Gwangju, South Korea

Gwangju Institute of Science and Technology (GIST)

Gwangju Institute of Science and Technology (GIST) is listed as QS 2026 rank =385. Gwangju Institute of Science and Technology (GIST) has 4 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Gwangju Institute of Science and Technology (GIST) is listed as QS 2026 rank =385. Gwangju Institute of Science and Technology (GIST) has 4 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Citation-ready summary

As of this public record, University AI Policy Tracker lists Gwangju Institute of Science and Technology (GIST) as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/gwangju-institute-of-science-and-technology-gist.json. The entity-level confidence is 86%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes Privacy claims.
  • Evidence includes Research claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims4Reviewed4Candidate0Official sources3

This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.

This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.

Policy profile

Deterministic source-backed dimensions derived from this record's public claims.

Coverage score80/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence71%

Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.

Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.

Coursework

Gwangju Institute of Science and Technology (GIST) has 1 source-backed public claim for coursework; deterministic analysis status: conditionally_allowed.

Conditionally AllowedMachine candidateConfidence73%Evidence1Sources1

Approved tools

No source-backed public claim identifying approved or licensed AI tools is present in this profile.

The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Teaching guidance

No source-backed public claim about teaching guidance is present in this profile.

The current public tracker record does not contain claim evidence about instructor, classroom, assessment-design, or syllabus guidance.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.

Evidence-backed claims

4 reviewed evidence-backed public claim

Academic Integrity

GIST's research misconduct reporting page lists reportable targets including fabrication, falsification, plagiarism, improper authorship, duplicate publication, investigation obstruction, serious departures from accepted academic norms, and coercing or proposing misconduct.

Review: Agent reviewedConfidence86%

Normalized value: research_misconduct_reporting_categories

Original evidence

Evidence 1
연구부정행위 신고대상 ‘위조’, ‘변조’, ‘표절’, ‘부당한 논문저자 표시’, ‘부당한 중복게재’, ‘연구부정 행위에 대한 조사 방해 행위’, 각 학문 분야에서 통상적으로 용인되는 범위를 심각하게 벗어난 행위, 타인에게 부정행위를 행할 것을 제안·강요·협박하는 행위

Localized display only

The page lists research misconduct reporting targets including fabrication, falsification, plagiarism, improper authorship, duplicate publication, investigation obstruction, serious departures from accepted norms, and proposing or coercing misconduct.

Privacy

For the NRF-scoped guidance relayed by GIST, the listed recommendations include not uploading evaluation materials to AI tools, indicating AI tool use, verifying reliability and validity, and caution about research-data leakage.

Review: Agent reviewedConfidence84%

Normalized value: nrf_genai_confidentiality_disclosure_validation_security_guidance

Original evidence

Evidence 1
○ 권고 내용 - (비밀유지) AI 도구에 평가자료 업로드 금지 - (정보공개) AI 도구 사용 내역 표기 권장 ※ 사용 시 표기 방식(예시) 마련 - (검증책임) AI 도구 사용 시 자료의 신뢰성, 타당성 확보를 위한 검증 책임 명시 - (보안책임) AI 도구에 연구자료 업로드 시 정보 유출 주의, 유출 시 연구자 책임 명시

Localized display only

The listed recommendations cover confidentiality, AI-use disclosure, validation responsibility, and security responsibility for research-data leakage.

Research

GIST's Research Office notice relays NRF guidance for NRF project applicants, performers, and evaluators to use generative AI tools ethically and responsibly in related work.

Review: Agent reviewedConfidence82%

Normalized value: nrf_project_participants_responsible_genai_use_guidance

Original evidence

Evidence 1
한국연구재단에서 재단 과제의 신청·수행 및 평가 업무에 참여하는 연구자가 생성형 인공지능(AI) 도구를 "윤리적이고 책임있게" 사용하도록 『생성형 인공지능(AI) 도구의 책임 있는 사용을 위한 권고사항』 (개정판)을 마련하여 붙임과 같이 배포하오니 관련 업무시 활용하여 주시기 바랍니다.

Localized display only

The notice says NRF prepared revised recommendations so researchers participating in NRF application, performance, and evaluation work use generative AI tools ethically and responsibly, and asks users to apply them to related work.

Academic Integrity

GIST's undergraduate academic handbook lists academic and research-related disciplinary categories including exam-score manipulation or question leakage, cheating during exams, class disruption, academic warning, and research ethics violations.

Review: Agent reviewedConfidence78%

Normalized value: undergraduate_handbook_academic_research_discipline_categories

Original evidence

Evidence 1
2. 학업/연구 관련 가. 시험성적 조작 및 문제 유출 나. 시험 중 부정행위 다. 수업방해 라. 학사경고 마. 연구윤리 위반

Localized display only

The handbook's academic/research discipline section lists score manipulation or exam-question leakage, cheating during exams, class disruption, academic warning, and research ethics violations.

Candidate claims

0 machine or needs-review claim

Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.

Official sources

3 source attribution

Change log

Source-check timeline and diff-style claim/evidence preview.

View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

Corrections and missing evidence

Corrections create review tasks and do not directly change this public record.

If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.

Back to universities