Teaching & Learning
- The university does not define an AI-specific rule for coursework and assignments in the provided sources
- It does state that academic dishonesty, including plagiarism and misuse of another's intellectual property, is prohibited and subject to sanctions
No forms of academic dishonesty will be tolerated. Students are encouraged to help each other maintain these high
standards. All academic dishonesty should be reported to the faculty directly. Faculty, upon evidence of academic
dishonesty (cheating, plagiarism, or misuse of another’s intellectual property), either by voluntary confession, report of
another student, or on the basis of work submitted, must follow the procedure outlined in the Catalog (under Academic
Honesty). This includes but is not limited to a zero for the work involved, 10% course grade reduction, or a failing grade
for the course.
- The university does not define an AI-specific exam policy in the provided sources
- It does require protection of assessment integrity, states that faculty are encouraged to be present during exams, and says online exams should be safeguarded against dishonesty
No form of academic dishonesty will be tolerated. Students
are encouraged to help each other maintain these high
standards. All academic dishonesty observed should be
reported to the faculty directly. Faculty members are in
charge of their classrooms and are encouraged to be present
during exams. In the case of exams given outside of a
classroom setting (such as online), efforts should be made
to safeguard the integrity of the evaluation.
- The actual content of those pages should be reviewed to determine whether AI learning assistance guidance exists
- The university library appears to provide AI-related guidance for students via LibGuides pages; the original extraction did not consult these sources and marked this classification as not defined
Potentially relevant guidance exists at https://libguides.swu.edu/c.php?g=1412131&p=10458937 and https://libguides.swu.edu/c.php?g=1412131&p=10458938 but was not extracted; content from these pages must be reviewed before confirming this classification as not defined.
Research
- The university library maintains AI-related LibGuides pages that may address research writing and manuscript preparation; these were not reviewed in the original extraction, so this classification cannot be confirmed as not defined without reviewing those sources
Potentially relevant guidance exists at https://libguides.swu.edu/c.php?g=1412131&p=10458937 and https://libguides.swu.edu/c.php?g=1412131&p=10458938 but was not extracted; content from these pages must be reviewed before confirming this classification as not defined.
- The university does not define AI use in research data or analysis in the provided sources
- It does require IRB review before starting any research in which faculty, staff, or students collect data on or from human subjects, including surveys, or use existing data collected from living human subjects
Any research activity in which faculty, staff, or students investigate and/or collect data on or from human subjects (including surveys), or use existing data (including specimens) collected from living human subjects requires review by the IRB prior to its initiation. Any changes to the project after IRB approval must be submitted for continued approval. Continuing review is also required at intervals established by the regulations and further determined by the IRB.
- The university does not define AI-specific research ethics or integrity rules in the provided sources
- It does state that the Research Compliance Committee promotes responsible conduct of research and requires committee review for human subjects research by faculty, staff, and students
The RCC supports the university in promoting the responsible conduct of research.
All research conducted in the following areas by faculty, staff, and students, on- and off-campus, regardless of funding support for the project, must be reviewed by the Research Compliance Committee:
1. Research/projects/study involving vertebrate animals.
2. Research/projects/study involving hazardous chemicals or biological agents.
3. Human subjects research.
Academic Integrity
- The university does not provide AI-specific disclosure or citation instructions in the provided sources
- It does require proper acknowledgment of others' material, methods, or ideas and treats failure to acknowledge the originator as plagiarism
At the beginning of
the course, faculty members are encouraged to convey and
to interpret their policy on plagiarism (academic dishonesty
involving the use of another's material, methods, or ideas
without properly acknowledging the originator).
- The university does not mention AI detection tools in the provided sources
- It does define enforcement procedures for academic dishonesty, including faculty reporting obligations and sanctions that range from a zero on the work to course failure and possible academic dismissal for more serious cases involving unauthorized aid or conspiracy
Faculty, upon evidence of academic
dishonesty (cheating, plagiarism, or misuse of another’s intellectual property), either by voluntary confession, report of
another student, or on the basis of work submitted, must follow the procedure outlined in the Catalog (under Academic
Honesty). This includes but is not limited to a zero for the work involved, 10% course grade reduction, or a failing grade
for the course.
In the event that there is evidence the
student either encouraged others to be
involved in the academic dishonesty, or
conspired with others in the process by
giving, receiving or using unauthorized aid,
the faculty member should consult with his
or her academic dean and recommend to the
provost a response that may include
academic dismissal from the university.
Institutional & Administrative
- The sources do assign faculty responsibility for classroom oversight, communicating plagiarism policy, and following misconduct procedures
- The university does not define AI-specific rules for faculty or staff use in grading, feedback, teaching preparation, or administrative work in the provided sources
Faculty members are in
charge of their classrooms and are encouraged to be present
during exams. In the case of exams given outside of a
classroom setting (such as online), efforts should be made
to safeguard the integrity of the evaluation.
At the beginning of
the course, faculty members are encouraged to convey and
to interpret their policy on plagiarism (academic dishonesty
involving the use of another's material, methods, or ideas
without properly acknowledging the originator).
Faculty, upon evidence of academic
dishonesty (cheating, plagiarism, or misuse of another’s intellectual property), either by voluntary confession, report of
another student, or on the basis of work submitted, must follow the procedure outlined in the Catalog (under Academic
Honesty).
- The university does not define approved AI platforms or AI-specific data-entry rules in the provided sources
- It does require users to access only authorized information, protect credentials and systems, and avoid unauthorized modifications to university data or access-controlled information
Protect your user id and system from unauthorized use. You are responsible for all activities on your user id or that originate from your system. Your user id and password act together as your electronic signature.
Access only information that is your own, that is publicly available, or to which you have been given authorized access.
Use computer programs to decode passwords or access-controlled information.
Attempt to circumvent or subvert system or network security measures.
Engage in any activity that might be purposefully harmful to systems or to any stored information. For example, do not create or propagate viruses, worms, or "Trojan horse" programs, or disrupt services, damage files, or make unauthorized modifications to university data.
- No formal university-wide AI governance or strategy document was identified in the reviewed sources; however, the university library's AI LibGuides pages were not consulted and may contain relevant institutional guidance or framework statements that could inform this classification
Potentially relevant institutional AI guidance exists at https://libguides.swu.edu/c.php?g=1412131&p=10458937 and https://libguides.swu.edu/c.php?g=1412131&p=10458938 but was not extracted; these pages should be reviewed before confirming this classification as not defined.
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 Southern Wesleyan University's AI Policies
Southern Wesleyan University has defined AI policies in 11 of 12 categories, with an overall coverage score of 92%.
The university does not provide AI-specific disclosure or citation instructions in the provided sources. It does require proper acknowledgment of others' material, methods, or ideas and treats failure to acknowledge the originator as plagiarism.
The university does not mention AI detection tools in the provided sources. It does define enforcement procedures for academic dishonesty, including faculty reporting obligations and sanctions that range from a zero on the work to course failure and possible academic dismissal for more serious cases involving unauthorized aid or conspiracy.
The university does not define approved AI platforms or AI-specific data-entry rules in the provided sources. It does require users to access only authorized information, protect credentials and systems, and avoid unauthorized modifications to university data or access-controlled information.