Policy presence
Shanghai Jiao Tong University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Open, evidence-backed AI policy records for public reuse.
Shanghai, China (Mainland)
Shanghai Jiao Tong University is listed as QS 2026 rank =47. Shanghai Jiao Tong University 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.
v1 public contract
Shanghai Jiao Tong University is listed as QS 2026 rank =47. Shanghai Jiao Tong University 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.
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.
Deterministic source-backed dimensions derived from this record's public claims.
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.
Shanghai Jiao Tong University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Shanghai Jiao Tong University has 3 source-backed public claims for coursework; deterministic analysis status: required.
Shanghai Jiao Tong University has 3 source-backed public claims for exams; deterministic analysis status: required.
Shanghai Jiao Tong University has 1 source-backed public claim for privacy and data entry; deterministic analysis status: recommended.
Shanghai Jiao Tong University has 1 source-backed public claim for academic integrity; deterministic analysis status: required.
Shanghai Jiao Tong University has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.
Shanghai Jiao Tong University has 1 source-backed public claim for named ai services; deterministic analysis status: unclear.
Shanghai Jiao Tong University has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
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.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
4 reviewed evidence-backed public claim
Ai Tool Treatment
Normalized value: four_tier_ai_use_classification_in_education
Original evidence
Evidence 1第六条 根据应用风险的差异,本规范将高等教育教学领域的人工智能应用划分为四 种类型:禁止使用、有限使用、鼓励使用、开放使用,从而推进“AI+教育教学”分级分 类改革。
Teaching
Normalized value: teachers_are_primary_responsible_persons_for_ai_teaching_design
Original evidence
Evidence 1第九条 教师是 AI+教学设计的第一责任人,应在遵守教育教学相关规章制度要求的 前提下,合理、合规、有效使用人工智能技术产品或服务,必要时提供人工智能测试验证 报告及备案,包括平台选择、使用范围及方式,并围绕场景应用、风险事项提示、应急预 案等各环节设置具体规范。对于使用未备案或存在风险的人工智能工具情况,学校可追究 相关责任。
Original evidence
Evidence 2高校老师在教学过程中使用生成式人工智能工具的指导性原则: 1. 保障数据的隐私与安全。教师需要清晰了解生成式人工智能工具所具有 的信息泄露方面的风险,并清晰了解生成式人工智能工具对服务中产生的数据 信息、输出等享有的权利。
Academic Integrity
Normalized value: students_must_follow_course_ai_use_rules_and_academic_integrity_requirements
Original evidence
Evidence 1第十三条 学生应了解并遵守各项课程的人工智能使用规范,在课堂学习、作业反馈 等环节,遵循教学计划、知识产权等法律法规、学术诚信要求。若有违规行为,学校将追 究相关责任。
Original evidence
Evidence 2学术不端一般包括以下行为:在作业或考试中作弊,包括未经授权使用在线 学习支持平台;在学术工作上进行未经授权的合作,包括在未经教师批准的在线 学习支持平台上发布学生完成的课程作业;未经教师许可获取或使用课程材料, 包括使用在线学习平台发布教师提供的课程材料等。
Other
Normalized value: ai_education_principles_human_centered_learning_centered
Original evidence
Evidence 1第五条 上海交通大学“AI+教育教学”各方主体应遵循以下基本原则: (一)技术以人为本、以学为本。围绕“让每个学生更优秀”育人理念,发展应用 有利于学生知识能力增长、有利于教师教学育人的人工智能技术。
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.
3 source attribution
sjtu.edu.cn
ctld.sjtu.edu.cn
ctld.sjtu.edu.cn
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.
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.