Teaching & Learning
- Use of generative AI in coursework is at instructor discretion
- If AI use is not authorized or is inconsistent with an instructor’s stated limits, it can be treated as academic dishonesty
- Faculty are expected to set clear course-level expectations, and students are responsible for understanding and following those expectations
As generative artificial intelligence (AI) platforms become more popular, it is important for each instructor to establish and communicate expectations to students regarding acceptable and unacceptable uses in each specific class setting.
By considering and communicating the acceptable uses of AI in each course, faculty can maximize opportunities for learning while minimizing opportunities for academic dishonesty.
At Eastern Washington University, each student is responsible for knowing and adhering to standards for academic integrity and honesty. In support of this endeavor, faculty are encouraged to communicate clear expectations regarding how students can use tools like AI in coursework. Any use of AI that is not authorized by the instructor, or that misrepresents the student’s own work, may constitute academic dishonesty.
Faculty should include statements in the course syllabus regarding generative AI use and discuss these expectations with students.
Academic dishonesty includes, but is not limited to, cheating, plagiarism, fabrication, facilitating dishonesty, and other forms of dishonesty as specified by the instructor or in the policy below.
- No university-wide AI rule specific to exams or quizzes is separately defined
- The university instead places responsibility on instructors to state acceptable and unacceptable AI use in each class, so exam-related AI use is governed by course-level expectations and academic integrity rules
As generative artificial intelligence (AI) platforms become more popular, it is important for each instructor to establish and communicate expectations to students regarding acceptable and unacceptable uses in each specific class setting.
Faculty should include statements in the course syllabus regarding generative AI use and discuss these expectations with students.
- Students may use AI for learning support when the instructor permits it and when the use is bounded by course expectations
- The university guidance gives examples such as brainstorming, review, and tutoring-oriented assistance, but these remain subject to instructor direction and student responsibility for the final work
Some AI uses support student learning without replacing the student’s own thinking. Examples may include:
• Brainstorming ideas for an assignment
• Creating practice quizzes or flashcards
• Getting feedback on a rough draft
• Explaining difficult concepts or terms
• Generating examples to aid understanding
Responsible use of generative AI by students depends on context and instructor expectations. Faculty should clearly define which uses are permitted, restricted, or prohibited in their courses.
Regardless of how AI is used, students are responsible for the accuracy, integrity, and originality of the work they submit.
Research
- The university does not provide a general, university-wide rule in the listed sources specifically governing AI use for drafting or editing research manuscripts
- However, researchers are told to follow sponsor and publisher requirements and should not list AI as an author; researchers remain accountable for all submitted content
Researchers should review and comply with sponsor requirements and publisher policies regarding the use of generative AI tools in proposal development and manuscript preparation.
Generative AI tools do not meet authorship criteria. Authors are responsible and accountable for the content of their work, including any portion generated or assisted by AI.
- The listed sources do not establish a detailed university-wide rule specifically authorizing or prohibiting AI-based data analysis itself
- Researchers are cautioned not to enter confidential, sensitive, or regulated research data into public AI systems and must comply with applicable sponsor, privacy, and compliance requirements
Do not enter confidential, sensitive, or regulated data into publicly available AI tools.
Examples of data that should not be shared with generative AI tools include:
• Personally identifiable information (PII)
• Student records protected by FERPA
• Health information protected by HIPAA
• Proprietary or unpublished research data
• Export-controlled or otherwise restricted information
Researchers should review and comply with sponsor requirements and publisher policies regarding the use of generative AI tools in proposal development and manuscript preparation.
- Research-related AI use is constrained by human accountability, confidentiality, and external compliance requirements
- The research misconduct policy separately defines fabrication, falsification, and plagiarism as prohibited in federally funded research
- Researchers must not submit confidential or regulated information to public AI tools, must follow sponsor and publisher rules, and remain responsible for the accuracy and integrity of AI-assisted work
Researchers should review and comply with sponsor requirements and publisher policies regarding the use of generative AI tools in proposal development and manuscript preparation.
Do not enter confidential, sensitive, or regulated data into publicly available AI tools.
Generative AI tools do not meet authorship criteria. Authors are responsible and accountable for the content of their work, including any portion generated or assisted by AI.
Research misconduct means fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results.
Plagiarism means the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.
Academic Integrity
- When instructors allow AI use, students may be required to disclose and document how they used it
- The university guidance recommends that faculty specify whether citation or an acknowledgment statement is required, and students remain responsible for accurate representation of their work
Faculty should make expectations explicit about whether students must disclose or document their use of AI tools in assignments.
Consider addressing the following in your syllabus or assignment prompt:
• Whether AI tools are allowed, limited, or prohibited
• What kinds of AI use are acceptable
• Whether students must cite or disclose their use of AI
• How misuse will be handled
Regardless of how AI is used, students are responsible for the accuracy, integrity, and originality of the work they submit.
- Undisclosed or unauthorized AI use may be enforced through the university’s academic dishonesty process
- The sources provided do not define a university-wide stance on use of AI detection tools, but they do state that unauthorized AI use can constitute academic dishonesty and is subject to instructor handling and existing integrity procedures
Any use of AI that is not authorized by the instructor, or that misrepresents the student’s own work, may constitute academic dishonesty.
Consider addressing the following in your syllabus or assignment prompt:
• Whether AI tools are allowed, limited, or prohibited
• What kinds of AI use are acceptable
• Whether students must cite or disclose their use of AI
• How misuse will be handled
Academic dishonesty includes, but is not limited to, cheating, plagiarism, fabrication, facilitating dishonesty, and other forms of dishonesty as specified by the instructor or in the policy below.
Institutional & Administrative
- Faculty and staff may use AI tools for instructional and administrative support, but they are expected to apply human judgment and protect privacy
- Guidance emphasizes that instructors should communicate course-specific AI rules, and staff must avoid entering restricted institutional information into public tools
Faculty may find generative AI tools useful for developing course materials, brainstorming assignments, creating examples, or supporting administrative tasks. However, instructors should carefully review all AI-generated output for accuracy, bias, and appropriateness before use.
Faculty should include statements in the course syllabus regarding generative AI use and discuss these expectations with students.
Generative AI tools can be useful for drafting communications, summarizing information, generating ideas, and increasing efficiency in administrative work. However, employees should exercise caution and apply human judgment before relying on AI-generated output.
Do not input confidential, sensitive, or protected university information into public AI tools unless the platform has been reviewed and approved for that level of data.
- The university restricts what data may be entered into AI systems and ties use to data sensitivity and platform approval
- Public AI tools must not receive confidential, sensitive, or protected university information unless the platform has been reviewed and approved for that data level, and examples of restricted data include student records, health information, unpublished research data, and other regulated information
Do not input confidential, sensitive, or protected university information into public AI tools unless the platform has been reviewed and approved for that level of data.
Examples of data that should not be shared with generative AI tools include:
• Personally identifiable information (PII)
• Student records protected by FERPA
• Health information protected by HIPAA
• Proprietary or unpublished research data
• Export-controlled or otherwise restricted information
Do not enter confidential, sensitive, or regulated data into publicly available AI tools.
- The guidance sets broad principles around responsible use, privacy, academic integrity, and human review for faculty, staff, and researchers
- Eastern Washington University has institution-level generative AI guidance rather than a formal comprehensive AI strategy in the listed sources
These guidelines are intended to support thoughtful, ethical, and effective use of generative AI across Eastern Washington University.
As AI tools continue to evolve, EWU encourages a balanced approach that embraces innovation while maintaining academic standards, protecting privacy, and ensuring human oversight.
The purpose of this document is to provide guidance for the responsible use of generative artificial intelligence tools by faculty, staff, and researchers at Eastern Washington University.
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 Eastern Washington University's AI Policies
Eastern Washington University has defined AI policies in 11 of 12 categories, with an overall coverage score of 92%.
When instructors allow AI use, students may be required to disclose and document how they used it. The university guidance recommends that faculty specify whether citation or an acknowledgment statement is required, and students remain responsible for accurate representation of their work.
Undisclosed or unauthorized AI use may be enforced through the university’s academic dishonesty process. The sources provided do not define a university-wide stance on use of AI detection tools, but they do state that unauthorized AI use can constitute academic dishonesty and is subject to instructor handling and existing integrity procedures.
The university restricts what data may be entered into AI systems and ties use to data sensitivity and platform approval. Public AI tools must not receive confidential, sensitive, or protected university information unless the platform has been reviewed and approved for that data level, and examples of restricted data include student records, health information, unpublished research data, and other regulated information.