Design of an Educational Psychology Research Material Sharing Platform Based on Fuzzy Clustering Algorithm

Abstract

In the interdisciplinary field of educational psychology, efficiently managing and accessing research materials remains a formidable challenge due to the vast and varied nature of available data. This paper introduces an innovative platform engineered to streamline the organization and dissemination of educational psychology research materials by harnessing the power of fuzzy clustering algorithms for automated content categorization. Motivated by the imperative to enhance the accessibility and discoverability of scholarly resources, our methodology employs the Fuzzy C-Means (FCM) algorithm, adept at accommodating the intrinsic ambiguity and overlap prevalent in educational psychology topics. The process initiates with a comprehensive preprocessing of diverse research materials, including scholarly articles, reports, and datasets, succeeded by meticulous feature extraction to distill pivotal themes and concepts. Subsequent application of the FCM algorithm facilitates the intuitive grouping of materials into clusters, each with varying degrees of relevance, thereby mirroring the multidimensional essence of the domain. Rigorous experimental validation of our approach underscores its efficacy in augmenting search precision and markedly diminishing the time scholars expend in locating pertinent materials. The platform’s user-centric interface further simplifies the exploration of educational psychology research, offering scholars a streamlined mechanism to access and engage with an extensive repository of resources. Through this study, we demonstrate a significant stride towards overcoming the hurdles in research material categorization and retrieval, heralding a new era of efficiency and accessibility for the educational psychology academic community on a global scale.