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Introduction to Survey Design

Week 1 (03-07 October 2022)

Lecturers: Sonila Dardha, Andrew Mukiibi

About the lecturers

Sonila Dardha is a survey methodologist researching on interviewer effects, response patterns, nonresponse error and 3MC surveys, and a survey practitioner coordinating comparative cross-cultural surveys. Sonila is currently pursuing her PhD in Survey Research Methodology at City, University of London, the host institution of the European Social Survey (ESS ERIC). She has previously obtained three Master degrees, one of which in M.Sc Statistics (Quantitative Analysis for the Social Sciences) from KU Leuven, Belgium. She is an experienced consultant for methods and statistics and has worked with a leading research company in Brussels and London, Kantar, for international projects and institutional clients. These include, for example, the Enterprise Surveys in Africa (World Bank), Eurobarometer Surveys (European Commission), European Elections 2015 (European Parliament), Life in Transition Survey (European Bank for Reconstruction and Development), and Global Attitudes Project (Pew Research Center).

Andrew Adrian Mukiibi is a social research consultant with over 16 years of experience in conducting research in East Africa. He has been a full time lecturer of Research Methods at Muteesa I Royal University and is currently supporting numerous non-governmental organisations strengthen research components of their programming function. He holds two Masters Degree one in Development Studies and the other in Monitoring and Evaluation from Uganda Martrys University and the University of Saarland respectively. He has also been exposed to Social Perfomance Management by the Social Perfomance Task Force based in France. He has worked on the Afrobarometer Survey in Uganda, conducted multiple projects with World Vision International, USAID, Habitant For Humanity (DR Congo, Rwanda, Kenya, and Uganda), Ford Foundation and the East African Philanthropy Networkamong others.

Short course description

Surveys are, arguably, one of the most popular methods of data collection for empirical social science research. This course is dedicated to the full survey life cycle and provides insights to every stage of this process. It discusses general guidelines and gold standards in survey design, and addresses common pitfalls and how to avoid them. The course examines the survey life cycle against the assumptions of the Total Survey Error (TSE) framework, a holistic theory to study errors at every stage of the survey process. The objective of this course is to enable participants to design a sound survey project and make informed decisions about core methodological aspects such as the mode of data collection, sampling design, questionnaire design, and fieldwork management. Finally, we discuss quality indicators, e.g. response rates and response styles, following recommendations provided by leading survey research organisations such as the American Association for Public Opinion Research.

A full-length syllabus will be available for download here closer to the course date.

Course prerequisites

  • No previous experiences in survey design required
  • Participants will benefit from basic knowledge of quantitative methods

Target group

Participants will find the course useful if:

  • They are already involved in a survey project but have little knowledge of the applied field of survey design
  • They want to conduct their own survey for an academic project such as a thesis or paper and would benefit from feedback on their designs
  • They have a specific research question, idea or project plan in mind and would like to check feasibility of using surveys and quantitative methods to implement them

Course and learning objectives

By the end of the course participants will:

  • Understand the relevance of surveys for conducting research
  • Have comprehensive knowledge on the full survey life cycle and the TSE framework
  • Be able to critically evaluate surveys
  • Gain skills to design, plan and manage own survey projects
  • Have the capability to transparently document survey data and quality
  • Recognise the importance of research integrity when designing, implementing, managing, and reporting surveys
  • Learn independently following guidelines and gold standards of survey methodology

Hardware and software requirements

Participants should bring their own laptops, ideally with an installed Office package and access to the internet to log onto ILIAS. Since this course does not cover survey data analyses, no statistical packages are required.