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Optimization Study of Higher Education Data Governance in the Era of AI

Published: 30 May 2024 Publication History

Abstract

Artificial intelligence technology has opened up new horizons for higher education, but it has also increased the scale and complexity of higher education data, posing numerous challenges for data governance. Firstly, the issue of data dependency not only affects the data itself but also has a reciprocal effect on technological development. Secondly, information silos hinder effective data sharing and integration between different departments or institutions. Additionally, security issues of privacy require finding a balance in open data sharing. Based on three major issues, this article aims to provide a reasonable evaluation and improvement scheme for educational data governance in the era of AI. Based at the principles of safety, effectiveness, and openness, a Dynamic Evaluation Model for Higher Education Data Governance in the era of AI is established, relying on seven evaluation indicators and three stages of dynamic changes. This model will analyze the current situation of higher education in China and propose optimization recommendations.

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ICIEAI '23: Proceedings of the 2023 International Conference on Information Education and Artificial Intelligence
December 2023
1132 pages
ISBN:9798400716157
DOI:10.1145/3660043
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 May 2024

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