Toward a framework of uncertainty in ill-structured problem solving

Abstract This study advances a framework for understanding uncertainty in ill-structured problem-solving contexts. A systematic review and qualitative synthesis of 74 peer-reviewed articles was conducted using thematic analysis and taxonomic coding to clarify how uncertainty is conceptualized across problem-solving and learning research. The resulting framework defines uncertainty as a subjective metacognitive and psychological experience that arises as learners interpret problems, make judgments, and regulate action under conditions of incomplete, conflicting, or changing information. Seven intersecting sources of uncertainty are delineated: problem context, outcomes, sociocultural influences, epistemological factors, environmental conditions, dynamicity, and complexity. By distinguishing uncertainty from adjacent terms (for example, ambiguity and vagueness) and from its manifestations (for example, hesitation or frustration), the framework provides conceptual clarity that supports more coherent theorizing and improved operationalization in empirical work. Implications for instructional design include informing the design and facilitation of problem-based, inquiry-based, and case-based learning tasks in which uncertainty is anticipated and supported as part of complex learning.