Beijing, China (Mainland)

Beijing Institute of Technology

Beijing Institute of Technology is listed as QS 2026 rank =259. Beijing Institute of Technology 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

Beijing Institute of Technology is listed as QS 2026 rank =259. Beijing Institute of Technology 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 Beijing Institute of Technology 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/beijing-institute-of-technology.json. The entity-level confidence is 90%. 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.

Claim coverage4 reviewedSource languagezhPublic JSON/api/public/v1/universities/beijing-institute-of-technology.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes Teaching claims.
  • No specific AI service name is highlighted by the current 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 score45/100Coverage labelpartial public coverageReview: Machine candidateAnalysis confidence76%

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.

Policy presence

No source-backed public AI policy or guidance record is present in this profile.

The current public tracker record does not contain a source-backed claim that establishes a policy or guidance source.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

AI disclosure

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Privacy and data entry

No source-backed public claim about privacy or data-entry restrictions is present in this profile.

The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

Named AI services

No source-backed public claim naming a specific AI service is present in this profile.

The current public tracker record does not contain claim evidence naming a specific AI service.

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

Beijing Institute of Technology requires graduate students to observe its academic ethics code and says violations of academic integrity are handled under the university academic misconduct rules.

Review: Agent reviewedConfidence90%

Normalized value: Graduate academic integrity obligations and misconduct handling

Original evidence

Evidence 1
研究生应自觉遵守《北京理工大学学术道德行为规范》。学校以适当方式记录学生学业、学术、品行等方面的诚信信息,建立对失信行为的约束和惩戒机制;对有严重失信行为的,可以给予相应的纪律处分,对违背学术诚信的,按照《北京理工大学关于学术不端行为认定和处理规定》处理。

Localized display only

The graduate management rule tells graduate students to observe academic ethics rules and ties academic integrity violations to the university academic misconduct procedure.

Academic Integrity

Beijing Institute of Technology academic misconduct rules apply to teaching and research staff, management staff, students, and others conducting academic activities under the university name.

Review: Agent reviewedConfidence90%

Normalized value: Academic misconduct rule scope

Original evidence

Evidence 1
第三条 本规定适用于北京理工大学教学科研人员(含博士后)、管理人员和学生,以及以北京理工大学名义从事学术活动的其他各类人员(如退休教职工、访问学者、进修教师、兼职人员、以同等学力申请硕士或博士学位人员等)。

Localized display only

The 2025 rule states its scope across staff, students, and others conducting academic activities under BIT name.

Teaching

Beijing Institute of Technology Graduate School says 2026 graduate program plans should add public foundational AI courses for all graduate students, with students required to take the appropriate tier according to program training requirements.

Review: Agent reviewedConfidence88%

Normalized value: Graduate AI public foundational courses required by training tier

Original evidence

Evidence 1
面向全体研究生开设人工智能课程,分 AI 通识课( 16 学时 1 学分)、 AI 进阶课( 16 学时 1 学分)、 AI 精通课( 16 学时 1 学分)。各学科(领域)的研究生根据培养要求,必修相应阶段的课程。

Localized display only

The Graduate School notice says AI courses are opened to all graduate students and required by each program's training requirements.

Academic Integrity

Beijing Institute of Technology identifies buying or selling research data and buying, ghostwriting, or proxy-submitting papers or project application/acceptance materials as conduct contrary to academic ethics.

Review: Agent reviewedConfidence88%

Normalized value: Examples of academic misconduct

Original evidence

Evidence 1
第十五条 其他违背学术界公认的学术道德规范的行为:(二)买卖实验研究数据,买卖、代写、代投论文或项目申报验收材料等;

Localized display only

The 2025 rule lists buying/selling data and buying, ghostwriting, or proxy-submitting papers or project materials as misconduct examples.

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.

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