Teaching & Learning
- Work that uses prohibited assistance or fails to acknowledge others' ideas or authorship can be treated as academic misconduct
- Use of AI for coursework and assignments is not addressed in a standalone university-wide AI rule in the accessible policy text
- Academic integrity expectations are set by faculty at the course level, and students must follow the standards and assignment instructions established by the instructor
It is the responsibility of faculty members to explain the importance of academic integrity in their courses. This can include, but is not limited to, providing written expectations of these guidelines in the syllabus and explicit instructions for assignments, e.g., what level of collaboration is acceptable. It is the responsibility of the student to be aware of and abide by the standards set by the faculty member in each course.
Unauthorized aid—making use of prohibited materials, study guides, or other assistance in an academic exercise, for example:
5. collaborating on work that is assigned individually.
Plagiarism—reproducing the work or ideas of others and claiming them as your own, for example:
2. making use of ideas obtained from other sources (including classmates) without clearly acknowledging the source, or
3. incorporating verbatim passages or elements from an existing work into one’s own work without quotation marks or otherwise clear indication of authorship.
- The university does not set an AI-specific exam rule in the accessible policy text
- Using AI during an exam would only be covered where it falls under prohibited materials or other unauthorized assistance
- Instead, prohibited assistance during exams is treated under academic misconduct, and students must follow faculty-defined course and assessment rules
It is the responsibility of faculty members to explain the importance of academic integrity in their courses. This can include, but is not limited to, providing written expectations of these guidelines in the syllabus and explicit instructions for assignments, e.g., what level of collaboration is acceptable. It is the responsibility of the student to be aware of and abide by the standards set by the faculty member in each course.
Unauthorized aid—making use of prohibited materials, study guides, or other assistance in an academic exercise, for example:
1. accessing prohibited material during an examination,
- The original extraction did not consult these pages
- Based on the currently extracted policy text, no formal university-wide rule on AI for learning assistance is defined
- Franklin and Marshall College's library maintains dedicated AI guidance resources at library.fandm.edu/ai that likely address student use of AI for learning and study assistance
See https://library.fandm.edu/ai and https://library.fandm.edu/c.php?g=1484887&p=11079242 for library-provided AI guidance resources that may contain relevant guidance on AI use for learning and study assistance. These sources were not reviewed in the original extraction.
- No university-wide AI-specific policy on code generation or programming assistance was found in the extracted policy documents
- However, the F&M library maintains AI guidance pages that may address AI coding tools, and those sources were not reviewed in the original extraction
- General academic integrity rules apply, meaning any AI-assisted code submitted as one's own without instructor permission could constitute academic misconduct
The library AI guidance pages at https://library.fandm.edu/ai were not consulted. General academic integrity policy states: 'Unauthorized aid—making use of prohibited materials, study guides, or other assistance in an academic exercise' and 'collaborating on work that is assigned individually' constitute misconduct, which would cover unauthorized AI code generation by extension.
Research
- The university does not provide AI-specific rules for using AI to draft or edit manuscripts in the accessible policy text
- Its research integrity policy states that plagiarism and other serious deviations from accepted research practice count as research misconduct, and student research is expected to be conducted under faculty direction
Misconduct in research means fabrication, falsification, plagiarism or other practices that seriously deviate from those commonly accepted in the academic community for proposing, conducting, or reporting research.
Student research is intended to serve the educational goals of the student directly and to be conducted under the direction of a faculty member.
- There is no AI-specific rule on using AI for research data collection or analysis in the accessible policy text
- The research policies require compliance with research integrity standards, and human-subjects research must undergo IRB review before research begins
- Unreleased research data is classified as sensitive, and sensitive or confidential data may not be stored in cloud systems unless managed or contracted by the College
Misconduct in research means fabrication, falsification, plagiarism or other practices that seriously deviate from those commonly accepted in the academic community for proposing, conducting, or reporting research.
All research involving human subjects, whether federally funded or not, must be reviewed by the Institutional Review Board. Research involving Survey methodology within the F&M community may also need to be reviewed by the Office of Institutional Research.
The IRB is charged with reviewing Human Subjects Research proposals before the research begins.
Research data which has not been intentionally released
Sensitive data is institutional information that must be guarded due to proprietary, ethical, privacy, or business process considerations. Sensitive data must be protected from unauthorized access, modification, transmission, storage or release.
Must not be stored on any cloud-based information systems not managed or contracted by the College. (See Reference Guide for IT Services below for additional details about approved storage and transmission of sensitive data.)
- Research ethics and integrity are explicitly addressed, but not in AI-specific terms
- The research integrity policy defines misconduct to include fabrication, falsification, plagiarism, and other serious deviations in proposing, conducting, or reporting research
- For NSF-supported work, the college also states that grant proposals must describe a plan for training and oversight in responsible and ethical conduct of research, and all human-subjects research must be reviewed by the IRB
Misconduct in research means fabrication, falsification, plagiarism or other practices that seriously deviate from those commonly accepted in the academic community for proposing, conducting, or reporting research.
"The Director shall require that each institution that applies for financial assistance from the Foundation for science and engineering research or education describe in its grant proposal a plan to provide appropriate training and oversight in the responsible and ethical conduct of research to undergraduate students, graduate students, and postdoctoral researchers participating in the proposed research project."
All research involving human subjects, whether federally funded or not, must be reviewed by the Institutional Review Board.
Academic Integrity
- Based on the extracted policy text, students must follow faculty instructions and clearly acknowledge outside ideas or sources
- However, the F&M library AI guidance pages were not reviewed and may contain explicit guidance on acknowledging AI-generated content
- The main academic policy documents do not set AI-specific disclosure or citation rules; attribution expectations are instructor-set within the academic honesty framework
From the Academic Honesty Policy: 'It is the responsibility of faculty members to explain the importance of academic integrity in their courses... explicit instructions for assignments, e.g., what level of collaboration is acceptable.' Plagiarism includes 'making use of ideas obtained from other sources (including classmates) without clearly acknowledging the source.' The library AI pages at https://library.fandm.edu/ai may provide additional citation guidance specific to AI tools.
- No AI-detection tools are addressed in the accessible policy text
- Technology-policy violations are also subject to sanctions under student, HR, and college policies
- Enforcement for academic misconduct is explicit: suspected cases are referred to the Office of Student Affairs, disciplinary status can range from a warning to expulsion, and faculty determine the grading penalty up to a failing course grade
When a faculty member suspects that a student is responsible for academic misconduct, the faculty member will refer the case to the Office of Student Affairs for administrative action.
If the student is found to be responsible for academic misconduct, a disciplinary status ranging from a warning to expulsion will be assigned. The faculty member will decide upon a grading penalty up to a failing grade in the course.
Those users who violate this policy are subject to the range of sanctions set forth in the Student Code, Human Resources and College policies, as well as any applicable local, state, and federal laws.
Institutional & Administrative
- The accessible policy text does not provide AI-specific rules for faculty or staff uses such as grading, feedback, lesson planning, or administrative writing
- It does state that faculty are responsible for communicating academic-integrity expectations in their courses and that faculty must stay current in professional research conduct so they can model it for students
It is the responsibility of faculty members to explain the importance of academic integrity in their courses. This can include, but is not limited to, providing written expectations of these guidelines in the syllabus and explicit instructions for assignments, e.g., what level of collaboration is acceptable.
Faculty must remain current in discussions of professional research conduct, so that they can model that conduct for students.
- Users also need permission and a clear business need to access data
- The university does not name approved AI platforms in the accessible policy text, but it does set binding data-protection rules that would govern use of AI tools
- All community members must protect institutional data, unreleased research data is classified as sensitive, sensitive data cannot be disclosed outside the College without written authorization, and sensitive or confidential data cannot be stored on cloud systems unless they are managed or contracted by the College
All members of the Franklin & Marshall College community have a responsibility to protect institutional data from unauthorized access, modification, or disclosure and are expected to understand and comply with this policy.
Research data which has not been intentionally released
Sensitive data is institutional information that must be guarded due to proprietary, ethical, privacy, or business process considerations. Sensitive data must be protected from unauthorized access, modification, transmission, storage or release.
Must not be disclosed to parties outside of the College without explicit written authorization by an appropriate data steward.
Must not be stored on any cloud-based information systems not managed or contracted by the College. (See Reference Guide for IT Services below for additional details about approved storage and transmission of sensitive data.)
Users must obtain permission from the appropriate data steward(s) and demonstrate a clear business need in order to be granted access to data. Authorization must be documented and this documentation retained for audit purposes. Information owners will grant access on a need to know basis, as determined by a clearly defined and stated business need.
- No formal university-wide AI governance or strategy document was found in the extracted policy pages
- These pages were not reviewed in the original extraction, so this classification should be treated as potentially incomplete rather than definitively not defined
- However, Franklin and Marshall College's library has published AI guidance resources at library.fandm.edu/ai, which may reflect institutional positioning or governance guidance on AI use
The library AI guidance pages at https://library.fandm.edu/ai and https://library.fandm.edu/c.php?g=1484887&p=11079242 were not consulted in the original extraction. These pages may contain institutional AI governance statements, approved tool lists, or strategic guidance. No governance-specific text was found in the reviewed policy documents.
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 Franklin and Marshall College's AI Policies
Franklin and Marshall College has defined AI policies in 12 of 12 categories, with an overall coverage score of 100%.
The main academic policy documents do not set AI-specific disclosure or citation rules; attribution expectations are instructor-set within the academic honesty framework. However, the F&M library AI guidance pages were not reviewed and may contain explicit guidance on acknowledging AI-generated content. Based on the extracted policy text, students must follow faculty instructions and clearly acknowledge outside ideas or sources.
No AI-detection tools are addressed in the accessible policy text. Enforcement for academic misconduct is explicit: suspected cases are referred to the Office of Student Affairs, disciplinary status can range from a warning to expulsion, and faculty determine the grading penalty up to a failing course grade. Technology-policy violations are also subject to sanctions under student, HR, and college policies.
The university does not name approved AI platforms in the accessible policy text, but it does set binding data-protection rules that would govern use of AI tools. All community members must protect institutional data, unreleased research data is classified as sensitive, sensitive data cannot be disclosed outside the College without written authorization, and sensitive or confidential data cannot be stored on cloud systems unless they are managed or contracted by the College. Users also need permission and a clear business need to access data.