Anne Arundel Community College AI Policy

MarylandPublicLast Updated: February 2026

Academic IntegrityInstitutional & AdministrativeTeaching & Learning
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Policy Coverage
42%5 of 12
Not Defined
Coursework
This university has not published a formal policy specifically addressing AI use in coursework.
Not Defined
Disclosure
No specific AI disclosure or attribution requirements have been published.
Active
Detection
The university has mechanisms in place to detect unauthorized AI use.
Strategy Set
Governance
A formal AI governance strategy or institutional framework has been defined.
POLICY OVERVIEW

AI Policy Summary

Anne Arundel Community College has defined AI policies across 5 of 12 policy categories, covering Academic Integrity, Institutional & Administrative, Teaching & Learning. The university has not established a formal policy on AI use in coursework and assignments. There are no specific AI disclosure requirements currently defined. The university employs detection and enforcement mechanisms for unauthorized AI use. At the institutional level, the university has established guidelines for faculty and staff AI use, AI governance strategy.

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Teaching & Learning

U1Coursework & Assignments
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No policy defined yet
U2Examinations & Assessments
AI Prohibited in ExamsIntegrity Code Applies
  • Use of unauthorized material, information, electronic devices, or study aids in assessments is prohibited unless the instructor gives permission
  • The college also states that it provided online exam proctoring through Honorlock, which includes artificial intelligence and academic integrity support

B. Cheating is using or attempting to use unauthorized material, information, electronic devices or study aids in an academic exercise, assignment or assessment without the instructor’s permission.

• Provided online exam proctoring through Honorlock®, which incorporates artificial intelligence and academic integrity

support

U3Learning & Study Assistance
Guidelines Issued
  • It also requires regular and substantive interaction by faculty and instructional staff in distance education courses
  • The college does not define a student AI study-assistance policy, but its online instruction guidance states that faculty are experimenting with artificial intelligence to help students learn

As we experiment with the wonderful possibilities of artificial intelligence to help our students learn, this is a reminder to keep the USDE’s guidance around regular and substantive interaction in mind. As you will see below, it is required, for student success as well as federal financial aid eligibility that faculty and instructional staff members regularly and substantially interact with students in their distance education courses.

The U.S. Department of Education emphasizes the importance of regular and substantive interaction in distance education courses. This interaction ensures that students receive meaningful engagement and support in online learning environments. Compliance with these requirements is essential for federal financial aid eligibility.

U4Code Generation & Programming
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No policy defined yet
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Research

U5Research Writing & Manuscript Preparation
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No policy defined yet
U6Research Data & Analysis
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No policy defined yet
U7Research Ethics & Integrity
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No policy defined yet
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Academic Integrity

U8Disclosure & Attribution Requirements
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No policy defined yet
U9Detection & Enforcement
Penalties DefinedIntegrity Process
  • Students found responsible may face discipline up to dismissal or revocation of a credential
  • Separately, the college states that it has provided Honorlock for online exam proctoring, which incorporates artificial intelligence and academic integrity support
  • Suspected academic misconduct may be reported by faculty, staff, students, or third parties, and the college investigates and determines responsibility under its procedures

A. Any faculty, staff, student or third party who suspects a student or former student has committed academic misconduct may submit a report to the college in accordance with the procedures.

B. A student or former student who is found responsible for academic misconduct may be disciplined, up to and including dismissal from the college or revocation of a credential in accordance with the procedures.

C. Upon receipt of a report, the college will conduct an investigation and make a determination as to whether the student or former student is responsible for academic misconduct in accordance with the procedures.

The board of trustees hereby authorizes the president (or designee) to develop, maintain and keep current appropriate procedures to implement and enforce this policy.

• Provided online exam proctoring through Honorlock®, which incorporates artificial intelligence and academic integrity

support

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Institutional & Administrative

U10Faculty & Staff Use
Staff Guidelines
  • Faculty and instructional staff may experiment with artificial intelligence to help students learn, but distance education courses still require regular and substantive human interaction
  • The guidance specifically requires faculty and instructional staff to interact regularly and substantially with students, and substantive interaction includes direct instruction, feedback on coursework, responding to content questions, facilitating discussions, or other accreditor-approved activities

As we experiment with the wonderful possibilities of artificial intelligence to help our students learn, this is a reminder to keep the USDE’s guidance around regular and substantive interaction in mind. As you will see below, it is required, for student success as well as federal financial aid eligibility that faculty and instructional staff members regularly and substantially interact with students in their distance education courses.

Substantive interaction is engaging students in teaching, learning, and assessment, consistent with the content under discussion. It must include at least two of five components:

* Providing direct instruction = “live synchronous instruction where both the instructor and the student are online and in communication at the same time.”

* Assessing or providing feedback on a student’s coursework

* Providing information or responding to questions about the content of a course or competency

* Facilitating a group discussion regarding the content of a course or competency

* Other instructional activities are approved by the institution’s or program’s accrediting agency

U11Institutional Data Protection & Approved AI Platforms
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No policy defined yet
U12University AI Governance & Strategy
AI Strategy Defined
  • AACC has an institutional strategy for the innovative and responsible adoption of artificial intelligence
  • The board minutes also describe a phased process of discovery and analysis, research and development, recommendations, and long-term implementation
  • The strategy is described as collaborative, values-based, ethical, and mission-aligned, with broad campus participation and focus areas that include pedagogy, digital literacy, academic integrity, AI infrastructure, information security, analytics, and governance

Dr. Millner and Dr. Kralevich presented AI at AACC, the College’s institutional strategy for the innovative and responsible adoption of artificial intelligence. They explained that the initiative reflected a collaborative, values-based approach to positioning AACC as a leader in leveraging AI to better serve its students and community, emphasizing the urgency for community colleges to prioritize AI given the needs of working adults, first-generation students, and career changers.

They noted that AI presents both opportunities and risks and reaffirmed AACC’s commitment to a thoughtful, ethical, and mission-aligned approach.

They outlined a comprehensive strategy that builds on existing AI-related work across the College, organized into two tracks, Academic Innovation and Technology Transformation, with broad campus participation. Key focus areas include pedagogy, digital literacy, academic integrity, AI infrastructure, information security, analytics, and governance. They described a phased approach beginning with discovery and analysis, followed by research and development, recommendations, and long-term implementation.

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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