Stephanie Brikho

Classical theories of learning and motivation generally assume that cognitive and motivational states are determinate, with observed variability attributed to measurement imprecision or incomplete knowledge. However, research in cognitive science has documented systematic deviations from classical probability theory, including context dependence, order effects, and non-additive influences on judgment and decision-making. The present article examines quantum cognition as a complementary theoretical framework for modeling learning and motivation in educational contexts. This approach extends classical models by representing cognitive states within a Hilbert space formalism, representing superposition, incompatibility, interference, and entanglement as mathematically defined properties. These constructs are introduced as formal representational tools and are conceptually mapped onto educational phenomena, including conceptual ambiguity, motivational conflict, and context-sensitive learning. The framework makes no assumptions regarding quantum physical processes in the brain; rather, it adopts quantum probability as a mathematical formalism aligned with empirically observed deviations from the classical probability axioms in human judgment and decision-making. The analysis is theoretical in scope and presents educational applications as conceptual extensions derived from the quantum cognition literature. The framework generates empirically testable predictions, including order-dependent response patterns and violations of classical probability constraints, which may be evaluated using counterbalanced assessment designs and controlled contextual manipulations. By specifying the conditions under which quantum and classical models converge or diverge, the article positions a quantum approach as a formal extension for modeling learning under uncertainty and contextual sensitivity.