Teaching & Learning
- No university-wide AI-specific rule for coursework was found in the provided materials
- The university treats submitting work that is not one's own as academic dishonesty, including purchasing or using another person's work, but the provided sources do not expressly mention AI use for regular coursework or assignments
Academic Dishonesty. All forms of academic dishonesty are prohibited. Examples of academic dishonesty include, but are not limited to: ... 7. purchasing essays, term papers, or other materials and submitting them as one’s own work.
- The university prohibits using unauthorized materials or assistance during tests and examinations
- The sources do not explicitly reference AI tools in exam settings, but they do state a general ban on unauthorized assistance during assessments
Academic Dishonesty. All forms of academic dishonesty are prohibited. Examples of academic dishonesty include, but are not limited to: 1. cheating on tests, examinations, or other classroom work through the use of unauthorized materials
Research
- Therefore, no AI-specific research ethics rule is defined in the provided texts
- The university states that fabrication and falsification are prohibited and defines research misconduct in line with federal regulations, but the provided sources do not specifically address AI in research ethics, grant proposals, or IRB materials
Research Misconduct means fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. 42 C.F.R. Part 93, 42 C.F.R. Part 50 and 45 C.F.R. Part 689.
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.
Academic Integrity
- No explicit rule was found requiring students or researchers to disclose AI use
- The provided sources require students to submit their own work and prohibit plagiarism, but they do not define any AI-specific disclosure, citation, or attribution requirement
Academic Dishonesty. All forms of academic dishonesty are prohibited. Examples of academic dishonesty include, but are not limited to: ... 4. plagiarism, which is the appropriation of another’s work, words, or ideas and the unacknowledged incorporation of that work, words, or ideas into one’s own work offered for credit
- The provided sources do not mention AI detection tools or AI-specific detection practices
- The university provides academic misconduct enforcement procedures and allows penalties ranging from assignment failure to expulsion, with appeals through university processes
A student found guilty of academic dishonesty at Francis Marion University may receive one or more of the following penalties:
1. a reprimand;
2. a requirement that the work be repeated;
3. assignment of a grade of F for the work involved;
4. assignment of a grade of F for the course;
5. suspension from the University; or
6. expulsion from the University.
A student accused of academic dishonesty can appeal by following the grade appeals process in this handbook.
When a student is charged with a violation of the University’s Academic Integrity Policy, a hearing board may find the student responsible or not responsible, and may impose sanctions if appropriate.
Institutional & Administrative
- No explicit AI platform or data-classification policy was found in the provided materials
- The university has general privacy and confidentiality expectations for student information, including FERPA-related protections, but the provided sources do not define AI-specific data entry rules, approved AI platforms, or prohibited AI systems
Students have the right to confidentiality concerning any records maintained by the University that are directly related to the student. However, under the “academic need to know” provisions of FERPA, educational records may be accessed by students, faculty, staff and other University officials who have a legitimate interest in the student’s academic development, as defined by federal regulations.
Nursing students are expected to maintain the confidentiality of all patient information. Failure to comply with this policy is considered unsafe practice and may result in a student being removed from the clinical area and placed on immediate suspension.
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 Francis Marion University's AI Policies
Francis Marion University has defined AI policies in 6 of 12 categories, with an overall coverage score of 50%.
The provided sources require students to submit their own work and prohibit plagiarism, but they do not define any AI-specific disclosure, citation, or attribution requirement. No explicit rule was found requiring students or researchers to disclose AI use.
The university provides academic misconduct enforcement procedures and allows penalties ranging from assignment failure to expulsion, with appeals through university processes. The provided sources do not mention AI detection tools or AI-specific detection practices.
The university has general privacy and confidentiality expectations for student information, including FERPA-related protections, but the provided sources do not define AI-specific data entry rules, approved AI platforms, or prohibited AI systems. No explicit AI platform or data-classification policy was found in the provided materials.