International Journal of
Information and Education Technology

Abstract

To solve the problem of imbalanced resource allocation in universities, we take six secondary colleges of a comprehensive university as the research object and propose a university resource optimization and governance decision-making method based on multidimensional data fusion. For data fusion, the data layer completes the cleaning and unified mapping of heterogeneous data from multiple sources, and the feature layer performs quality evaluation on the integrity rate and cross system consistency verification of the introduced data. Objectively determine the weights of each indicator using the entropy weight method. When constructing the indicator system, it covers three dimensions: supply, efficiency and fairness, and verifies the internal consistency and structural validity of the indicator system through Cronbach’s alpha and KMO tests. For resource optimization, we formalize the problem of cross departmental teacher allocation as a constraint optimization model, with the objective function of minimizing the coefficient of variation of the student teacher ratio. We set three types of constraints and directly use the model output as the basis for allocation decisions. Scenario comparison analysis shows that after optimization, the coefficient of variation of teacher to teacher ratio decreased by 40.2%, classroom utilization rate increased by 9.76%, and the comprehensive index of each college exceeded the warning threshold of 0.40.