A Study on the Development of Government-Recommended Standard Design Tools through the Analysis of Components of University Generative AI Usage Guidelines

Abstract

This study raises the issue of institutional disparities in university generative AI usage guidelines in response to the diffusion of generative AI and pushes for effective standards governing generative AI usage. Accordingly, this study aims to analyze generative AI usage guidelines of Korean universities to derive their core components, present types according to the levels of inclusion and elaboration of components and patterns of integration, and propose an analytical framework and implications to support the design of government-recommended standards premised on universities’ autonomous application. The results show that the core components of university generative AI usage guidelines are derived as six elements: (1) the presentation of the concept, characteristics, and limitations of generative AI; (2) purposes of use and application domains; (3) support for practical uses; (4) stakeholder-specific guidelines; (5) ethical and accountability norms; and (6) operational and management support. In addition, the types of university generative AI usage guidelines are classified into four categories—minimal guidance and responsibility-oriented, practice-support-oriented, operation and quality management–enhanced, and comprehensive manual and tool package—according to the ways in which components are integrated and their sub-elements. Based on these findings, this study develops evaluation tables and rubrics that present criteria for component levels of elaboration and coupling domains and strength of coupling to ensure operational effectiveness, and proposed them as a government-recommended standard design tool. Furthermore, from a governance perspective, this study presents governmental implications for supporting public quality management while respecting university autonomy. These findings provide policy and academic implications in that they present the minimum standards that university generative AI usage guidelines should comprise from a governance perspective that supports both university autonomy and public quality management, and propose an effective design.

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