Keywords
public education
data privacy
access control
learner trust
governance maturity
educational technology
institutional accountability
Abstract
This study develops a digital governance framework for managing learning data in public education initiatives. The study is designed to examine approximately 60 public education programs using digital attendance systems, online learning platforms, learner profiles, automated assessment tools, and feedback databases. Data are collected from institutional policy documents, platform-use records, administrator surveys, learner consent forms, privacy notices, access-control logs, and user trust questionnaires. The dataset is expected to include around 60 governance policy files, 300 administrator responses, 2,000 learner questionnaires, 500 consent records, and 120,000 anonymized access-control logs. The study measures data ownership clarity, consent transparency, privacy protection, access-control strength, data-use explainability, retention policy completeness, breach-response readiness, and learner trust. Quantitative analysis applies governance maturity scoring, factor analysis, cluster analysis, logistic regression, and structural equation modeling to examine how data governance quality affects learner trust and institutional credibility. The study also identifies different governance maturity types, such as compliance-oriented, platform-dependent, risk-reactive, and transparency-driven models. The innovation of this study lies in connecting educational data governance with measurable learner trust and institutional accountability, providing a practical evaluation model for public education programs that increasingly rely on digital learning records and automated decision-support systems.
References
Lin, T., Chen, A., & Spivack, Z. (2026). Research on Collaborative Piano Teaching Models and Teaching Resource Efficiency Optimization in Public Art Education Systems. Available at SSRN 6284818.
Malomo, O. O., Adekoya, A. A., Donald, A. M., Eyob, E., Omojokun, E., Mummalaneni, V., & Garuba, M. (2025). AI as asset and liability: A dual-use dilemma in higher education and the SPARKE Framework for institutional AI governance. Online Journal of Applied Knowledge Management (OJAKM), 13(2), 57-76.
Hong, Z., Xu, T., & Chen, H. (2026). Automated Detection and Reclamation of Orphaned Compute and Storage Resources in Cloud Infrastructure. Available at SSRN 7116258.
Alhazmi, A. K. (2026). Data Privacy and Security in AI-Driven Education Systems. In Revolutionizing Secure Learning in the Age of AI (pp. 263-294). IGI Global Scientific Publishing.
Rodriguez Müller, A. P., Tangi, L., & Lerusse, A. (2025). Understanding the adoption of artificial intelligence in local government decision‐making: The influence of institutional pressures and managerial perceptions. Public Administration.
Li, J., Zhang, Y., & Gu, Y. (2026). Chain-Hash Audit Framework with Trusted Anchoring for Tamper-Evident Evidence Lifecycle Management.
Zhang, Y., Gu, W., & Wang, J. (2025, December). Research on First Article Inspection (FAI)-Driven Quality Assurance Methods for Wind Turbine Installation and Operation & Maintenance and Their Effect on Reliability Improvement. In Proceedings of the 2025 6th International Conference on Computer Science and Management Technology (pp. 1700-1705).
Huang, R. (2026). Edge-Centric Generative AI: A Survey on Efficient Inference for Large Language Models in Resource-Constrained Environments. Journal of Computer and Communications, 14(4), 238-253.
Da Costa, J., Cloke, H. L., Neumann, J., & Salvidge, N. (2025). Warning cultures in practice: shadow systems in local flood risk governance. Progress in Disaster Science, 100513.
Lin, T., Spivack, Z., & Chen, A. (2026). Monitoring Teaching Quality and Validating Educational Equity in Public Art Education. Available at SSRN 6512778.
Wu, J., Zhang, J., Wu, D., & Peng, Y. (2026). Visual Transformation Mechanisms for Integrating Digital Cultural Heritage Resources into Junior High School Art Curricula.
Alibayeva, R. N., & Allayarova, S. U. (2025). From data to pedagogy: leveraging explainable artificial intelligence to enhance trust, transparency, and effectiveness in intelligent learning systems. Qubahan Techno Journal, 4(3), 51-65.
Gui, H., Fu, Y., Wang, Z., & Zong, W. (2025). Research on Dynamic Balance Control of Ct Gantry Based on Multi-Body Dynamics Algorithm.
Wang, Y., Wang, Y., Yin, X., Arias, R., & Chen, J. (2026). Research on Dynamic Assessment of Glucose‐Lipid Metabolism and Personalized Drug Response Prediction Based on Wearable Multimodal Sensing.
Ko, E. G., & Hughes, J. E. (2026). Value-Sensitive Design in Action: Designing Student-Centered Intelligent Tutoring Systems with Community College Students and Instructors. Computers and Education: Artificial Intelligence, 100560.
Zhang, Z., Tong, Y., & Gao, Y. (2026). Causal Representation Learning for Explainable Early Warning in High-Stakes Decision Systems.
Qi, C., & Qiao, X. (2026, May). Design Patterns for Multi-Agent Systems in Production. In 2026 International Conference on Intelligent Systems, Automation and Control (ISAC) (pp. 198-202). IEEE.
Ismail, I. A., & Aloshi, J. M. R. (2025). Data privacy in AI-driven education: An in-depth exploration into the data privacy concerns and potential solutions. In AI applications and strategies in teacher education (pp. 223-252). IGI Global Scientific Publishing.
Su, D., & Wu, Y. (2026). Multilevel Growth and Social Network Modeling for Functional Communication Enhancement in Students with Intellectual Disabilities.
Gao, G., Gao, R., Lu, C., Gao, R., & Kuang, Y. (2026, March). Security Governance Methods and Quantitative Evaluation for Enterprise SMS and Verification Code Systems. In 2026 International Conference on Generative Artificial Intelligence and Information Security (GAIIS) (pp. 455-458). IEEE.
Rüland, A. L., & Rüffin, N. (2026). Uncertainty and de facto policy design from below: the case of research security. Policy Design and Practice, 1-11.
Xiong, W., Guo, Y., & Zeng, Y. (2026). A Study on the Energy Efficiency of MEP Systems and Coordinated Dispatch Mechanisms for Multi-energy Systems in High-density Urban Buildings. Available at SSRN 7120518.
Bettahi, A., Beloudha, F. Z., & Harroud, H. (2025). Continuous-time modeling in educational data mining and learning analytics: a literature review on methods, ethics, and emerging AI trends. IEEE Access.
Hong, Z., Xu, T., & Chen, H. (2026). A Study on Test Coverage Mapping and Release Risk Prediction in Continuous Delivery of Cloud Services.
Du, Y. (2025). Research on Digital Quality Traceability System for Temperature-Controlled Supply Chain of Foreign Trade Wine Driven by Blockchain and IoT. Business and Social Sciences Proceedings, 4, 57-65.
Gilbert, C., & Gilbert, M. A. (2025). Impact of General Data Protection Regulation (GDPR) on data breach response strategies (DBRS). International Journal of Research and Innovation in Social Science, 9(14), 760-784.
Tamana, S., Yiangou, K., Orphanou, K., Chatzimatthaiou, S., Kountouris, P., & Cremonesi, F. (2026). FAIR data gaps and collaboration willingness among hemoglobinopathy research centers. Scientific Data, 13(1), 582.
Yang, J. (2026). Stage‐Coupled Computational Framework for Stratified Accessibility and Equity Analysis in Community‐Based Elderly Care Services.
Zhang, Z. (2026). A Study on Return Optimization in E-commerce for Complex Consumer Goods Driven by Installation Information Quality. Available at SSRN 6734720.
Myeong, S., & Kanzamanova, R. (2026). When digital trust collapses: an exploratory comparative framework for citizen involvement in digital governance. Humanities and Social Sciences Communications.