The Path of Building Trusted Data Space under Digital Transformation of Education

Abstract

In the context of education digital transformation, the problems of data siloing and low trustworthiness seriously constrain the release of education data value. Based on the perspective of new quality productivity, this paper proposes a systematic framework for constructing a credible data space in education, aiming to promote the intelligent transformation of education data through the synergistic innovation of technical architecture and governance mechanism. The study points out that the current domestic education data sharing faces the core challenges of fuzzy data sovereignty attribution and insufficient cross-system compatibility. Based on this, an education data governance framework based on the theory of trusted data space is proposed, which aims to provide a systematic solution to the multidimensional dilemma of education data circulation by constructing a five-layer synergistic architecture system and integrating blockchain, identity governance, and other technologies. The architecture supports the intelligent deployment of regional educational resources and cross-domain training of AIGC tools, effectively balancing data privacy and utility, as verified by scenario projection. The study emphasizes that credible data space needs to rely on new digital infrastructure and education subject literacy enhancement to promote the transformation of education productivity to data intelligence paradigm through “innovation of governance mechanism, embedding of technology tools, and reconfiguration of business scenarios,” and to provide theoretical support and practical paths for optimal allocation of education resources and enhancement of the quality and efficiency of education services.