Hands-On Learning

Gain practical experience through hands-on projects and real-world applications.

Expert Guidance

Learn from industry experts with years of experience in Generative AI research.

Flexible Schedule

Study at your own pace with our online platform, allowing you to balance work and learning effectively.

About the Course

Our AI Literacy for Academic Integrity Across the Student Lifecycle course is designed to help educators, academic developers, and student support teams cultivate responsible AI use at every stage of higher education. From induction to graduation, the course provides practical frameworks, literacy-building activities, and ethical guidelines that support both learning and institutional integrity. Whether you are introducing new students to the basics of AI literacy or working with graduates to embed ethical practice into their professional lives, this course offers adaptable strategies and real-world examples. By the end, you will be equipped to design interventions, resources, and policies that not only safeguard academic integrity but also empower students as confident, responsible users of AI throughout their educational journey.

Meet Your Instructor

Jonathan Wong is the founder of CloudPedagogy, where he develops ethical, practical, and future-ready learning systems for Generative, Agentic, and emerging Quantum AI. Drawing on over 20 years of experience in higher education, research, and digital innovation, he specialises in applying AI to real-world contexts — from curriculum design and assessment reform to research acceleration and institutional strategy. His frameworks and courses help educators, researchers, and professionals build the confidence, capability, and critical insight needed to thrive across the evolving Continuum of Intelligence.

Curriculum

8 Chapters · 75 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

    9.1 Induction to Final Year: A Longitudinal Approach

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      9.1.1 Introducing AI Literacy and Ethics in Year One

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      9.1.2 Building Academic Skills alongside AI Tools

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      9.1.3 Revisiting and Reinforcing Expectations Each Year

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      9.1.4 Ethical Scaffolding in Capstone and Final Projects

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      9.1.5 Creating a Continuum of Integrity Development

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      9.1.6 Key Takeaways

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      9.1.A Practical Use Cases

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      9.1.B Learning Activities

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      9.1.C Prompt Templates

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      9.1.D Innovative Use Cases

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      9.1.E Reflection & Discussion

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      9.1.F Productivity Tips

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      9.1.G Prompt Library

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      9.1.H Applying the AI Capability Framework

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    9.2 Embedding AI Literacy into Support Services

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      9.2.1 Training Librarians and Learning Advisors on GenAI Ethics

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      9.2.2 AI Tool Literacy Through Academic Skills Workshops

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      9.2.3 Ethical Use Drop-Ins and 1:1 Coaching

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      9.2.4 Linking GenAI Support with Wellbeing and Pressure Management

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      9.2.5 The Role of Career Services in AI Ethics Preparedness

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      9.2.6 Key Takeaways

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      9.2.A Practical Use Cases

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      9.2.B Learning Activities

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      9.2.C Prompt Templates

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      9.2.D Innovative Use Cases

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      9.2.E Reflection & Discussion

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      9.2.F Productivity Tips

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      9.2.G Prompt Library

    14. (Included in full purchase)

      9.2.H Applying the AI Capability Framework

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    9.3 Cross-Curricular Literacy Frameworks

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      9.3.1 Building AI Ethics into Graduate Attributes

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      9.3.2 Mapping Integrity Skills Across Modules

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      9.3.3 Interdisciplinary Approaches to AI-Use Case Integration

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      9.3.4 Aligning GenAI Literacy with Digital Capability Frameworks

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      9.3.5 Teaching AI Concepts Without Tech-Heavy Language

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      9.3.6 Key Takeaways

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      9.3.A Practical Use Cases

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      9.3.B Learning Activities

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      9.3.C Prompt Templates

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      9.3.D Innovative Use Cases

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      9.3.E Reflection & Discussion

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      9.3.F Productivity Tips

    13. (Included in full purchase)

      9.3.G Prompt Library

    14. (Included in full purchase)

      9.3.H Applying the AI Capability Framework

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    9.4 Peer-Led Learning and Integrity Culture

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      9.4.1 Creating Peer Support Schemes for AI Integrity

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      9.4.2 Training Student Mentors in Ethical AI Use

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      9.4.3 Student Clubs and Societies as AI Literacy Hubs

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      9.4.4 Peer-Led Campaigns and Digital Literacy Events

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      9.4.5 Co-Creating Resources with Students

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      9.4.6 Key Takeaways

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      9.4.A Practical Use Cases

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      9.4.B Learning Activities

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      9.4.C Prompt Templates

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      9.4.D Innovative Use Cases

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      9.4.E Reflection & Discussion

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      9.4.F Productivity Tips

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      9.4.G Prompt Library

    14. (Included in full purchase)

      9.4.H Applying the AI Capability Framework

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    9.5 Measuring Progress and Literacy Maturity

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      9.5.1 Developing Rubrics for AI Literacy Growth

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      9.5.2 Capturing Longitudinal Data on Ethical Readiness

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      9.5.3 Using Reflection to Assess Development

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      9.5.4 Linking Literacy to Student Outcomes and Employability

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      9.5.5 Continuous Evaluation and Framework Improvement

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      9.5.6 Key Takeaways

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      9.5.A Practical Use Cases

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      9.5.B Learning Activities

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      9.5.C Prompt Templates

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      9.5.D Innovative Use Cases

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      9.5.E Reflection & Discussion

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      9.5.F Productivity Tips

    13. (Included in full purchase)

      9.5.G Prompt Library

    14. (Included in full purchase)

      9.5.H Applying the AI Capability Framework

  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

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