students to the principles and practice of modern survey design. The module exposes students to the considerable literature on survey methodology that informs best practice in contemporary survey research. Survey methodology has, over the past two decades or so, developed into a more or less unified field of research and practice. It brings together insights from, inter alia, cognitive and social psychology and statistics to explain how human behaviour and survey design decisions interact to produce data of varying quality. Key to this perspective is the concept of 'total survey error'. This framework is used throughout the module to discuss the multiple sources of error that modern survey design methods aim to mitigate. The initial focus of this module is on introducing social science graduates to the fundamentals of survey design and to the concept of survey error. A variety of different types of design are introduced with their relative costs, benefits and indications for particular types of study purpose. The focus then moves to introducing students to a variety of modes of data collection and the significance of survey mode on data quality. Different sources of measurement error are then identified and explored; respondents, questions, and interviewers. We then look at how to design questions, and ways of evaluating questions to avoid eliciting measurement error. Finally, we look at the role of survey management; keeping a balance between survey errors and costs. Throughout the module, concepts and methods will be illustrated with real examples and case studies - many of them drawn from the survey work that takes place at ISER.
Aims
The aim of this course is to provide an introduction to the theory and practice of modern survey design and measurement The focus will be on practical transferable survey skills required to conduct professional surveys.
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Learning Outcomes
By the end of the module students should be able to:
* Distinguish between different types of survey designs and their uses
* Understand and explain the total survey error framework
* Demonstrate an understanding of the key features of effective questionnaire design
* Design a questionnaire using current best practice
* Identify the different modes of survey data collection and the implications for cost and quality
Syllabus
* Survey Quality and Survey Error: The Total Survey Error perspective (1 week)
* What is a survey? Steps in the process (population of inference, from concepts to questions)
* Survey quality and survey error (total survey error)
* Survey mode and data collection methods (2 weeks)
* Telephone, face to face, self-completion, web, mobile
* Mixed and multi-mode surveys
* Mode effects on survey error
* Current practices
* New develoments in surveys (1 week)
* The future of surveys?
* Online access (non-probability) panels
* Data collection using mobile devices, sensors, wearables
* Linkage to 'big data', e.g. government administrative records, social media data
* Sources of measurement error (2 weeks)
* Psychology of survey response (Cognitive Aspects of Survey Methodolgy).
* Sources of measurement error - the interviewer (interviewer effects), respondent (recall, satisficing, social desirability), questionnaire (context and framing effects)
* Question wording (1 week)
* Principles of writing survey questions
* Hands-on practice and critique of survey measures
* Question and Questionnaire evaluation methods (1 week)
* Cognitive testing
* Behaviour coding
* Expert review
* Other methods and issues
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* Designing web surveys in Qualtrix (1 week)
* Principles of web survey design
* Hands-on practice on how to design a web survey in Qualtrics
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* Survey Management (1 week)
* Survey management practice and quality control
* Legal and ethical obligations
- Module Supervisor: Annette Jackle