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 practical, responsible and future-focused approaches to digital learning and emerging technology. Drawing on over 20 years of experience in higher education, research and digital innovation, his work explores how technology can support learning, analysis and knowledge creation. His work spans generative and agentic AI, digital learning design, interactive learning systems, educational technology and open-source development. A particular focus is translating emerging technologies into practical tools, workflows and learning experiences while maintaining transparency, critical judgement and human oversight. Through CloudPedagogy, Jonathan develops courses, frameworks, demonstrations and open-source projects designed to help learners and professionals understand complex ideas, experiment with new technologies and apply them in meaningful real-world contexts.

Curriculum

8 Chapters · 71 Lessons

    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

    1. 6.1.1 Key Principles and Terminology in Interdisciplinarity Free preview
    2. 6.1.2 Challenges and Opportunities in Programme-Level Integration Free preview
    3. 6.1.3 Curriculum Models for Interdisciplinary Learning Free preview
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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

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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

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      6.2.G Prompt Library

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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

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      6.3.G Prompt Library

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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

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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

    10. (Included in full purchase)

      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

    1. (Included in full purchase)

      Course Complete: Share Your Feedback

    1. (Included in full purchase)

      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.

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