This study examines the optimization of digital resource management and sharing in preschool education, employing the Goodness of Fit (GoF) algorithm to assess eigenvalues’ suitability in this context. As digital educational materials proliferate, effectively managing and disseminating these resources is a critical challenge. We have developed a preschool educational digital resource management and sharing system grounded in GoF algorithmic principles through an in-depth evaluation of various GoF algorithms’ classification and detection capabilities. Our methodology combines theoretical exploration with empirical algorithm performance testing. Findings indicate that a GoF algorithm, explicitly leveraging the chi-square distribution, achieves over 95% accuracy in identifying preschool digital resources. Furthermore, this study introduces a novel dynamic fitting object model, addressing the GoF algorithm’s adaptability in fluctuating environments. Results affirm the algorithm’s broad adaptability and promising efficiency for managing and sharing digital resources in preschool education settings.