Application of Quantum Fuzzy Decision-Making in the Cultivation of Humanistic Literacy in College English Courses
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Abstract
To address the high subjectivity and inability of traditional models to handle cognitive superposition and psychological interference in multi-source evaluations, this paper proposes a dynamic evaluation model based on quantum fuzzy decision-making for cultivating humanistic literacy in college English courses. An evaluation system comprising three primary and seven secondary indicators is established. Unstructured teaching data is mapped onto a complex Hilbert space using quantum state probability amplitude, effectively capturing evaluators’ multiple cognitive superposition characteristics without information loss. Furthermore, quantum coherence and phase angle parameters are introduced to quantify and correct cognitive interference biases stemming from subjective preferences, contextual dependence, and cross-cultural differences. A quantum spherical fuzzy aggregation operator then performs a nonlinear weighted fusion of the heterogeneous data. This process outputs comprehensive results while preserving individual dimensional traits to support precise tiered teaching interventions. Simulation experiments utilizing five hundred real teaching samples demonstrate the significant superiority of this approach over traditional linear methods. The proposed model reduces the average absolute percentage error by over fourteen percent when processing highly conflicting subjective data, maintains strict logical consistency, and exhibits strong robustness against random noise perturbations with minimal information loss. Ultimately, this framework accurately identifies students’ individual weaknesses, offering a reliable engineering paradigm to facilitate targeted teaching interventions and improve the overall effectiveness of interdisciplinary educational evaluation.
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