Classification and Hierarchical Governance Approaches of Educational Data from the Perspective Contextual Integrity Theory

Educational data is the core element driving the digital transformation of education. In view of the prevailing problems in static classification and hierarchy of educational data, such as poor rule adaptability and distorted risk assessment,, this paper reconstructed the classification and hierarchical governance system based on contextual theory. In term of classification dimension, four core scenarios including teaching, scientific research, management and operation, as well as public administration and their extended scenarios were divided according to contextual elements, with differentiated governance rules formulated accordingly. In the hierarchical dimension, a “base risk level + contextual dynamic factor”model was adopted to classify educational data into low-risk, medium-risk, and high-risk categories, and to formulate gradient governance strategies centered on context integration, context adaptation and context locking respectively. Finally, the data management regulations of five universities were selected to verify the feasibility and effectiveness of the proposed scheme. This research provided an innovative approach for balancing the security protection and development and utilization of educational data, facilitating the sustainable digital transformation of education.