ESRA 2027 sessions by theme

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Session Details

Survey quality depends not only on sampling, measurement and fieldwork strategy, but also on the experience people have when they are asked to take part. As surveys increasingly move to online, mobile and mixed-mode self-completion, respondents are asked to interpret questions, navigate instruments, understand communications and resolve uncertainty with little to no interviewer support. This creates methodological and practical challenges: how can surveys remain rigorous, inclusive and comparable while also being understandable, usable and meaningful to respondents?

This session invites contributions that apply user-centred, respondent-centred, UX research or design-thinking approaches to the development, testing or redesign of surveys. Contributions may focus on new surveys designed with respondents from the outset, or on established studies where redesign must balance respondent needs with time-series continuity, data-user requirements, commissioner expectations, operational constraints and cost.

We welcome academic and practitioner perspectives, including methodological papers, case studies, evaluations and reflective accounts of implementation. Topics may include but not limited to usability, cognitive or “cogability” testing of questionnaires, respondent materials, interviewer tools or training; journey mapping, mental model research, prototyping and iterative testing; visual, interaction and content design, including mobile responsiveness, accessibility, inclusivity and plain language; using paradata, qualitative evidence or experiments to identify burden, friction, engagement or measurement risks; and applying UX principles to re-examine conventional survey design practices, respondent communications, mode choices or fieldwork processes.

The session aims to build a shared methodological conversation about what UX and design thinking add to survey research: how they can improve respondent experience, support data quality, surface trade-offs, and help survey teams design instruments and processes that work better for respondents, interviewers, commissioners and data users.