How to Write an Academic Integrity Policy on Generative AI Use
A section-by-section breakdown of what your assignment actually requires — definitions, SACSCOC alignment, enforcement, faculty responsibilities, APA citations, and the structural decisions that determine whether your policy holds together.
The assignment asks you to develop a balanced, enforceable academic integrity policy on the use of generative AI — as if submitting it to academic leadership. That framing matters. This is not a reflective essay about AI in education. It is a policy document that will be evaluated on whether it is operationally sound, institutionally grounded, and professionally presented. This guide breaks down every required component, tells you what weak responses look like, and shows you how to build each section to a standard that holds up to faculty scrutiny.
What This Guide Covers
What the Assignment Actually Demands
The prompt specifies that your policy must read as if submitted to academic leadership. That single instruction shapes every decision you make about format, tone, and content. Academic leadership — a provost, a chief academic officer, a faculty senate — does not read student essays. It reads policy documents. Those documents use precise, professional language, are organised by numbered sections with clear headings, include specific procedural language, and are tied directly to institutional and regulatory sources.
Two common errors appear immediately: writing the policy as an essay with flowing paragraphs and no structural markers, or writing it as an academic reflection on AI ethics rather than as an operational governance document. Both will underperform against the rubric even if the ideas are sound, because the format signals that the writer has not understood what kind of document this is supposed to be.
The assignment includes an appendix titled “Academic Integrity Policy Template.” This is not supplementary material — it is the structural skeleton your policy should follow. The template specifies seven sections with explicit subsection requirements under each. If your submitted policy does not follow that structure, you are not answering the assignment even if your content is good. Use the template as your outline and populate each section with substantive, institution-specific material.
The Two Deliverables
The assignment has two graded components: the policy document itself (Part 2) and a faculty training presentation (Part 3). This guide covers both, but the policy document requires the deeper analytical work. The presentation is derivative — it translates the policy into a training format, which means the policy must be complete and coherent before the presentation can be built well.
Section I: Policy Purpose and Institutional Fit
This section has two jobs: establish why the policy exists and anchor it to the specific institution you have selected. Weak responses write generically about AI in education without connecting to an actual university’s mission statement, handbook language, or strategic plan. That approach fails the “institutional fit” requirement regardless of how accurate the general points are.
How to Write This Section
Start by identifying the institution you are using for the assignment. Then locate two things: the institution’s mission statement (usually on the About page or in the strategic plan) and the relevant section of the student or faculty handbook addressing academic integrity. These are your two required institutional sources, and they should appear in this section by name, not just in the reference list.
The purpose statement should explain the specific gap the policy fills. Generative AI tools were not in widespread use when most current academic integrity policies were written — your policy addresses that gap. Connect this to the institution’s existing integrity standards by showing that generative AI use without policy creates ambiguity that undermines those standards. Do not assert this abstractly; quote or closely paraphrase the relevant handbook language and then explain what the absence of AI-specific guidance means for enforcement of that language.
What to Include
- Named institution, mission statement excerpt, and citation
- Specific handbook or integrity code reference with section number
- Explanation of the policy gap generative AI creates
- Defined scope: which populations are covered (undergrad, grad, faculty, staff)
- Effective date placeholder and revision cycle statement
What Weakens This Section
- Generic statements about AI advancement without institutional anchoring
- No direct reference to the handbook or integrity code
- Vague scope that does not specify affected populations
- Treating this section as an essay introduction rather than a policy preamble
- No mention of SACSCOC in the context of this section’s regulatory backdrop
Weak: “As artificial intelligence becomes more prevalent in society, universities must address its use in academic settings. This policy aims to ensure that students use AI responsibly.”
Stronger: “Liberty University’s Academic Honor Code (2024, Section 2.1) defines academic dishonesty as ‘submitting work that is not the student’s own without proper attribution.’ The emergence of generative AI tools — including ChatGPT, Claude, and Gemini — creates a category of submission that existing definitions do not clearly address. This policy establishes the framework by which the University’s existing integrity standards apply to AI-assisted academic work, in alignment with the institutional mission to ‘develop Christ-centered men and women with the values, knowledge, and skills essential to impact the world’ (Liberty University, 2024).”
Section II: Definitions and Classifications of AI Use
This is the most technically precise section of the policy and the one most likely to be underdeveloped in weak submissions. The assignment requires three classification categories: acceptable use, prohibited use, and conditional use. Each must be defined clearly enough that a student or faculty member reading the policy can determine, without ambiguity, which category a specific action falls into.
The Three Classification Categories
The acceptable and prohibited categories are relatively straightforward to define. The conditional category is where most enforcement ambiguity lives — and where your policy demonstrates whether it is operationally sound. Vague conditional use language (“AI may be used with instructor permission”) is not enforceable because it puts all definitional burden on individual instructors with no institutional standard. Strong conditional use language specifies what disclosure looks like, what conditions trigger the need for it, and how compliance is verified.
Section III: Academic Expectations and Violations
This section has two subsections the assignment explicitly requires: faculty responsibilities and student responsibilities. Both must reference actual handbook or integrity code wording — not paraphrase it loosely, but cite specific sections. This is where your two institutional sources do their heaviest work.
Faculty Responsibilities
The assignment specifies that faculty responsibilities must address AI-use expectations in syllabi, assignment design, instruction, and feedback. A policy that only says “faculty should address AI in syllabi” is too vague to be enforceable. Your policy should specify what syllabi must include — for example, a required statement classifying the course’s AI use category, the consequences for undisclosed AI use in that course, and the disclosure format the course requires.
On assignment design, the policy should note that faculty are responsible for designing assessments that are not trivially completable with generative AI — not as an absolute prohibition, but as a shared accountability principle. This connects to the SACSCOC Good Practices emphasis on faculty oversight of the learning environment, which you will develop further in Section V.
Student Responsibilities
Student responsibilities should be stated as affirmative obligations, not just prohibitions. Students are responsible for: knowing this policy and any course-level AI policy stated in the syllabus, disclosing AI use when required in the format specified, and seeking clarification from the instructor before submitting any work involving AI assistance when the course policy is unclear. Responsibility for policy compliance rests with the student, not with uncertainty about what is permitted.
Faculty: Syllabus Requirements
Each course syllabus must include an AI use statement that classifies the course (no AI / conditional AI / AI-permitted) and specifies the disclosure format. Template language should be provided by the academic integrity office.
Students: Disclosure Obligations
Students must disclose AI use in the format specified by the course syllabus. Where no format is specified and conditional use applies, disclosure must be made in writing before submission with a description of how AI was used.
Violations and Consequences
Violations should be tiered by severity. First-offense conditional-use violations (e.g., AI use without disclosure) may warrant different consequences than prohibited-use violations (submitting AI-generated work as original). Reference the handbook’s existing sanction framework and extend it to this context.
Section IV: Implementation and Enforcement
This section covers how violations are reported, reviewed, and adjudicated. It is procedural rather than definitional — it tells readers what happens when the policy is invoked. Weak submissions describe the enforcement section in abstract terms (“violations will be reviewed by the appropriate committee”) without specifying who initiates the process, what documentation is required, what the review timeline is, or how appeals work.
Reporting Mechanisms
The standard model for academic integrity violations runs through the instructor. When an instructor suspects a violation, they initiate the reporting process by documenting the suspected violation and notifying the academic integrity office or equivalent body. Your policy should specify: what constitutes sufficient documentation of a potential AI violation (AI detection tool output is not sufficient alone — this is important to note explicitly), what the instructor submits to the integrity office, and what the student is entitled to know at each stage.
On AI Detection Tools and Evidence
A policy that treats AI detection tool output as definitive evidence of a violation is both procedurally unsound and legally vulnerable. Detection tools produce probabilistic assessments, not determinations. They generate false positives, particularly for non-native English writers. Your enforcement section should specify that AI detection tool output may be used to initiate a review but cannot alone constitute a violation finding — additional evidence such as process documentation, prior drafts, or in-person follow-up is required. This protects students and makes the policy defensible under due process challenges.
Review Process and Appeals
Specify the body responsible for reviewing reported violations — typically an academic integrity board, honor council, or conduct office. Include: the composition of the review panel (faculty, student representation if applicable, administrator), the timeline from report to initial determination, the standard of evidence required for a finding, and the appeals pathway. Your handbook will have an existing due process framework — reference it by section and explain how your policy’s enforcement mechanism integrates with it rather than creating a parallel process.
Implementation Timeline
The assignment requires an implementation plan that includes an effective date, a communication strategy, and an integration plan for handbooks, syllabi templates, and LMS tools. This section should be specific. A vague statement that the policy will be “communicated to all stakeholders” is not an implementation plan. Name the channels (faculty senate presentation, student email, LMS announcement, syllabus template update), assign responsibility to specific offices (CAO, Dean of Students, IT/LMS administrator), and state the annual review cycle.
Section V: SACSCOC Alignment
This section is the most distinctive requirement of this particular assignment and the one students most often handle poorly. SACSCOC — the Southern Association of Colleges and Schools Commission on Colleges — is the regional accreditor for institutions in the southeastern United States and Latin America. The assignment specifically references the SACSCOC Good Practices document from June 2025 and requires you to cite at least three key Good Practice areas that your policy addresses.
What SACSCOC Good Practices Covers
The SACSCOC Good Practices document provides guidance on institutional responsibilities related to AI in higher education. The areas most directly relevant to an academic integrity policy on generative AI include academic integrity frameworks, faculty oversight of the academic environment, FERPA compliance in the context of student data submitted to AI platforms, and institutional accountability for quality assurance in learning outcomes. Your policy should not generically reference SACSCOC — it should identify specific Good Practice areas by name or section, quote or closely paraphrase the relevant guidance, and then explain the specific policy provision that fulfils that guidance.
How to Structure the SACSCOC Alignment Section
A table format works well here: column one lists the SACSCOC Good Practice area, column two identifies the relevant policy section that addresses it, column three provides a brief justification connecting the two. This format is easy to read and demonstrates systematic alignment rather than a loose narrative claim that the policy generally supports SACSCOC expectations. You need at minimum three rows in this table — but four or five is stronger if you can genuinely connect your policy provisions to additional Good Practice areas.
FERPA Considerations
SACSCOC Good Practices specifically addresses FERPA compliance in the context of AI — when students submit work to AI platforms, they may be sharing information that constitutes educational records. Your policy should include a provision noting that students should not submit personally identifiable information, assessments containing confidential course material, or third-party data to generative AI platforms without considering FERPA implications. This provision connects directly to the SACSCOC FERPA guidance and demonstrates that your policy is not limited to the academic integrity dimension of AI use.
Section VI: References and APA Citations
The assignment specifies APA format with at minimum three scholarly sources and two institutional sources. The institutional sources are specific: the SACSCOC Good Practices document (June 2025), and relevant institutional documents such as handbooks, policy manuals, or strategic plans from the university you have chosen.
What Counts as a Scholarly Source Here
For a policy document on AI and academic integrity, peer-reviewed articles or professional publications from recognised higher education organisations are appropriate scholarly sources. Relevant sources include work on academic dishonesty frameworks, AI ethics in education, faculty governance of learning technology, and institutional policy design. Avoid citing news articles or blog posts as scholarly sources — they can appear in the text as contextual references but should not count toward your scholarly source requirement.
| Source Type | Counts Toward | APA Format Note |
|---|---|---|
| SACSCOC Good Practices (June 2025) | Institutional source + SACSCOC alignment requirement | Cite as an institutional report: Author/Organization. (Year). Title. Publisher URL. |
| University student or faculty handbook | Institutional source | Cite the specific edition and section. If online: University Name. (Year). Handbook title. URL. |
| University strategic plan or mission document | Institutional source | Cite as institutional document. Include the URL if accessed online. |
| Peer-reviewed journal article on AI ethics or academic integrity | Scholarly source | Standard APA journal format: Author, A. A. (Year). Title. Journal Name, Volume(Issue), pages. DOI |
| Professional association report (e.g., AAUP, ACE) | Scholarly/professional source | Cite as organizational report with URL and access date if online. |
The most common APA errors in this type of assignment: failing to include a DOI for journal articles that have one; formatting the reference list with incorrect hanging indent (APA uses hanging indent — the first line flush, subsequent lines indented); using “&” outside of parenthetical citations (in-text narrative citations use “and”); and omitting the retrieval date for sources that require it. For institutional documents accessed online, always include the URL. For documents behind a login, note the institutional access point rather than a direct URL.
If you need support with APA citation formatting across your references, citation and referencing assistance covers APA 7th edition across all source types including institutional documents, government reports, and online publications.
Part 3: The Faculty Training Presentation
The presentation is worth 100 points and requires 10–12 slides with presenter notes. It should be designed as a professional training module — not a summary of the policy, but a tool for preparing faculty to implement it. The distinction matters: a summary tells faculty what the policy says; a training module shows faculty how to act on it in their specific roles.
Required Slide Structure
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Introduction and Policy Rationale (1–2 slides)
Summarise why the policy was developed and why it matters now. This should be brief — faculty in a training do not need the full policy history. Emphasise the gap being filled and the institutional context. Reference the mission language from Section I of your policy.
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Policy Overview: Key Terms and Classifications (2 slides)
Review the three AI use categories — acceptable, prohibited, conditional — with concrete examples. A simple visual table works better than bullet lists here. Faculty need to be able to distinguish categories quickly, which means the examples need to be course-relevant rather than abstract.
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Faculty Responsibilities (2 slides)
Cover the three specific areas the assignment requires: syllabus statements, assignment design, and student advising. Include a sample syllabus AI-use statement that faculty can adapt — the assignment explicitly requires “one sample scenario or suggested syllabus statement.”
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Institutional and Biblical Integration (1 slide)
The assignment requires one Bible verse aligned with faculty responsibility or academic truth. This slide should connect the verse to the institutional mission language and to the academic integrity framework — not as decoration, but as a substantive statement about the values underpinning the policy. Appropriate verses include those addressing honesty, stewardship, and the pursuit of truth.
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Reporting Process (1 slide)
Walk faculty through the enforcement mechanism from Section IV of your policy. Make the steps concrete: what faculty do when they suspect a violation, what documentation to collect, who they contact, and what the timeline looks like from report to resolution.
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Support and Resources (1 slide)
List the institutional offices and contacts relevant to policy implementation — the academic integrity office, IT/LMS support for detection considerations, the CAO’s office for policy clarifications. Include the URL for the full policy document and the SACSCOC Good Practices reference.
The assignment explicitly requires presenter notes. In many submissions, this element is underdeveloped — notes that only restate what is on the slide do not demonstrate the depth the assignment is evaluating. Effective presenter notes add context that is not on the slide: the reasoning behind a policy decision, a common question faculty ask about this area, a specific scenario that illustrates the point, or a connection to the institutional handbook. Notes should be substantial enough that a different presenter could deliver the module without additional briefing.
Mistakes That Cost Marks
Generic Institution
Writing a policy for “a university” rather than a named institution means you cannot fulfil the requirement to reference actual handbook language, strategic plans, or mission statements. The institutional sources requirement cannot be met without a specific institution.
Instead
Choose a real institution — ideally one you are familiar with or enrolled in — and locate its published handbook and mission statement before writing a word of the policy. Those documents are your anchors for Sections I, III, and the reference list.
Vague Conditional Use Language
“Students may use AI with instructor permission” leaves every definitional question unanswered. What constitutes permission? How is it communicated? What disclosure does the student then owe? Vague language is unenforeable language.
Instead
Define the conditions operationally: what the instructor must communicate (in the syllabus or in writing), what the student must disclose (format, timing), and how the use is documented. Every conditional use provision should answer: who decides, how is it communicated, and how is compliance verified.
SACSCOC Section as Afterthought
Listing three SACSCOC principles without quoting or paraphrasing the actual guidance and without connecting them specifically to policy provisions fails the alignment requirement. Generic mentions of SACSCOC do not constitute citation of specific Good Practice areas.
Instead
Use a structured table: Good Practice area → policy provision that addresses it → justification. Each row should be specific enough that someone reading the SACSCOC document could verify the connection without taking your word for it.
Treating AI Detection as Proof
An enforcement section that relies on AI detection tool output as the basis for a violation finding is procedurally unsound. Detection tools have documented false positive rates, are not designed for legal or academic evidentiary standards, and disproportionately flag non-native English writers.
Instead
State explicitly that detection tool output is one input into the review process, not a determination. Specify additional evidence requirements — process documentation, prior drafts, oral follow-up — before a violation finding can be made. This makes the policy defensible and demonstrates policy-design sophistication.
Before Submitting: A Structural Checklist
- Policy follows the appendix template structure with all seven sections present
- Named institution with handbook and mission statement citations in Section I
- All three AI use categories (acceptable, prohibited, conditional) defined with examples
- Generative AI defined with at least three named tool examples
- Faculty responsibilities cover syllabi, assignment design, instruction, and feedback
- Student responsibilities stated as affirmative obligations, not just prohibitions
- Enforcement section specifies reporting trigger, documentation, review body, timeline, and appeals
- AI detection tool limitations addressed in the enforcement section
- SACSCOC section includes at minimum three specific Good Practice areas with policy connections
- Reference list includes at least three scholarly sources and two institutional sources in APA format
- Presentation has 10–12 slides with substantive presenter notes on every slide
- Presentation includes sample syllabus statement and one Bible verse with institutional connection
Frequently Asked Questions
A policy document on generative AI use is not a thought experiment — it is a governance instrument. It will be evaluated on whether it is enforceable, whether it is specifically grounded in the institution it claims to serve, and whether every provision it makes can be acted upon by the administrators and faculty who would implement it. That standard is higher than most academic essay assignments, and the gap between a generic attempt and a genuinely strong submission is usually not about depth of AI knowledge — it is about policy-writing discipline: specificity, operational precision, and the ability to connect abstract principles to concrete procedures. The guidance above covers what that discipline looks like in each required section. If you need support executing it under deadline pressure, academic writing assistance is available for graduate education policy assignments at every stage from outline to final submission.