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

This course empowers educators and learners to develop critical AI literacy and ethical digital practices. Participants will explore the foundations of responsible AI use, learn to evaluate AI outputs with a critical eye, and engage in ethical case studies highlighting bias, harm and misinformation to inform their approach. Through reflexive activities emphasising digital citizenship, learners will cultivate self-awareness and collaborative design skills, co-creating AI-enhanced learning experiences that uphold fairness and accountability.

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

9 Chapters · 66 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

    6.1 Foundations of AI Literacy and Responsible Use

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      6.1.1 Defining AI Literacy in the Higher Education Context

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      6.1.2 Framing AI as Collaborator vs. Shortcut

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      6.1.3 Embedding AI Literacy into Orientation and Induction

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      6.1.4 Mapping AI Literacy vs. Digital and Data Literacy

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      6.1.5 Developing Prompt Responsibility as a Literacy Practice

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      6.1.6 Key Takeaways

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      6.1.A Practical Use Cases

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      6.1.B Learning Activities

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      6.1.C Prompt Templates

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      6.1.D Innovative Use Cases

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      6.1.E Reflection & Discussion

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      6.1.F Productivity Tips

  3. 3

    6.2 Teaching Students to Evaluate AI Outputs Critically

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      6.2.1 The RRV Framework: Reliability, Relevance, Validity

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      6.2.2 Contradiction as a Learning Tool: Juxtaposing Outputs

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      6.2.3 Critique in Practice: Debunking, Testing, Revising

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      6.2.4 Logging and Reflecting: The AI Critique Journal

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      6.2.5 Simulating Diverse Voices: AI as Debate Partner

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      6.2.6 Key Takeaways

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      6.2.A Practical Use Cases

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      6.2.B Learning Activities

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      6.2.C Prompt Templates

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      6.2.D Innovative Use Cases

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      6.2.E Reflection & Discussion

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      6.2.F Productivity Tips

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    6.3 Ethical Case Studies: Bias, Harm, and Misinformation in AI

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      6.3.1 Recognising AI Bias: Understanding the Roots and Risks

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      6.3.2 Harm in Practice: From Algorithmic Discrimination to Misinformation

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      6.3.3 Exploring Ethical Dilemmas Through Case-Based Learning

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      6.3.4 Generative AI and Misinformation: Understanding and Countering Propagation

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      6.3.5 Student and Staff Voice in AI Ethics Debates

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      6.3.6 Key Takeaways

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      6.3.A Practical Use Cases

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      6.3.B Learning Activities

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      6.3.C Prompt Templates

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      6.3.D Innovative Use Cases

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      6.3.E Reflection & Discussion

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      6.3.F Productivity Tips

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    6.4 Building Reflexive Practices: Self-Awareness and Digital Citizenship

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      6.4.1 The Role of Reflexivity in the AI Era

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      6.4.2 AI Diaries: A Tool for Critical Reflection

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      6.4.3 Visualising Data Trails: Revealing the Hidden Curriculum

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      6.4.4 Co-Authorship and Intellectual Agency

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      6.4.5 Writing Personal AI Codes of Conduct

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      6.4.6 Key Takeaways

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      6.4.A Practical Use Cases

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      6.4.B Learning Activities

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      6.4.C Prompt Templates

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      6.4.D Innovative Use Cases

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      6.4.E Reflection & Discussion

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      6.4.F Productivity Tips

  6. 6

    6.5 Co-Designing AI Learning Experiences with Students

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      6.5.1 Redefining Student Roles in the Age of Generative AI

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      6.5.2 Establishing AI Design Studios and Hackathons

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      6.5.3 Building a Student-Curated Prompt Library

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      6.5.4 Integrating Student Voice into Curriculum and Tool Evaluation

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      6.5.5 Navigating Ethical Tensions Through Co-Reflection

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      6.5.6 Key Takeaways

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      6.5.A Practical Use Cases

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      6.5.B Learning Activities

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      6.5.C Prompt Templates

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      6.5.D Innovative Use Cases

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      6.5.E Reflection & Discussion

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      6.5.F Productivity Tips

  7. 7

    Knowledge Check

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      Knowledge Check (Coming Soon!)

  8. 8

    Final Lesson Message

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      Course Complete: Share Your Feedback

  9. 9

    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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