DATA COMPLIANCE FRAMEWORK IN AI APPLICATION OF REMOTE EDUCATION: LEGAL PATH BASED ON KNOWLEDGE MANAGEMENT AND EFFECT EVALUATION
Chen Chenwei
PhD, School of Economics and Management, Yunnan Open University , (Yunnan Technical College of Industry), Kunming, China
Abstract
The deep integration of artificial intelligence into distance education has triggered a systemic data compliance crisis. This study addresses the unique contradiction where educational data possesses both personal attributes and knowledge value, as well as issues in existing governance models such as the disconnect between technical approaches and institutional regulations, the separation of knowledge management from effectiveness evaluation, and the absence of cross-border rules. It proposes a "knowledge management-effect evaluation" dual-driven framework for legalizing data compliance. First, it analyzes four major challenges: imbalance of rights and responsibilities among stakeholders, regulatory blind spots in data types, risks arising from technological development, and conflicts of sovereignty across borders. Second, it establishes theoretical foundations by clarifying that the knowledge management dimension must balance incentives for knowledge innovation with data security controls, while the effectiveness evaluation dimension should ensure data credibility and algorithmic trustworthiness. These two dimensions achieve synergy through goal alignment, risk complementarity, and tool integration. Third, it designs a legal pathway: establishing three core principles—education-oriented, tiered control, and dynamic informed consent; building an institutional system featuring restructured stakeholder responsibilities, embedded lifecycle processes, and cross-border data flow safety gates; and integrating technical governance tools like privacy-enhancing technologies, algorithm rule parameterization, and blockchain judicial empowerment. Finally, it proposes an implementation safeguard system comprising specialized regulatory mechanisms, optimized responsibility allocation, and closed-loop feedback for effectiveness evaluation. This study provides a theoretically innovative and practically actionable solution to address data governance challenges in educational technology innovation, aiming to strengthen the legal foundation for educational equity and quality in the digital era.
Keywords: Distance Education; Artificial Intelligence; Data Compliance; Knowledge Management; Effectiveness Evaluation; Rule of Law Path; Dual-Wheel Drive Framework
Journal Name :
VIEW PDF
EPRA International Journal of Environmental Economics, Commerce and Educational Management
VIEW PDF
Published on : 2025-07-31
| Vol | : | 12 |
| Issue | : | 7 |
| Month | : | July |
| Year | : | 2025 |