The Construction of Higher Education Evaluation Index System Based on Vector Analysis

Abstract

The construction of a higher education evaluation index system based on vector analysis involves a comprehensive approach to assessing the quality and effectiveness of higher education institutions. By leveraging vector analysis, which considers both magnitude and direction, this method enables the integration of diverse factors and perspectives into the evaluation process. Key considerations in constructing such an index system include academic performance, research output, faculty qualifications, student satisfaction, institutional resources, and societal impact. Each factor is represented as a vector, with its magnitude reflecting its importance and its direction indicating its alignment with the overarching goals of higher education. This paper presents a novel approach for constructing a robust evaluation index system for higher education institutions leveraging vector analysis, supplemented by Periodic Vector Chain Learning (PVCL). the incorporation of PVCL enhances the dynamism and adaptability of the evaluation system. PVCL allows for periodic updates and adjustments to the evaluation index system, ensuring its relevance and effectiveness amidst changing educational landscapes and emerging trends. The integration of vector analysis with PVCL presents a promising avenue for the construction of a robust evaluation index system for higher education institutions.