Across multiple disciplines and research paradigms, question asking is understood as a central mechanism for inquiry, learning, and reasoning. Prior work frames questioning as a cognitive, linguistic, social, and epistemic process through which individuals move from vague uncertainty to structured inquiry. Foundational models describe how questions emerge in response to perceived knowledge gaps, while linguistic frameworks clarify how questions function logically and how their structure shapes reasoning. Educational and learning focused literature emphasizes how questions scaffold understanding, deepen dialogue, and support collaborative sense making. Collectively, this body of work suggests that effective question asking arises from interactions among cognitive processes, social context, communicative norms, and epistemic goals, and that iterative refinement, awareness of assumptions, and shared framing are central to intentional inquiry.
Despite this rich foundation, most existing questions asking models remain focused at the individual or disciplinary level. However, for interdisciplinary and collaborative scientific contexts problems can be complex with high uncertainty and with knowledge distributed across disciplines. Few of the question-asking literature provide frameworks that are grounded on these latter contexts. This would include frameworks that address varying disciplinary assumptions of a team and that point to inter- or trans-, rather than multi-disciplinary approaches. Moreover, there is limited empirical or conceptual guidance on how questions evolve within interdisciplinary teams, how questioning supports the resolution of conceptual conflict, or which forms of questions best enable collective reasoning and effective collaboration.
This presentation synthesizes insights from cognitive, educational, and linguistic literatures to inquire about how existing models can inform a team level understanding of scientific questions asking, and what gaps may exist within these frameworks. Some previous works offer partial entry points for this extension but remain unexplored. For example, models of reasoning repair through meta questioning describe how teams surface and resolve breakdowns in shared understanding. Research on “great questions” highlights how questioning strengthens relationships and reveals tacit knowledge in collaboration, stage based and taxonomy driven approaches provide structures for guiding groups from intuitive, discipline specific concerns toward negotiated research questions. Other theoretical works posit logic based frameworks as a path forward, integrating problem formulation and question asking within an interdisciplinary structure.
Across these sources, effective interdisciplinary questions tend to (1) expose assumptions, (2) explore interactions across scales or systems, (3) require synthesis across knowledge domains, and (4) explicitly engage with uncertainty. We argue that these properties point toward the need for a framework for interdisciplinary scientific questions; one that integrates logical structure, cognitive triggers, and collaborative reasoning processes, while explicitly accounting for scale, systems thinking, and uncertainty. The presentation will conclude by outlining implications for future empirical research and training interventions in team science.