In-person examinations at Princeton will be proctored starting July 1
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2026 年 5 月 11 日,Princeton University 的教职员工投票决定自 7 月 1 日起对所有线下考试强制实施监考,结束自 1893 年以来持续了 133 年的荣誉制度。该政策以仅一票反对获得通过,要求教师在考场内作为见证人,但不得干预学生答题。监考人员将记录疑似违规行为并上报由学生组成的 Honor Committee,必要时可出庭作证。此举是在数月讨论后做出的,主要由对学术诚信日益担忧所驱动,尤其是人工智能工具和个人电子设备的普及使作弊更难被察觉。
最初的荣誉准则是在学生请愿取消监考后制定的;一个多世纪以来,Princeton 的制度依赖个人自律与同伴举报。但新政策指出,观察不当行为越来越困难,且学生因担心网上曝光或人肉搜索而不愿直接举报同伴。 2025 年高年级学生调查显示,近 30% 的受访者承认曾作弊,44.6% 的人知道违规行为却选择不举报,仅有 0.4% 的人曾举报过同伴。这些趋势,加上生成式 AI 等新挑战,促使学校转向正式监考。
该提案由学院院长 Michael Gordin 牵头,得到了包括 Honor Committee 、本科生院长办公室和 Undergraduate Student Government 在内的主要学生与教职团体的支持。虽然部分学生和教职员担心监考会削弱信任,但也有人认为这是必要的调整。 2026 年 11 月已有一项政策要求对个人和小组考试实施监考,为这次更广泛的改变奠定了基础。 Honor Committee 的章程将保持不变,但学校中关于禁止监考的规定会相应更新以反映新要求。
支持者认为,监考虽不能完全杜绝作弊,但能起到威慑作用,并减轻学生在考试期间监督同伴的负担。前 Honor Committee 主席 Nadia Makuc '26 表示,委员会长期考虑将监考人员作为额外见证人,尤其是在案件增加和 AI 带来新问题的情况下。前同伴代表联合主席 William Aepli '26 预计,听证会上呈交的证据类型将发生变化。教职员工反应不一,教授 Jill Dolan 称此举"虽遗憾,但有必要",并承认这标志着 Princeton 文化的一次重大转变。
On May 11, 2026, Princeton University faculty voted to mandate proctoring for all in-person examinations starting July 1, ending a 133-year-old honor system that had relied on student self-governance since 1893. The policy, passed with only one opposing vote, requires instructors to be present in exam rooms as witnesses but prohibits them from interfering with students. Suspected violations will be documented by proctors and reported to the student-run Honor Committee, where they may later testify. This change follows months of deliberation driven by rising concerns over academic integrity, particularly due to the proliferation of AI tools and personal electronic devices that make cheating harder to detect.
The original Honor Code was established after a student petition to eliminate proctoring, and for over a century, Princeton's system depended on individual accountability and peer reporting. However, the new policy cites increased difficulty in observing misconduct and a growing reluctance among students to report peers directly, fueled by fears of online shaming or doxxing. A 2025 Senior Survey found that nearly 30% of respondents admitted to cheating, while 44.6% knew of violations they chose not to report, and only 0.4% had ever reported a peer. These trends, combined with challenges like generative AI, prompted the shift toward formal supervision.
The proposal, led by Dean of the College Michael Gordin, received endorsements from key student and faculty groups, including the Honor Committee, the Office of the Dean of Undergraduate Students, and the Undergraduate Student Government. While some students and faculty expressed concern that proctoring could erode trust, others supported it as a necessary adaptation. A November 2026 policy had already mandated proctoring for individual and small-group exams, setting the stage for this broader change. The Honor Committee Constitution remains unchanged, but university rules banning proctoring will be updated to reflect the new requirement.
Proponents argue that while proctoring won't eliminate cheating, it will serve as a deterrent and reduce pressure on students to monitor peers during exams. Former Honor Committee Chair Emerita Nadia Makuc '26 noted that the committee had long considered adding proctors as additional witnesses, especially given recent strains like increased case loads and AI-related challenges. William Aepli '26, former co-chair of the Peer Representatives, anticipated changes in the types of evidence presented in hearings. Faculty reactions were mixed, with Professor Jill Dolan calling the move "a shame, but necessary," acknowledging it marks a significant cultural shift for Princeton.
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• Princeton 大学的荣誉准则依赖学生自我监督而非监考人员,目前正面临危机——调查显示 29.9% 的高年级学生承认作弊,44.6% 的人知道违规却没有举报,这些数字自 2022 年以来持续上升。
• COVID-19 大流行标志着学术诚信的重要转折:远程教学削弱了师生之间的社会联系,使大学体验更趋功利化,同时技术手段也让作弊变得更容易。
• 美国更广泛的文化转变正在侵蚀社会契约,个人主义占据主导,个人进步常被用来为不诚实行为辩护,影响从学术到企业再到政治领域。
• 随着 ChatGPT 等 AI 工具的出现,作弊的便利性急剧增加;这些工具能解决本科水平的问题,再加上学生长期使用手机进行隐蔽操作的经验,使得传统的荣誉准则越来越难以维持。
• 历史上,荣誉准则旨在将"学生对抗教师"的对立转化为"荣誉对抗作弊者"的关系,但外部因素使旧有的对抗心态重新抬头,破坏了这一制度。
• 关于举报作弊的争论凸显了朋友忠诚与制度诚信之间的张力:很多人认为在普遍作弊的背景下,作弊不足以断绝友谊;另一些人则认为包庇蓄意的不诚实已超出忠诚的范畴。
• 一些人捍卫荣誉制度,认为它能塑造品格、营造高信任社区并降低管理成本,主张把学生视为值得信赖的人有助于培养道德;但批评者反驳称,当近 30% 的学生承认不诚实时,继续信任学生是天真的。
• 大学学位被视为经济未来的"成败关键",学生感受到的风险骤增,导致绝望式的"求生"行为:一次考试失利可能令毕业推迟、损失数万美元,因此作弊在理性计算下显得可理解。
• 精英院校在维护品牌价值与学术诚信之间面临紧张局面:放任作弊会摧毁学历的价值,但分数膨胀和普遍作弊已削弱了名校高 GPA 的含义。
• 作弊规范存在文化与国际差异:有人指出国际学生的学术背景和语言挑战不同,影响其合作方式,尽管数据显示在西方大学中国际学生的作弊率更高。
讨论揭示了学术诚信中理想主义与实用主义的根本张力。参与者普遍认为荣誉准则在过去曾有效,但在当前环境下正逐渐失效:COVID 期间社会联系的瓦解、 AI 驱动的作弊手段以及更广泛的个人主义文化,共同创造了使自我监督变得不切实际的条件。尽管有人坚持认为信任能塑造品格、反对以监考为主的"军备竞赛",但广泛的作弊证据已让多数人相信需要结构性变革。对话还凸显了学术不端如何反映并强化更广泛的社会趋势——当风险高或被发现的可能性低时,不诚实行为更易被视为可接受。 • Princeton's honor code system, which relies on student self-policing rather than proctors, is facing a crisis as surveys show 29.9% of seniors admitted to cheating and 44.6% knew of violations they didn't report, with these numbers rising steadily since 2022.
• The COVID-19 pandemic marked a significant shift in academic integrity, as remote learning broke the social connection between students and professors, making college feel more transactional and enabling easier cheating through technology.
• A broader cultural shift in America has eroded the social contract, with individualism now dominating to the point where personal advancement justifies dishonesty, affecting everything from academic cheating to corporate behavior and politics.
• The ease of cheating has increased dramatically with AI tools like ChatGPT, which can solve undergraduate-level problems, combined with students' decade-long experience using phones discreetly, making traditional honor codes increasingly unenforceable.
• Historical context shows the honor code was originally implemented to transform a "students vs faculty" mentality into an "honor vs cheaters" dynamic, but external factors have caused the old adversarial mentality to resurface, undermining the system.
• The debate over reporting cheating reveals a tension between loyalty to friends and institutional integrity, with many arguing that cheating in a widespread context isn't severe enough to justify ending friendships, while others maintain that protecting deliberate dishonesty goes beyond loyalty.
• Some defend honor systems as building character and creating high-trust communities that reduce overhead, arguing that treating students as trustworthy helps develop moral character, though critics counter that continuing to trust students when 30% admit dishonesty is naive.
• The perceived stakes of college have increased dramatically, with students viewing degrees as "make or break" for their financial future, creating desperate "survival" behavior where cheating seems rational given that one bad test can cost tens of thousands in delayed graduation.
• Elite institutions face a tension between maintaining their brand value and academic integrity, as "letting cheaters cheat" would destroy the credential's worth, yet grade inflation and cheating already undermine the meaning of high GPAs from prestigious schools.
• Cultural and international differences in cheating norms exist, with some noting that international students may have different academic backgrounds and language challenges that affect collaboration styles, though data shows higher cheating rates among international students at Western universities.
The discussion reveals a fundamental tension between idealism and pragmatism in academic integrity, with participants broadly agreeing that honor codes worked in the past but are failing in the current environment. The erosion of social bonds during COVID, combined with AI-enabled cheating and a broader cultural shift toward individualism, has created conditions where self-policing becomes impractical. While some maintain that trust builds character and that proctoring represents a dehumanizing arms race, the empirical evidence of widespread cheating has convinced most that structural changes are necessary. The conversation also highlights how academic dishonesty reflects and reinforces broader societal trends, with the behavior of leaders and institutions signaling that dishonesty is acceptable when the stakes are high or detection unlikely.