Ashland University has defined AI policies across 8 of 12 policy categories, covering Academic Integrity, Institutional & Administrative, Research, Teaching & Learning. AI tools are generally permitted in coursework, subject to instructor guidelines. Students are required to disclose and attribute AI-generated content in their academic work. The university employs detection and enforcement mechanisms for unauthorized AI use. Research-related AI policies address manuscript preparation, data analysis, research ethics. At the institutional level, the university has established guidelines for data protection and approved AI tools.
The work that one submits for academic evaluation must be his/her own unless an instructor expressly permits certain types of collaboration.
D. Submitting as one’s own any academic assignment (e.g. written work, painting, sculpture, etc.) prepared totally or in part by another.
In addition to submitting the Academic Integrity Incident Report the faculty member should take such action as is deemed appropriate and pursuant to any stated policy of the faculty member and/or department, if any. Such action may be, but is not limited to, assigning a grade of zero for the assignment or test involved, assigning an F for the course, suspension from the major, or permanent dismissal from the major.
G. Taking a test (or other evaluation) for someone else or permitting someone else to take a test for oneself.
C. Using notes, textbooks or other information in homework, examinations, tests or quizzes, except as expressly permitted.
D. Securing, giving or exchanging information during examinations without authority to do so.
A. Obtaining confidential information about, examinations tests or quizzes other than that released by the instructor.
Proper acknowledgment of ideas and sources is central to academic honesty.
Plagiarism is the intentional or unintentional presentation of someone else’s words, ideas or data as one’s own work.
If the work of another is used, acknowledgment of the original source must be made through a recognized documentation practice.
Fabrication is the intentional falsification or invention of research, data, citations, or other information.
C. Inventing or altering data or source information for research or other academic exercise.
Fabrication is the intentional falsification or invention of research, data, citations, or other information.
A. Citing information not taken from the source indicated.
B. Including in a reference list sources which have not been consulted.
C. Inventing or altering data or source information for research or other academic exercise.
Proper acknowledgment of ideas and sources is central to academic honesty.
If the work of another is used, acknowledgment of the original source must be made through a recognized documentation practice.
A. Whenever one quotes another person’s actual words,
B. Whenever one uses another person’s idea, opinion or theory, even if it is completely paraphrased in one’s own words, or,
C. Whenever one borrows facts, statistics, or other illustrative materials, unless such information is of such common knowledge so as not to be questioned.
When a faculty member has observed a student violating any of the policies stated herein, an allegation of academic dishonesty shall be filed with Registrar.
When a proctor has observed a student violating any of the policies stated herein, the faculty member, under whose authority the proctor oversaw the academic activity, shall file an allegation of academic dishonesty with the Registrar.
Upon findings of an academic integrity violation, the student shall be placed on Academic Integrity Probation, and notification of that status shall be sent to the student’s academic advisor for placement in the academic advising folder.
Such action may be, but is not limited to, assigning a grade of zero for the assignment or test involved, assigning an F for the course, suspension from the major, or permanent dismissal from the major.
If the student is found by the Board to have committed a subsequent act of academic dishonesty, or multiple acts of academic dishonesty, the student under most circumstances shall be suspended from Ashland University for a period to be determined by the Board, but not to exceed two years.
3.3.1. Users must strictly comply with all restrictions relating to the use of AU Confidential Data, (e.g., Protected Health Information (PHI), Personally Identifiable Information (PII), or export-controlled data.
3.3.3. Users must comply with all requirements regarding retention, disclosure, and management of AU data, and return, upon request, any AU data that you place in a cloud service or other external repository.
3.4.1. You must not use AU IT resources to violate the privacy rights of anyone.
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.
Ashland University has defined AI policies in 8 of 12 categories, with an overall coverage score of 67%.
Ashland requires acknowledgment of original sources through recognized documentation practice when another’s words, ideas, or data are used. The university does not define an AI-specific disclosure statement requirement, but it does require attribution for borrowed material.
The policy establishes formal reporting, adjudication, and sanctions for academic dishonesty. Faculty or proctors file allegations with the Registrar, first offenses place students on Academic Integrity Probation and may carry assignment- or course-level penalties, and subsequent offenses are typically referred to the Academic Integrity Board and usually result in suspension.
The university requires all users to comply with restrictions on AU confidential data and with retention, disclosure, and management requirements for AU data, including data placed in cloud services or other external repositories. The policy does not identify approved AI platforms or AI-specific data-entry rules, but it clearly restricts handling of confidential and university data in external systems.
Disclaimer:* All university AI policy information presented on this platform is compiled from publicly available information, official university websites, and related academic sources. This data reflects information available at the time of last verification as on 27th February 2026. University and institution names referenced on this platform are the property and trademarks of their respective institutions. Their inclusion does not imply any affiliation with, endorsement by, or partnership with those institutions. Policy coverage scores and categorical indicators are automated assessments derived from available documentation and are provided for informational and comparative purposes only. They do not constitute legal, academic, or compliance advice. Users are advised to exercise their own judgement and independently verify all policy information directly with the respective university before making any academic or institutional decisions. For any queries or corrections, please contact us at support@trinka.ai