AI & Academic Integrity: A Policy Framework

Introduction

Artificial intelligence is no longer a future concept; it's a tool available to learners and staff now. While offering huge potential for efficiency and creativity, generative AI also presents a significant challenge to academic integrity. Banning its use is impractical and risks leaving learners unprepared for the modern workplace. The only sustainable path forward is a clear, consistent, and educational whole-provider policy. This framework outlines the key components you need to consider.

Foundational Principles: Defining Your Stance

Before drafting rules, your leadership team and governors must decide on your provider's strategic stance. This forms the foundation of your policy and ensures consistency. You are not just managing a risk; you are shaping your curriculum and defining what constitutes achievement. Ask yourselves:

• Is our primary goal to teach learners to use AI ethically and effectively as a workplace tool?
• How do we balance the use of AI as a supportive aid with the need to assess a learner's own unfiltered knowledge and skills?
• How will our policy apply across different provision types, from technical apprenticeships to A-Level courses?

Policy Component 1: Acceptable and Unacceptable Use

Clarity is crucial. Your policy must give learners and staff concrete examples of what is and is not permitted. This should be a spectrum, not a simple binary choice, and may vary by subject or assessment.

• Examples of Acceptable Use (with permission/declaration):
  • Brainstorming or generating initial ideas for a project.
  • Summarising long texts to aid understanding (where the original texts are then read and cited).
  • Checking grammar, spelling, and sentence structure in a learner's own original writing.
  • Generating code snippets for analysis and annotation, not for direct submission as their own work.
• Examples of Unacceptable Use:
  • Submitting AI-generated text, visuals, or code as one's own work.
  • Using AI to answer assessment questions where the goal is to test recall or application of knowledge.
  • Inventing or fabricating sources and citations using AI.
  • Paraphrasing content with AI to avoid plagiarism detection without understanding or citing the original source.

Policy Component 2: Declaration and Citation

Transparency is the cornerstone of ethical AI use. Learners must be taught how and when to acknowledge their use of AI tools. This normalises its use as a tool, rather than something to be hidden, and maintains the principle of academic honesty.

• Establish a simple, clear format for declaration (e.g., a statement at the end of an assignment).
• Provide examples: "I used ChatGPT 4.0 to help structure the initial outline for this report and to proofread my final draft for grammatical errors."
• Explain that this declaration allows tutors to understand the learner's process and provide more relevant feedback.

Policy Component 3: Detection and Investigation

While AI detection software exists, it is notoriously unreliable and can produce false positives. Over-reliance on it can damage trust and lead to unfair accusations. Your policy should prioritise professional dialogue over automated judgment.

• State that detection software is not the primary basis for a misconduct finding.
• Focus the investigation process on a supportive, professional dialogue with the learner.
• Use the situation as a learning opportunity. Can the learner explain their work, discuss their sources, or show their draft history?
• Align the process with your existing academic misconduct procedure. Treat it as a failure of attribution, not a new category of offence.

Policy Component 4: Staff CPD and Support

A policy is only effective if staff feel confident and consistent in applying it. This requires targeted professional learning to build competence and understanding across your organisation.

• Provide training on how generative AI models work, their capabilities, and their limitations.
• Equip staff with strategies for designing assessments that are more resistant to AI misuse, such as in-class activities, vivas, practical demonstrations, and reflective accounts.
• Support staff in modelling ethical AI use in their own practice.
• Consider developing in-house experts through accredited training, such as the Focus Awards Level 3 Award in AI in Education, to lead practice and support colleagues.

Policy Component 5: Learner Education

Your policy should not just be a list of rules published in a handbook. It must be actively taught and reinforced as part of developing learners' wider skills and professional behaviours.

• Integrate AI literacy into induction, tutorials, and digital skills curricula.
• Frame the rules within the context of digital citizenship and professional ethics required in the workplace.
• Explain why academic integrity matters for their own learning, achievement, and future career.
• Ensure guidance covers the online safety aspects of using AI, such as avoiding the input of personal or sensitive data.

Where this fits in QualityHero

An effective policy on AI and academic integrity is crucial evidence for whole-provider Leadership and Governance. It directly impacts your approach to Curriculum, Teaching and Training, Achievement, and Participation and Development. Using the QualityHero Toolkit Areas module to store your policy, associated staff CPD records, and learner guidance ensures this key aspect of quality is managed, monitored, and integrated into your self-assessment and improvement planning.