Integrating AI into higher education pedagogy
The integration of artificial intelligence into higher education can support pedagogy when it is connected to clear learning aims. Used thoughtfully, AI can help staff design materials, test explanations, improve accessibility and create opportunities for students to practise judgement.
Key applications include adapting materials for different levels, drafting formative questions, supporting feedback workflows and helping students explore data analysis. These outputs need review: a fluent answer is not evidence that the model has understood the discipline, the learner, or the assessment context.
Effective integration, however, necessitates a structured approach. This involves not only exploring the practical tools but also establishing clear institutional guidelines. Frameworks for assessment and ethics are crucial to ensure that AI is used responsibly and enhances, rather than undermines, academic integrity and student learning.
The pedagogical cycle
Six areas of application
👤 Personalised & differentiated instruction
AI enables truly personalised learning by adapting to individual student needs, learning styles, and pace. Create customised materials, varied assessment approaches, and targeted support.
Practical applications
- Adapt learning materials for advanced, intermediate, and basic knowledge levels
- Transform dense academic materials into summaries or study guides
- Develop personalised study plans based on individual student performance
Prompt examples
Tools
NotebookLM · Microsoft Copilot · Google AI Studio · Magic School AI
📝 Assessment & feedback
Support assessment through AI-assisted drafting of formative questions, rubrics and feedback prompts. These outputs need academic review and alignment with learning outcomes.
Practical applications
- Generate comprehensive rubrics aligned with learning objectives
- Create formative and summative assessment questions based on course context
- Design quizzes with multiple formats, such as short answer or multiple choice, aligned to standards
Prompt examples
Tools
Formative · Blackboard AI Design Assistant · Gradescope · Kahoot!
🎨 Engaging course materials
Rapidly create dynamic, interactive course materials including presentations, case studies, simulations, and multimedia content that enhances knowledge retention and engagement.
Practical applications
- Generate professional-quality educational videos with customisable AI avatars and text-to-speech
- Develop interactive scenario-based learning activities that adapt to student responses
- Repurpose lecture notes into podcast-style audio discussions
- Produce structured lesson plans and interactive activities tailored to specific learners
Prompt examples
Tools
Google AI Studio · ThingLink · Teachfloor · ElevenLabs · Pictory
⚙️ Workflow automation & support
Streamline administrative tasks, manage communications, and provide scalable student support to free up valuable time for teaching and research.
Practical applications
- Draft emails to students about course announcements or deadlines
- Generate lesson plans and align them with learning objectives
- Summarise academic papers or long documents to quickly grasp key points
- Create FAQs and knowledge bases from course materials for student self-service
Prompt examples
Tools
📊 Data analysis & visualisation
Democratise data analysis by enabling students and staff to interact with datasets using natural language, making quantitative analysis more accessible, particularly for those intimidated by traditional methods.
Practical applications
- Create meaningful charts and graphs from datasets (e.g., Excel, CSV) using conversational prompts
- Perform statistical analysis without requiring coding knowledge
- Build forecasting models from your data
Prompt examples
Tools
♿ Accessibility & inclusivity
Leverage AI to create inclusive learning materials that cater to diverse student needs, abilities, and learning preferences.
Practical applications
- Automatically generate descriptive alt text for images in presentations and documents
- Provide real-time transcription and language translation for lectures and meetings
- Convert visual data or colour-based information into accessible formats for students with visual impairments
- Create multilingual versions of teaching resources to support international students
Prompt examples
Tools
Assessment
Framework for incorporating AI in assessment
This framework helps staff make AI expectations visible at assessment level. It is not an institutional policy claim: adapt it to the module, assessment brief and local regulations so students understand what is permitted, what must be evidenced, and how responsibility is assessed.
| Level | Description | Requirement |
|---|---|---|
| 1 — No AI | The assessment is completed entirely without AI assistance. This level ensures that students rely solely on their own knowledge, understanding, and skills. | AI must not be used at any point covered by the assessment brief. |
| 2 — AI-assisted idea generation and structuring | AI can be used in the assessment for brainstorming, creating structures, and generating ideas for improving work. | AI may support idea generation and planning, but the final submission should not include AI-generated content unless the assessment brief explicitly permits it. |
| 3 — AI-assisted editing | AI can be used to make improvements to the clarity or quality of student-created work to improve the final output, but no new content can be created using AI. | Where required by the brief, provide evidence of your original work and explain how AI-assisted editing was checked. |
| 4 — AI task completion, human evaluation | AI is used to complete certain elements of the task, with students providing discussion or commentary on the AI-generated content. This level requires critical engagement with AI-generated content and evaluating its output. | You will use AI to complete specified tasks in your assessment. AI-created content must be verified, disclosed and referenced according to the brief. |
| 5 — Collaborating with AI | AI should be used as a 'co-pilot' in order to meet the requirements of the assessment, allowing for a collaborative approach with AI and enhancing creativity. | You may use AI throughout the assessment to support your own work. Keep a record of significant AI use and follow the disclosure requirements in the brief. |
| 6 — Must use AI | AI use is required as a local or module-specific extension of the assessment, designed to build confidence and critical proficiency with AI tools. | You must use AI where specified, evidence how it was used, verify the outputs, and show how this work is assessed. |
For the ethical dimension of these choices, see the ethics page; for research-specific use, see the research page.
Companion guides