ESRA 2027 sessions by theme

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Session Details

Development and validation of measurement instruments can pose challenges related to item selection, answer scale construction, and instrument modifications, all of which should meet different quality criteria, such as minimizing systematic measurement error and maximizing reliability, validity, and comparability across population groups. Computational methods (CSS) and Artificial Intelligence (AI) have become relevant for solving such problems and can foster innovation in questionnaire development and evaluation. Use of these methods is also promising for understanding underlying cognitive response processes, as they can help investigate numerous potential sources of measurement bias and improve questionnaire design to maximize measurement quality and data comparability.
The session aims to foster discussions among researchers who use CSS methods and AI to optimize questionnaire design, evaluate systematic and non-systematic measurement error, and validate measurement instruments. Papers are invited that provide a conceptual basis for the use of AI and CSS in measurement, serve as examples of the use of these methods for the research on questionnaire design or cognitive response processes, compare different methods, or discuss limitations and further developments.