Description of the symposium
The quality of data is paramount to obtaining robust results in linguistic research. From large quantitative studies to in-depth qualitative analyses and ethnographic fieldwork, all researchers encounter questions concerning the relevance, significance, and reliability of their data.
The purpose of the IRG symposium is to give young researchers an opportunity to gain valuable experience in interacting with peers and fellow researchers during a scientific conference and to invite them to reflect on some fundamental scientific issues. Graduate and doctoral students, often working on their first independent research project, are constantly faced with challenges related to data. They must consider what type of data best suits their research questions and how these data can be accessed. Once they have been obtained, the data have to be stored, sorted, classified, analysed, and finally interpreted. During this long process, researchers must keep sight of what is theoretically and empirically advantageous, socially and ethically appropriate and practically feasible. Finally, these questions re-emerge when researchers present their data and findings to different audiences, which might range from co-workers and experts in the field to non-scientific institutions and stakeholders. Thus, the process of empirical research is to a considerable extent that of finding a path from data to knowledge.
Focussing on methods, processes, challenges and problems rather than results, we will discuss issues concerning data, which arise at every step of the research process. We aim to broaden the discussion and exchange new ideas by bringing together perspectives from various language sciences including, but not limited to, applied linguistics, psycholinguistics, neurolinguistics, second language acquisition and bilingualism research, sociolinguistics, historical linguistics, linguistic anthropology, computer linguistics, forensic linguistics, language teaching research and language assessment. We invite contributions dealing with a variety of approaches to data, ranging from single-case to large-scale studies and including both primary and secondary data as well as mixed methods approaches.