Seekingasking

Seekingasking is a term used in discussions of conversational dynamics to describe a deliberate practice that blends information seeking with asking questions in order to steer dialogue toward uncovering relevant knowledge. The term combines seeking and asking and is used in contexts where the quality of information depends on iterative questioning. The concept is not widely standardized, and its meaning can vary across disciplines.

In practice, seekingasking involves formulating questions that are open-ended yet targeted, employing reflective questions, clarifying prompts, and verification checks. It often follows a planned sequence that gradually reveals gaps in understanding, while maintaining rapport with the interlocutor. Effective seekingasking balances curiosity with restraint, avoiding leading questions and focusing on evidence, reasoning, and sources.

The approach appears in fields such as education, user research, journalism, and human–computer interaction, where interviewers, educators, researchers, or interview-oriented interfaces aim to maximize data quality through structured inquiry. In AI and chatbot design, seekingasking can guide interactions to extract precise user needs and reduce ambiguity by prompting users to elaborate or confirm assumptions.

Benefits of seekingasking include clearer information, reduced misinterpretation, and the facilitation of collaborative inquiry. It can also help uncover implicit assumptions and align expectations. Potential drawbacks involve a perception of being interrogative or intrusive if overused, the possibility of biased question framing, and cultural differences in communication style. Skillful execution often requires practice in question design, active listening, and adaptive sequencing.

See also: Socratic method, inquiry-based learning, active listening, information-seeking behavior, conversational user experience.