Teaching & Learning
- Whether AI use is allowed for graded work depends on whether an instructor has authorized it and whether the work is represented honestly
- The university does not provide an AI-specific rule for coursework in the provided sources, but it does state that submitting work that is not one's own or getting unauthorized help is academic dishonesty
Cheating: to claim as one’s own work which one has not done, or to submit as one’s own work a group assignment without participating acceptably in the project.
Plagiarism: to take ideas, writings, words, or anything else from another and to pass these off as one’s own by failing to give credit to the source.
Any student who assists another student in violating any of the above regulations shall also be considered to have committed an infraction of the Academic Honor Code.
- The university does not set an AI-specific examination rule in the provided sources
- Its academic integrity policy prohibits unauthorized assistance and claiming work as one's own, so AI use during exams or assessments would be governed only insofar as it falls under those general rules or specific instructor directions
Cheating: to claim as one’s own work which one has not done, or to submit as one’s own work a group assignment without participating acceptably in the project.
Any student who assists another student in violating any of the above regulations shall also be considered to have committed an infraction of the Academic Honor Code.
Research
Academic Integrity
- The rule is framed as a general attribution requirement under plagiarism policy
- The university requires students to give credit when using another source's ideas, writings, or words, but the provided sources do not contain AI-specific disclosure or citation instructions
Plagiarism: to take ideas, writings, words, or anything else from another and to pass these off as one’s own by failing to give credit to the source.
- The university describes academic misconduct procedures and sanctions, but it does not mention AI-detection tools in the provided sources
- Suspected misuse would be handled through the ordinary Academic Honor Code process, which includes reporting, board review, and possible sanctions up to expulsion
A student or faculty member who suspects an Honor Code infraction should report the allegation to the dean of the faculty.
The dean of the faculty will investigate the case and determine if the matter should be resolved administratively or if there are grounds to convene the Judicial Board. The accused student will be informed of the allegation and the proceedings.
The possible sanctions are as follows: reduced grade on assignment, reduced grade for course, failure in the course, disciplinary probation, suspension, or expulsion from the university.
A grade of F due to a violation of the Academic Honor Code is a grade for the course itself, but the transcript is marked with an asterisk indicating that the course failure was due to a violation of the Academic Honor Code.
Institutional & Administrative
- The university does not name approved AI platforms, but it does impose general data protection and system-use limits that would apply to entering university information into external tools
- Users may not expose confidential institutional data without authorization, and university technology resources must be used in ways consistent with privacy, security, and legal requirements
Users are prohibited from using University technology resources to violate the rights of any person or company protected by copyright, trade secret, patent or other intellectual property or similar laws or regulations, including but not limited to the installation or distribution of pirated or other software products that are not appropriately licensed for use by Lawrence.
Users are prohibited from divulging any confidential, proprietary or private information, unless properly authorized.
Protecting information privacy and ensuring the cybersecurity of both technical and non-technical systems is a top priority at Lawrence University.
We restrict access to personal information to individuals who need access to perform their official University duties and obligations, except as otherwise provided by law.
No one should expect privacy over information stored on or sent through university technology systems, except as required by law.
DocuMark: Responsible AI Use for Academic Integrity
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Common Questions About Lawrence University's AI Policies
Lawrence University has defined AI policies in 5 of 12 categories, with an overall coverage score of 42%.
The university requires students to give credit when using another source's ideas, writings, or words, but the provided sources do not contain AI-specific disclosure or citation instructions. The rule is framed as a general attribution requirement under plagiarism policy.
The university describes academic misconduct procedures and sanctions, but it does not mention AI-detection tools in the provided sources. Suspected misuse would be handled through the ordinary Academic Honor Code process, which includes reporting, board review, and possible sanctions up to expulsion.
The university does not name approved AI platforms, but it does impose general data protection and system-use limits that would apply to entering university information into external tools. Users may not expose confidential institutional data without authorization, and university technology resources must be used in ways consistent with privacy, security, and legal requirements.