Situated learning and the problem of scientific inference

Challenging the dominant view of learning as abstract content internalization, Situated Learning Theory (SLT) reframed learning as a socially mediated, context-bound process and gained influence by aligning with late-twentieth-century commitments to authenticity, participation, and identity. This paper examines the inferential structure of Situated Learning Theory as a theoretical framework, arguing that despite its descriptive and sociocultural appeal, it cannot sustain empirical scrutiny, with references to curricular, policy, professional development, and workplace contexts serving only to illustrate the downstream consequences of adopting a theory without explicit inferential constraints. Key terms such as authentic context and community of practice remain analytically vague and difficult to operationalize. The analysis applies formal tools from Signal Detection Theory, Bayesian model comparison, and information theory to identify three criteria that any viable learning theory must satisfy: (1) a rule for distinguishing learning from non-learning, (2) a mechanism for penalizing predictive error through likelihood updating, and (3) a basis for comparing competing explanations by parsimony and explanatory yield. These standards reveal that SLT offers no testable boundary conditions, no criterion for identifying failure, and no mechanism for theoretical revision. Like the Ptolemaic system that expanded epicycles to preserve its assumptions, SLT accommodates all outcomes but predicts none. This critique does not dispute the interpretive or descriptive contributions of sociocultural research, but evaluates SLT’s scientific standing in contexts where theories are expected to support discrimination, prediction, and revision. As a result, the paper positions its critique not as a terminal verdict, but as an invitation to recast SLT into a form that can be tested, refined, and applied in instructional contexts—preserving its sociocultural insights while restoring empirical accountability. This approach redefines theory advancement in education as the capacity to generate, test, and refine explanations of learning across contexts.