ESRA 2027 sessions by theme
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Do New Technologies in Questionnaire Translation require New Best Practices? |
| Coordinator 1 | Dr Patricia Hadler (SHARE Berlin Institute) |
| Coordinator 2 | Dr Dorothée Behr (GESIS - Leibniz Institute for the Social Sciences) |
| Coordinator 3 | Ms Ulrike Efu Nkong (GESIS - Leibniz Institute for the Social Sciences) |
Session Details
Following best practice, questionnaires for multilingual surveys have traditionally been translated using the TRAPD approach, which comprises translation, review, adjudication, pretesting, and documentation. Ideally, the initial translations are produced independently by at least two professional translators with expertise in survey translation, while additional team members serve as reviewers and adjudicators. However, many cross-cultural survey projects face challenges in recruiting and funding sufficient personnel to fulfil these roles, and so modifications of TRAPD exist, with single initial translations, split up translations, reconciliations or reviews of initial translations by one person, or focused team discussions.
At the same time, rapid advances in machine translation—notably translation done by large language models—are increasingly being incorporated into the translation workflows of major survey and research infrastructures, including the ESS, SHARE, and PISA. These developments call for a reassessment of current translation approaches. While machine translation offers opportunities to improve efficiency and reduce costs, its use raises methodological questions regarding translation quality, measurement equivalence, and the comparability of survey data across languages and cultures. Establishing evidence-based best practices for integrating machine translation into questionnaire translation is therefore a pressing challenge for survey methodology.
This session welcomes papers examining the quality of machine-generated translations, explore the integration of machine translation into team-based translation approaches or into quality assessment of translations. We are also interested in papers exploring the integration of other types of technological developments into questionnaire translation processes in the widest sense or technologies that might be used to facilitate self-administered surveys across different languages or language registers. We welcome papers delineating the roles of humans and the machine. Contributions addressing the implications of machine translation for measurement equivalence and cross-national comparability, as well as methodological, practical, and quality-assurance aspects of translation workflows, are particularly encouraged.
