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Survey Design

Member rate £492.50
Non-Member rate £985.00

Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked

*If you attended our Methods School in the last calendar year, you qualify for £45 off your course fee.

Course Dates and Times

Monday 6 – Friday 10 February 2023
Minimum 2 hours of live teaching per day
Monday – Thursday 10:00 – 12:00 CET
Friday 14:00 – 16:00 CET

Sabrina Mayer

sabrina.mayer@uni-bamberg.de

University of Bamberg

Bernd Schlipphak

bernd.schlipphak@uni-muenster.de

University of Münster

This seminar-type course provides a highly interactive online teaching and learning environment, using state-of-the-art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the Instructor can cater to the specific needs of each individual.

Purpose of the course

Most people can run a survey, especially with the help of online platforms. However, not everyone can conduct one that complies with best practice and standards in the field to ensure high quality data is collected. This course teaches you how to design surveys for various outcomes, target groups and constructs, by drawing on the Total Survey Error (TSE) framework.

ECTS Credits

3 credits Engage fully with class activities 
4 credits Complete a post-class assignment


Instructor Bio

Sabrina holds a PhD in political science and is Head of the Data and Methods Research Department at the German Center for Integration and Migration Research (DeZIM). 

She has ample experience with survey design. She coordinated the Immigrant German Election Study and has led several large-scale surveys using different modes.

Her research focuses on social identities, electoral behaviour, and survey research. She has previously worked on sampling methods for small and hard-to-reach groups, as well as interviewer effects.

Twitter @SabrinaJMayer

Bernd is Associate Professor of Political Science with a focus on Empirical Research Methods.

He has ample experience with survey design as a coordinator of several large-scale and regular surveys in the Global North and the Global South. Bernd's research focuses on citizens' political attitudes at the domestic and international level. To better understand and explain these attitudes, he has recently focused on experimental settings, such as vignette or multifactorial designs.

Bernd recently published a chapter on survey design in a handbook on political science methodology.

 @BSchlipphak

Key topics covered

This course covers the most important stages in the survey life cycle. You will learn how to design your own structured surveys, no matter which units you are surveying, eg people or organisations.

We will cover the Total Survey Error framework and move on to sample and questionnaire design, as well as the central aspects of survey modes, interviewer recruiting (where applicable) and pre-testing. Finally, we talk about data harmonisation and storage.

You are welcome to raise additional questions relating to your own work. You will get the most out of this course if you are currently designing your own survey and are willing to present and discuss it in class.

This course will not cover analysis of survey data after collection has taken place. We will not cover qualitative interviews or focus group techniques. The Interviews for Qualitative Data Generation course will help you to learn more about this. 

Day 1

You will get to know the Total Survey Error framework, discussing all potential sources of errors (biases, actual errors, and 'noise'). We focus on the problematic relationship between Measurement (validity) and Representation.

Day 2

We start with sampling (probability and non-probability) and then discuss probability and non-probability sampling approaches especially feasible for smaller projects.

Day 3

We introduce current survey modes (personal, telephone, and online surveys), and look at their differences, strengths and weaknesses. We discuss the role of incentives.

Day 4

We introduce questionnaire design, taking a hands-on approach based on positive and negative rules: how to do it, and how not to do it.

Day 5

An overview of problems and potential solutions for translating, pre-testing and fielding a survey. This class is based not only on state-of-the-art literature in the field, but also on Instructors' personal experiences.

We focus on issues of data harmonisation and storage. The latter is becoming increasingly important in publishing survey data-based findings. There will be some time for presentation and discussion of participants' work.

Based on the number of participants and individual needs, there may be slight changes to this outline and the order in which we present the topics.


How the course will work online

During the course week, expect to join live classroom teaching for over ten hours in total. This course relies on the concept of the flipped classroom, where you will introduce yourself to new topics outside of the live sessions via the short, pre-recorded lectures and there will be live two-hour sessions each day to discuss your ideas in greater depth and explore the topics further.

We use a combination of different learning tools. You will read relevant parts of the literature, and do related exercises on your own, the results of which we will discuss in the live sessions.

Live sessions will also cover additional parts of the topics and other application exercises.

You are welcome to discuss your own survey project, or relevant aspects of it, with participants and Instructors, either in small groups or with the whole course cohort. We will give feedback on your design, so you can see how it holds up against the standards of the profession.

You do not need experience in survey research, though some experience of research methods in general is useful.

You don't need to know how to use statistical software, because the course focuses on the design of surveys and will not deal with data analysis.

Some experience in data analysis using survey data, however, would be beneficial.