DOCUMENT CONTROL
| Policy Number | EES-POL-2026-003 |
| Policy Title | Academic Integrity in Online Education |
| Classification | Institutional · Academic · Accreditation |
| Version | 3.0 |
| Effective Date | May 28, 2026 |
| Last Reviewed | May 28, 2026 |
| Next Review | May 2027 (annual review cycle) |
| Policy Owner | Office of the Chief Executive Officer |
| Approval Authority | Executive Leadership Team (School Board) |
Table of Contents
- Purpose 4
- Scope 4
- Definitions 4
- Statement of Principles 6
- Standards of Academic Conduct 6
- Prohibited Conduct 7
- Assessment Design Standards 7
- Responsible Use of Artificial Intelligence 8
- Detection, Screening, and Verification Tools 10
- Identity Verification and Secure Assessment 10
- Human Oversight and Oral Verification 11
- Learning Analytics and Behavioral Monitoring 11
- Academic Integrity Culture, Training & Communication 12
- Reporting, Investigation, and Consequences 12
- Roles and Responsibilities 13
- Policy Governance, Review, and Revisions 14
- Effective Date and Authority 15
1. Purpose
This policy establishes the standards, expectations, systems, and procedures by which Excel Education Systems, Inc. (“EES” or “the Institution”) and its schools uphold academic integrity in a fully online learning environment. It affirms that the value of an EES credential depends on the authenticity of the work behind it.
Academic integrity in online education requires a multi-layered approach that combines instructional design, technology, assessment methodology, identity verification, human oversight, and institutional culture. EES does not rely on any single anti-cheating solution. Instead, the Institution builds systems in which authentic learning is the most efficient and rewarding path for students, making genuine engagement easier than academic dishonesty.
This policy defines what constitutes academic integrity and misconduct, establishes the design standards and technologies used to safeguard it, governs the responsible use of artificial intelligence, and sets out the procedures for reporting, investigating, and resolving violations.
2. Scope
This policy applies to all students, faculty, instructional designers, education technologists, academic coaches, registrars, and administrators participating in any academic activity offered by an EES school, including but not limited to:
- Excel High School (and its state-specific campuses, including Excel High School Texas)
- Northgate Academy
- Washington Technical Institute (WTI)
- Learn Star Academy
- Adult high school diploma programs and any future schools, programs, or educational entities operated by Excel Education Systems
This policy governs all coursework, assessments, projects, discussion boards, examinations, capstones, and any other graded or credit-bearing activity, regardless of delivery format, and applies to work produced with or without the assistance of artificial intelligence tools.
3. Definitions
For the purposes of this policy, the following definitions apply:
Academic Coach. A staff member who provides course-specific support, reviews grade concerns, and helps students understand assignment expectations and feedback, as further defined in EES-POL-2026-004.
Academic Integrity. The commitment to honesty, trust, fairness, respect, and responsibility in all academic work. It requires that all work submitted for credit be the authentic product of the enrolled student, properly attributed, and produced in accordance with the rules of each assessment.
Academic Fingerprint. The identifiable pattern of a student’s work, including writing style, assessment performance, engagement behaviors, demonstrated knowledge, and learning progression over time.
Academic Misconduct. Any act that compromises academic integrity, including plagiarism, unauthorized use of artificial intelligence, identity fraud, unauthorized collaboration, fabrication, and violations of test security, as further described in Section 6.
Authentic Assessment. An assessment requiring the student to demonstrate understanding, synthesis, application, and critical thinking through work products such as projects, presentations, portfolios, case studies, and performance tasks, rather than simple recall.
Contract Cheating. The submission of work completed by a third party, whether a person or a service, paid or unpaid, as if it were the student’s own.
Easy Grader. The current approved AI-assisted grading system used by Excel Education Systems to evaluate eligible student assignments and provide rubric-aligned scores and feedback. Easy Grader grades submitted work on the staff side and is distinct from BRYTE, the student-facing AI tutor governed by EES-POL-2026-003, which does not grade or produce submittable work.
Generative Artificial Intelligence (AI). Software systems capable of producing text, code, images, or other content in response to prompts. Includes both general-purpose tools and the Institution’s own educational AI systems.
Plagiarism. Presenting the words, ideas, structure, or work of another, including AI-generated content, as one’s own, without proper attribution.
BRYTE. The Institution’s dedicated AI tutor. BRYTE tutors Socratically, guiding students with questions, hints, and worked examples rather than finished answers, and is intentionally constrained so it cannot produce submittable work. It logs tutoring interactions, which, with appropriate disclosure, can serve as positive evidence of authentic engagement and authorship rather than only as a misconduct check. Acceptable and prohibited uses are governed by Section 8 of this policy. BRYTE is a student-facing tutoring system and is distinct from Easy Grader, the Institution’s staff-facing AI grading tool, which evaluates submitted work and is governed by EES-POL-2026-004 (AI-Assisted Grading and Grade Review Policy).
Learn Stage. The Institution’s proprietary learning management and student information system, through which coursework, assessments, analytics, and integrity tools are administered.
Executive Leadership Team (School Board). The senior executives holding final institutional authority over academic policy, as defined in the EES Curriculum, Graduation Standards, and Academic Governance Policy (EES-POL-2026-002).
4. Statement of Principles
EES affirms the following principles as the foundation of this policy:
- Authentic learning is the goal. The purpose of every assessment is to produce and verify genuine learning. Integrity safeguards exist to protect that purpose, not merely to detect wrongdoing.
- Design is the first line of defense. The most effective protection against academic dishonesty is course and assessment design that makes authentic work the path of least resistance.
- Technology supports, but does not replace, human judgment. Detection tools, analytics, and verification systems inform, but never solely determine, findings of misconduct. Qualified human reviewers make final decisions.
- AI is part of the future of learning. The Institution’s strategy is not to prohibit artificial intelligence entirely, but to design education that remains meaningful in an AI-enabled world, teach responsible AI use, and assess the higher-order human skills that AI cannot easily replicate.
- Integrity is a shared culture. Students, faculty, and staff share responsibility for an environment in which honesty is expected, taught, modeled, and consistently upheld.
5. Standards of Academic Conduct
All students enrolled in an EES school are required to:
- Submit only work that is their own authentic product, except where collaboration is expressly authorized by the instructor.
- Properly attribute all sources, including text, ideas, data, media, and AI-generated content.
- Use artificial intelligence tools only in the manner authorized for each assignment, as set out in Section 8.
- Complete all identity-verified and secured assessments personally, without impersonation or unauthorized assistance.
- Refrain from sharing, distributing, or obtaining assessment content in violation of test security.
- Affirm and abide by the EES academic integrity agreement as a condition of enrollment.
All faculty, instructional designers, and education technologists are required to design, deliver, and oversee courses in accordance with the assessment, detection, verification, and oversight standards established in this policy.
6. Prohibited Conduct
The following acts constitute academic misconduct and are prohibited:
Plagiarism. Presenting another’s words, ideas, structure, or work , including AI-generated content , as one’s own without proper attribution.
Unauthorized Use of Artificial Intelligence. Using generative AI to produce work submitted as the student’s own where such use is prohibited or undisclosed, in violation of Section 8.
Identity Fraud. Having another person complete coursework or assessments, impersonating another student, or permitting one’s own identity or credentials to be used by another.
Unauthorized Collaboration. Working with others on assessments designated as individual work, or sharing work in a manner not authorized by the instructor.
Contract Cheating. Obtaining, purchasing, or commissioning work from a third party and submitting it for credit.
Test Security Violations. Capturing, sharing, distributing, or obtaining examination content; using unauthorized materials or devices during secured assessments; or circumventing assessment security controls.
Fabrication. Falsifying data, sources, citations, credentials, or records, including the misrepresentation of process documentation or revision history.
| NOTE This list is illustrative, not exhaustive. Conduct that undermines the authenticity or fairness of academic work may constitute misconduct even if not specifically enumerated above. |
7. Assessment Design Standards
EES schools shall design authentic assessments to make authentic demonstration of learning the most efficient path for students. The following standards apply to course and assessment design.
7.1 Unique and Randomized Assessments
Static, reusable test banks are vulnerable to answer-sharing, screenshot distribution, and memorization. To reduce these risks, courses shall, where appropriate, employ:
- Dynamic question generation, including AI-generated assessment variants aligned to standards
- Time-limited testing windows
- One-question-at-a-time presentation
- Adaptive assessment sequencing
- Continuous retirement of compromised questions
The objective is to ensure that no two students receive an identical assessment experience and that question text is not predictably repeated.
7.2 Authentic Assessment Requirement
Every course shall include authentic assessment that requires demonstration of understanding, synthesis, application, and critical thinking. Acceptable forms include projects, presentations, research assignments, multimedia submissions, portfolios, case studies, performance tasks, career-aligned demonstrations, and real-world problem solving.
To make authentic work difficult to outsource or AI-generate, major authentic assessments shall, wherever practicable: use staged, scaffolded submissions (proposal → outline → draft → final) with iterative feedback, so the process is visible and mastery is demonstrated over time; personalize prompts to the student’s own context, experience, or prior work; include a synchronous or oral checkpoint (see Section 11); and require a short process or reflection artifact with each submission.
7.3 Mastery-Based Learning
Programs that rely heavily on memorization are more easily compromised in an AI-enabled environment. Courses shall therefore be designed around competency mastery, applied learning, analysis and synthesis, problem-solving, communication, collaboration, and reflection. Students are assessed on what they can do, not merely on what they can recall.
7.4 Frequent Low-Stakes Assessment
Rather than relying on a small number of high-stakes examinations, courses shall incorporate frequent short quizzes, regular knowledge checks, ongoing participation, and the tracking of learning progression over time. Distributed assessment establishes a stronger “academic fingerprint” for each student and reduces the incentive to cheat on any single high-value event.
8. Responsible Use of Artificial Intelligence
EES embraces the responsible use of artificial intelligence as a learning aid while prohibiting its use to substitute for authentic student work. This policy distinguishes AI-assisted work , work a student authors themselves while using AI to explain concepts, check understanding, or obtain feedback (permitted under 8.1) , from AI-generated work, in which AI produces the substantive content a student submits as their own (prohibited under 8.2). Each course shall communicate its specific AI-use expectations.
8.1 Acceptable AI Assistance (Ai-As)
AI-assisted work, in which the student remains the author is permitted. Unless specified otherwise, students may use approved AI tools, including the BRYTE AI tutor, to explain concepts, provide worked examples, suggest study plans, check understanding, and obtain feedback on drafts. These uses support learning without replacing it.
8.2 Prohibited AI Use
Students may not use AI to generate complete assignments, essays, solutions, or assessment responses for submission as their own work; to complete secured or identity-verified assessments; or in any manner expressly prohibited by the instructor. Submitting AI-generated work as original work constitutes plagiarism under Section 6.
8.3 Citation and Disclosure
Where AI assistance is permitted and materially contributes to a submission, students shall disclose and, where applicable, cite that use in accordance with course and Institutional citation expectations.
8.4 Designing for the AI Era
The Director of Academics and Curriculum and the Director of AI and Education Technology shall ensure courses are designed to remain meaningful in an AI-enabled world by teaching responsible AI usage, assessing higher-order thinking, emphasizing creativity and originality, requiring evidence of the learning process, integrating ethical technology literacy, and focusing on human skills that AI cannot easily replace.
8.5 AI Literacy as a Graduation Competency
Responsible and effective AI use is a competency students are taught, practice, and are assessed on, not solely a constraint. Students shall demonstrate, at grade-appropriate levels and as a condition of graduation, the ability to use approved AI tools while preserving authentic authorship, critically evaluate AI-generated output, distinguish permitted from prohibited use, and disclose and cite AI assistance as required under 8.3, aligned to the ISTE Standards for Students. The competency shall be assessed through the authentic assessments required under Section 7 rather than as a standalone exercise, and students who do not yet meet it shall be offered remediation and reassessment.
8.6 Assessment-Design Audit
To keep courses AI-resilient as tools evolve, the Director of Academics and Curriculum and the Director of AI and Education Technology shall ensure an assessment-design audit is conducted at least annually. The audit shall evaluate course assessments against current AI capabilities, identify items that are vulnerable or no longer valid measures of learning, and require their retirement or redesign in alignment with Section 7. Findings shall be documented, tracked to completion, and used to inform faculty professional development and course redesign.
9. Detection, Screening, and Verification Tools
Authentic writing assignments, discussion boards, projects, and research submissions shall be screened using a combination of integrity tools, which may include AI-content detection, plagiarism detection, similarity-analysis engines, writing-pattern analysis, and citation-validation systems.
9.1 Use of Detection Results
Detection tools are investigative indicators of possible authenticity concerns, not conclusive proof of misconduct, and not a grading mechanism. A detection score shall never serve as the sole basis for a finding of academic misconduct or trigger an automated penalty; where a flag raises a genuine authenticity concern, a qualified staff member reviews it before any determination. AI-content detectors, in particular, have high false-positive rates and have shown bias against English-language learners and some neurodivergent writers; faculty shall be trained on this limitation. Grading of student work, grade reviews, and grading-quality audits are governed by EES-POL-2026-004 (AI-Assisted Grading and Grade Review Policy).
9.2 Process Evidence and Authenticity
To support authenticity, instructors may require students to submit drafts, revision history, or process documentation alongside final work. Authenticity may also be evaluated through writing consistency over time, and, where concerns arise, particularly on capstone and high-stakes assignments, through oral defense or verification interviews as described in Section 11.
9.3 AI-Use Policy Communication
Each course shall clearly communicate its AI-use policy, defining acceptable AI assistance, prohibited AI-generated work, citation expectations, and ethical AI standards, consistent with Section 8.
10. Identity Verification and Secure Assessment
Ensuring that the enrolled student is the actual learner is essential to accreditation and institutional credibility. EES shall employ identity-verification and secure-assessment measures proportionate to the stakes of each assessment.
10.1 Identity Verification
Identity-verification measures may include government-issued identification verification, secure login authentication, and multi-factor authentication (MFA). Additional measures under consideration include biometric verification, facial-recognition matching, and keystroke analytics.
10.2 Secure Test-Taking
For high-stakes assessments, EES may employ browser-lockdown technology, and the AI-assisted flagging of suspicious testing behaviors.
10.3 Proportionality
Secure-assessment controls shall be applied proportionately. Routine low-stakes assessments shall not be subjected to intrusive monitoring where less restrictive measures suffice. The level of verification and security shall correspond to the academic stakes of the assessment.
11. Human Oversight and Oral Verification
Human interaction substantially improves academic authenticity. Technology alone cannot ensure integrity.
11.1 Oral Verification
EES may require oral or interactive verification of student work, including live teacher conferences, oral presentations, video submissions, viva voce assessments, student walkthroughs of projects, and random competency interviews. Live teacher conferences and random competency interviews are particularly associated with the Future Ready program.
If a student cannot verbally explain submitted work to a reasonable degree consistent with authorship, the matter shall be treated as a potential integrity concern and reviewed under Section 14.
11.2 Faculty and Education Technologist Oversight
The Director of Academics and Curriculum, academic coaches, and education technologists shall review suspicious patterns, evaluate assessment quality, continuously improve course design, monitor student engagement, audit grading consistency, and review AI-generated content concerns. Human oversight remains an essential and non-delegable component of the Institution’s integrity model. Reports should be made to the Director of Academics and Curriculum and Chief Operations Officer.
12. Learning Analytics and Behavioral Monitoring
The Learn Stage platform and associated analytics may be used to identify academic-behavior patterns that warrant review. Indicators may include:
- Atypically rapid completion times
- Log-in anomalies
- Copy-and-paste behavior
- Sudden, unexplained changes in writing style
- Assessment irregularities
- Unusual grade spikes inconsistent with prior performance
Analytics serve to surface high-risk behaviors early for human review. As with detection tools, analytic indicators are investigative signals and shall not, on their own, establish a finding of misconduct. Use of learning analytics shall comply with the Institution’s privacy and data-governance standards.
13. Academic Integrity Culture, Training & Communication
Academic integrity shall be embedded in the culture of every EES school. The Institution shall:
- Require students to affirm an academic integrity agreement as a condition of enrollment
- Provide academic-honesty training, including ethical AI usage, through LMS onboarding modules
- Clearly define academic-misconduct policies and procedures
- Train faculty and staff to identify and respond to integrity concerns
- Reinforce professionalism, accountability, and the value of authentic learning
13.1 Publication of Policy
This policy and its associated expectations shall be published in student handbooks, course catalogs, enrollment agreements, and LMS onboarding modules, so that integrity expectations are communicated clearly and consistently to every student.
Students are significantly less likely to engage in misconduct when integrity expectations are clearly communicated, fairly applied, and consistently enforced.
14. Reporting, Investigation, and Consequences
EES applies a consistent, fair, and documented process for responding to suspected academic misconduct. The process balances the integrity of the credential with the student’s right to a fair review.
14.1 Reporting
Suspected academic misconduct may be identified by faculty, staff, detection tools, or learning analytics, and shall be reported to the appropriate academic authority for review. Reports shall document the specific concern and the supporting evidence.
14.2 Investigation and Human Review
All reports shall be reviewed by qualified faculty or academic staff. Where automated tools or analytics contribute to the concern, the reviewer shall independently evaluate the work — which may include requesting a process or reflection artifact, reviewing automatically captured signals such as document version history, requesting a brief recorded explanation of the work, or comparing the work against the student’s established academic fingerprint (see 7.4).
The goal of the investigation is verification of learning. Whenever appropriate and consistent with academic standards, a student may be given an opportunity to demonstrate mastery through an alternate assessment, asynchronous (recorded) oral verification, supervised reassessment, or other authentic demonstration of learning. Where misconduct is confirmed, this does not limit the consequences that otherwise apply.
14.3 Tiered Response Framework
Consequences shall be proportionate to the nature, severity, and recurrence of the violation. EES applies the following recommended tiered framework:
| Tier | Typical Circumstances | Representative Response |
| Tier 1 — Educational | First, minor, or apparently unintentional violation | Coaching conversation; resubmission; targeted integrity education |
| Tier 2 — Corrective | Clear violation or repeated Tier 1 conduct | Reduced or zero grade on the assessment; documented academic warning |
| Tier 3 — Serious | Severe violation, including identity fraud or contract cheating | Course failure; academic probation; formal record |
| Tier 4 — Terminal | Egregious or repeated serious violations | Suspension or dismissal, subject to review by leadership |
14.4 Student Appeal Rights
A student found to have committed academic misconduct shall have the right to appeal the finding through the Institution’s published grievance and appeals process.
15. Roles and Responsibilities
| Role | Academic Integrity Responsibilities |
| Students | Produce authentic work; follow AI-use rules; complete verified assessments personally; affirm and uphold the integrity agreement. |
| Instructional Designers | Build authentic, mastery-based, low-stakes-distributed assessments and randomized question sets aligned to standards. |
| Education Technologists | Help to support design integrity standards; communicate AI-use policy; review flagged work; conduct oral verification; report suspected misconduct. Maintain detection, analytics, and verification systems; surface high-risk patterns; support faculty review; safeguard data. |
| Director of Academics and Curriculum | Ensure courses remain meaningful in an AI-enabled world; review suspicious patterns and AI-generated content concerns; evaluate assessment quality and continuously improve course design; monitor student engagement; audit grading consistency; receive and act on reports of suspected misconduct. |
| Director of AI and Education Technology | Ensure instructional designers build AI-resilient courses that teach responsible AI use and assess higher-order thinking; oversee the BRYTE AI tutor and approved AI tools; maintain detection, analytics, and verification systems; safeguard related data. |
| Registrars / Academic Admin | Maintain misconduct records; administer consequences and appeals consistently across schools. |
| Executive Leadership Team (School Board) | Own, approve, and review this policy; resolve terminal-tier cases; ensure consistency across all EES schools. |
16. Policy Governance, Review, and Revisions
16.1 Periodic Review
This policy shall be reviewed at least annually by the Executive Leadership Team (School Board), and more frequently as needed in response to accreditation cycles, technological change, regulatory developments, or material changes in EES programs.
16.2 Reserved Authority
The Executive Leadership Team (School Board) retains final authority over the adoption, interpretation, and revision of this policy; the selection and approval of integrity technologies; and the resolution of terminal-tier academic-misconduct cases.
16.3 Document Control
This policy is maintained as a controlled document under EES document-control procedures. The current authoritative version is published in the EES Policy Library and supersedes all prior versions. Material revisions shall be communicated to affected schools, faculty, staff, students, and families through standard institutional channels.
17. Effective Date and Authority
This policy takes effect upon approval by the Executive Academic Leadership Team and remains in effect until revised, superseded, or rescinded by formal institutional action. All prior policies or statements addressing academic integrity within EES schools that are inconsistent with this policy are superseded to the extent of such inconsistency.
17.1 Citation
This policy shall be cited as:
Excel Education Systems, Inc. — Policy on Academic Integrity in Online Education, EES-POL-2026-003, Version 3.0.
17.2 Inquiries
Inquiries regarding the interpretation or application of this policy may be directed to:
| Office of the Chief Executive Officer
Excel Education Systems, Inc. |
Signed Attestation
By signature below, the undersigned members of the Excel Education Systems Executive Academic Leadership Team approve and adopt this Policy on Academic Integrity in Online Education, EES-POL-2026-003, Version 3.0, as the official institutional policy governing the matters set forth herein.