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WCQR2027 – 11th World Conference on Qualitative Research
19 January 2027 @ 8:00 – 4 February 2027 @ 17:00 WET Add to calendar Google Calendar iCalendar Outlook 365…
WCQR2027 Training Day
Aimed at providing participants with practical, hands-on learning experiences, this day will feature short courses focused on qualitative research methods.
Art education must shift from focusing solely on technical skill with generative AI to cultivating algorithmic responsibility, where students critically examine how AI-generated images are produced, interpreted, and shared.
In qualitative research with AI, uncertainty should not be eliminated but made visible, because doubt, ambiguity, and even absences in the data can constitute relevant information.
Qualitative research has often been characterized by a paradox: while it claims to be open to complexity, ambiguity, and the emergence of social phenomena, it frequently ends up reproducing predictable, incremental, and overly controlled analytical trajectories…
Agentic AI is particularly effective in operational and analytical support tasks that do not compromise the researcher’s interpretative autonomy, or sovereignty, so to speak. These include proposing initial codes…
The integration of Artificial Intelligence (AI), essentially Generative Artificial Intelligence (GenAI), into qualitative research is redefining the way we produce knowledge. Generative tools, language models, and AI agents have transformed previously time-consuming tasks…
The relationship between the Chain of Thought (CoT) prompting and the STORM tool is rooted in their common goal of enhancing capabilities…
The balanced integration between the potential of AI and the competences of researchers will be crucial to ensure that the future of educational research is more inclusive, innovative, and diverse.
WCQR2025 pre-conference panel discussion “Redefining the Qualitative Researcher’s Role in the Era of AI…”
This paper focuses on qualitative research in its various forms, highlighting the emergent and iterative epistemological features of qualitative data collection and analysis.