Teaching & Learning
- Use of AI in coursework is at instructor discretion rather than governed by a single university-wide rule
- The syllabus guidance tells faculty to state course-specific expectations, and the honor-system materials frame unauthorized assistance or submitting work not one's own as academic dishonesty
Because standards and expectations vary by discipline and assignment, instructors should decide and articulate what is acceptable in their context.
Rather than using broad statements like “no AI use” or “AI-generated text is prohibited,” consider language that describes what kinds of use are/aren’t acceptable and why.
Examples:
Students may use AI to help brainstorm topic ideas or review grammar, but all analysis and final writing must be their own.
For this coding assignment, use of GitHub Copilot is allowed only if you document where and how it was used.
The instructor should discuss these distinctions openly in class.
No student shall knowingly procure, provide, or accept any materials which contain questions or answers to any examination or assignment to be given at a subsequent time.
No student shall represent the work of others as his or her own.
No student shall knowingly submit false, misleading, or fabricated information, including forged or altered documents, in any academic matter.
- No AI-specific exam rule is stated, but AI use during assessments would be governed by instructor expectations and the broader academic honesty rules
- The university's honor-system policy prohibits obtaining, providing, or accepting materials containing exam or assignment questions or answers for later use
No student shall knowingly procure, provide, or accept any materials which contain questions or answers to any examination or assignment to be given at a subsequent time.
The various forms of academic dishonesty violate the principles of the Honor System. They include cheating, plagiarism, fabrication, and facilitating dishonesty by others.
- There is no single institution-wide student rule; expectations should be communicated in the syllabus and class discussion
- The college's AI teaching guidance allows instructors to permit limited AI use for learning support, such as brainstorming and grammar review, if they specify those boundaries
Because standards and expectations vary by discipline and assignment, instructors should decide and articulate what is acceptable in their context.
Examples:
Students may use AI to help brainstorm topic ideas or review grammar, but all analysis and final writing must be their own.
The instructor should discuss these distinctions openly in class.
- Programming-related AI use is at instructor discretion
- The teaching guidance provides an example in which GitHub Copilot is allowed for a coding assignment only if the student documents where and how it was used
Because standards and expectations vary by discipline and assignment, instructors should decide and articulate what is acceptable in their context.
Examples:
For this coding assignment, use of GitHub Copilot is allowed only if you document where and how it was used.
Research
- The college has research-integrity rules that prohibit fabrication, falsification, and plagiarism in proposing, performing, reviewing, or reporting research, but it does not explicitly mention AI
- Misconduct allegations must be handled under formal procedures, and research training emphasizes responsible conduct in areas such as data acquisition, authorship, peer review, and conflicts of interest
Research Misconduct means fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results.
Fabrication means making up data or results and recording or reporting them.
Falsification means manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record.
Plagiarism means the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.
The College and all College members must report observed, suspected or apparent Research Misconduct to the Research Integrity Officer.
Kalamazoo College values and promotes integrity and ethical behavior by all members of the Kalamazoo College community in all aspects of research and scholarly activity. This policy applies to all individuals at Kalamazoo College engaged in research or scholarly activity, regardless of the funding source.
As a condition of support, all grants or sponsored projects funded by the National Science Foundation (NSF) and National Institutes of Health (NIH) require training and oversight in the responsible and ethical conduct of research for undergraduate and graduate students, postdoctoral researchers, faculty and other senior personnel. Therefore, any faculty principal investigator (PI) applying for grants from these and all other federal granting agencies, and all Kalamazoo College personnel or students who receive support from grants funded by these agencies, are required to complete training in the ethical conduct of research.
Areas of research ethics identified by NSF and NIH include: mentor/trainee responsibilities and relationships, acquisition and management of data, ownership of data and intellectual property, publication practices and responsible authorship, peer review, collaborative science, conflicts of interest and commitment, research misconduct, and the responsible use of animals and human subjects in research.
Academic Integrity
- Disclosure of AI use is handled at the course level rather than through a single institution-wide citation rule
- The teaching guidance tells instructors to specify acceptable uses and includes an example requiring students to document AI assistance in coding assignments
Because standards and expectations vary by discipline and assignment, instructors should decide and articulate what is acceptable in their context.
Examples:
For this coding assignment, use of GitHub Copilot is allowed only if you document where and how it was used.
Rather than using broad statements like “no AI use” or “AI-generated text is prohibited,” consider language that describes what kinds of use are/aren’t acceptable and why.
- The college advises against relying on AI-detection tools as proof of misconduct and emphasizes dialogue, trust, and ordinary academic-integrity processes instead
- Suspected violations are addressed through the Honor System, which treats cheating, plagiarism, fabrication, and facilitating dishonesty by others as misconduct and routes cases to an Honor Board process
The session strongly discouraged relying on AI detection software as proof of misconduct, noting both high false positive rates and the danger of undermining trust between faculty and students.
Instead, participants emphasized designing assignments that foreground process, require reflection, and build in opportunities for revision and conversation.
Ultimately, the workshop reinforced the idea that our response to AI in education should be rooted in dialogue, trust, and pedagogical clarity rather than surveillance or fear.
The various forms of academic dishonesty violate the principles of the Honor System. They include cheating, plagiarism, fabrication, and facilitating dishonesty by others.
The student Honor System process at K starts with students, faculty, or staff filing a written complaint. Honor Board Co-Chairs investigate and decide whether to resolve the complaint administratively or refer the complaint to a hearing board.
Institutional & Administrative
- The provided sources do not set a broader formal policy for faculty or staff use of AI in grading, feedback, recommendation letters, or administrative communications
- Faculty are encouraged to establish and communicate clear course-specific rules on student AI use, and institutional teaching support emphasizes pedagogical clarity rather than surveillance
Because standards and expectations vary by discipline and assignment, instructors should decide and articulate what is acceptable in their context.
The instructor should discuss these distinctions openly in class.
Ultimately, the workshop reinforced the idea that our response to AI in education should be rooted in dialogue, trust, and pedagogical clarity rather than surveillance or fear.
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 Kalamazoo College's AI Policies
Kalamazoo College has defined AI policies in 8 of 12 categories, with an overall coverage score of 67%.
Disclosure of AI use is handled at the course level rather than through a single institution-wide citation rule. The teaching guidance tells instructors to specify acceptable uses and includes an example requiring students to document AI assistance in coding assignments.
The college advises against relying on AI-detection tools as proof of misconduct and emphasizes dialogue, trust, and ordinary academic-integrity processes instead. Suspected violations are addressed through the Honor System, which treats cheating, plagiarism, fabrication, and facilitating dishonesty by others as misconduct and routes cases to an Honor Board process.
No explicit data protection or approved AI platform policy is currently defined in the available policy sources.