Hands-On Learning

Simulate real-world teaching and institutional scenarios with guided AI prompts, case studies and interactive activities.

Education-Focused Insights

Explore best practices and real examples of AI integration in pedagogy, curriculum design and student support.

Flexible, Self-Paced Learning

Work through structured, on-demand modules at your own pace, with resources tailored to your teaching and leadership goals.

About the Course

Discover how AI can transform learning environments to cater for all students. This course explores Universal Design for Learning principles, leveraging AI to personalise instruction, create accessible text, audio and visual materials, and deliver multilingual, culturally responsive experiences. You’ll learn to apply ethical guidelines and develop differentiated support strategies that respect diverse needs and backgrounds. Through practical examples, hands-on exercises and implementing tailored feedback mechanisms, you’ll be equipped to design inclusive AI-powered learning solutions that empower every learner to thrive.

Meet Your Instructor

I'm Jonathan Wong, a Lead AI Scientist and researcher specialising in medical diagnostics, data science, and advanced research technologies. My work focuses on applying generative AI and machine learning to improve healthcare outcomes and support complex research workflows. In this course, I share practical tools, ethical strategies, and real-world insights developed through applied experience in research and development. Whether you're just beginning or looking to deepen your skills, you'll find structured guidance to help you use AI effectively, creatively, and responsibly in your research practice.

Curriculum

8 Chapters · 65 Lessons

  1. 1

    Introduction

    1. Welcome to the Course Free preview
    2. How This Course Works Free preview
    3. Legal Disclaimer & Terms of Use Free preview
  2. 2

    7.1 Designing with Universal Design for Learning (UDL) Principles and AI

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      7.1.1 Understanding UDL and Its Relevance to Generative AI

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      7.1.2 AI for Enhancing Representation: Multimodal Content Generation

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      7.1.3 AI for Scaffolding Engagement: Simulating Inclusive Learner Experiences

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      7.1.4 Promoting Flexible Expression: AI as a Tool for Student-Centred Output

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      7.1.5 Auditing Content and Redesigning with AI

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      7.1.6 Key Takeaways

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      7.1.A Practical Use Cases

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      7.1.B Learning Activities

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      7.1.C Prompt Templates

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      7.1.D Innovative Use Cases

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      7.1.E Reflection & Discussion

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      7.1.F Productivity Tips

  3. 3

    7.2 Using AI for Personalisation and Differentiated Support

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      7.2.1 Understanding AI-Enabled Personalisation

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      7.2.2 Adaptive Pathways: Responsive Sequencing and Differentiation

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      7.2.3 AI Learning Companions and Scaffolding Support

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      7.2.4 Differentiated Pacing and Micro-Interventions

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      7.2.5 Goal-Setting, Motivation, and Student Agency

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      7.2.6 Key Takeaways

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      7.2.A Practical Use Cases

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      7.2.B Learning Activities

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      7.2.C Prompt Templates

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      7.2.D Innovative Use Cases

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      7.2.E Reflection & Discussion

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      7.2.F Productivity Tips

  4. 4

    7.3 Creating Accessible Content with AI Tools (Text, Audio, Visual)

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      7.3.1 Redefining Accessibility through AI-Supported Multimodal Design

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      7.3.2 AI Automation for Captions, Transcripts, and Alt-Text

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      7.3.3 From Static Materials to Responsive Content: Personalisation Meets Accessibility

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      7.3.4 Tools for Educators: Dashboards, Templates, and Format Checkers

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      7.3.5 Ethical and Practical Tensions: Accuracy, Bias, and Representation

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      7.3.6 Key Takeaways

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      7.3.A Practical Use Cases

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      7.3.B Learning Activities

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      7.3.C Prompt Templates

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      7.3.D Innovative Use Cases

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      7.3.E Reflection & Discussion

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      7.3.F Productivity Tips

  5. 5

    7.4 Multilingual and Culturally Responsive AI-Powered Learning

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      7.4.1 The Role of Language in Learning and Belonging

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      7.4.2 Culturally Responsive Design with Generative AI

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      7.4.3 Bridging Global Classrooms with Real-Time AI Translation

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      7.4.4 Identifying and Mitigating Bias in Language Models

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      7.4.5 Personalised Support for Multilingual Students

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      7.4.6 Key Takeaways

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      7.4.A Practical Use Cases

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      7.4.B Learning Activities

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      7.4.C Prompt Templates

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      7.4.D Innovative Use Cases

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      7.4.E Reflection & Discussion

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      7.4.F Productivity Tips

  6. 6

    7.5 Ethical Considerations in Inclusive AI Use

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      7.5.1 Defining Inclusive AI in Higher Education

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      7.5.2 Auditing AI Tools for Bias and Harm

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      7.5.3 Co-Designing Inclusive AI Practices with Students and Staff

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      7.5.4 Enhancing Transparency and Trust in AI Use

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      7.5.5 Embedding Inclusive AI into Institutional Policy and Culture

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      7.5.6 Key Takeaways

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      7.5.A Practical Use Cases

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      7.5.B Learning Activities

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      7.5.C Prompt Templates

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      7.5.D Innovative Use Cases

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      7.5.E Reflection & Discussion

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      7.5.F Productivity Tips

  7. 7

    Final Lesson Message

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      Course Complete: Share Your Feedback

  8. 8

    Feedback

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      End of Course Survey

Unlock Your Genai Potential

Join our course today and unlock the full potential of Generative AI in your research projects. Empower yourself with the knowledge and skills to drive innovation and make a significant impact in your field.

£97.00

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