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

This course explores how generative AI can support the design of interdisciplinary and transdisciplinary programmes in higher education. You will learn the core principles of integration, examine models that connect disciplines around shared themes, and use GenAI tools to identify conceptual links, co-create outcomes, and build cohesive learning experiences. By the end of the course, you’ll be able to design programmes that bridge disciplinary boundaries, align with institutional priorities, and prepare students for complex, real-world challenges.

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 · 76 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
    4. Download: Universal AI Practice Workbook Free preview
  2. 2

    6.1 Foundations of Interdisciplinary Curriculum Design

    1. (Included in full purchase)

      6.1.1 Key Principles and Terminology in Interdisciplinarity

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      6.1.2 Challenges and Opportunities in Programme-Level Integration

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      6.1.3 Curriculum Models for Interdisciplinary Learning

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      6.1.4 Role of GenAI in Identifying Thematic and Conceptual Links

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      6.1.5 Designing Shared Learning Outcomes Across Disciplines

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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

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      6.1.G Prompt Library

    14. (Included in full purchase)

      6.1.H Applying the AI Capability Framework

  3. 3

    6.2 Facilitating Cross-Departmental Collaboration with GenAI

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      6.2.1 Using AI to Synthesize Inputs from Diverse Academic Teams

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      6.2.2 Co-Creating Interdisciplinary Rubrics and Learning Activities

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      6.2.3 AI Support for Curriculum Alignment Across Faculties

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      6.2.4 Visualising Overlaps and Gaps Between Disciplines

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      6.2.5 Moderating Language and Epistemology Differences with AI Tools

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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

    13. (Included in full purchase)

      6.2.G Prompt Library

    14. (Included in full purchase)

      6.2.H Applying the AI Capability Framework

  4. 4

    6.3 Building Flexible Pathways Across Faculties

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      6.3.1 AI-Supported Design of Electives and Minors with Thematic Cohesion

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      6.3.2 GenAI for Mapping Student-Created Interdisciplinary Programmes

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      6.3.3 Enabling Transitions Between Disciplines Through Microcredentials

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      6.3.4 Co-Designing Interdisciplinary Modules with Students and AI

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      6.3.5 Ensuring Assessment Validity in Interdisciplinary Programmes

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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

    13. (Included in full purchase)

      6.3.G Prompt Library

    14. (Included in full purchase)

      6.3.H Applying the AI Capability Framework

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    6.4 Industry and Societal Challenge-Based Integration

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      6.4.1 Using GenAI to Translate Global Challenges into Curriculum Themes

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      6.4.2 Embedding Real-World Problem Solving in Programme Design

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      6.4.3 AI Tools for Facilitating External Co-Design with Industry Experts

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      6.4.4 Mapping UN SDGs and Societal Goals onto Curriculum Content

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      6.4.5 Designing Experiential Interdisciplinary Projects with GenAI

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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

    11. (Included in full purchase)

      6.4.E Reflection & Discussion

    12. (Included in full purchase)

      6.4.F Productivity Tips

    13. (Included in full purchase)

      6.4.G Prompt Library

    14. (Included in full purchase)

      6.4.H Applying the AI Capability Framework

  6. 6

    6.5 Sustaining and Evolving Interdisciplinary Programmes

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      6.5.1 Institutional Strategies for Supporting Interdisciplinary Teaching

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      6.5.2 Building Communities of Practice Across Faculties with AI Tools

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      6.5.3 Evaluating Programme Impact Across Disciplinary Lines

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      6.5.4 Leveraging GenAI for Continuous Redesign and Feedback Loops

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      6.5.5 Planning for Growth and Curriculum Complexity with AI Modelling

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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

    11. (Included in full purchase)

      6.5.E Reflection & Discussion

    12. (Included in full purchase)

      6.5.F Productivity Tips

    13. (Included in full purchase)

      6.5.G Prompt Library

    14. (Included in full purchase)

      6.5.H Applying the AI Capability Framework

  7. 7

    Final Lesson Message

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      Course Complete: Share Your Feedback

  8. 8

    Feedback

    1. (Included in full purchase)

      End of Course Survey

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