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 course Designing End-to-End AI-Supported Assessment Systems equips professionals with the frameworks and tools to build resilient, ethical, and innovative assessment systems powered by generative AI. From system thinking and workflow design to governance, scaling, and foresight, you will explore how AI can transform the entire assessment lifecycle. Whether you are seeking to enhance assessment in education, training, or professional development, this course provides a comprehensive curriculum with practical insights for sustainable, future-ready practice. Join us and develop the expertise to lead assessment innovation responsibly and effectively.

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. (Included in full purchase)

      Download: Universal AI Practice Workbook

  2. 2

    10.1 System Thinking in AI-Supported Assessment

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      10.1.1 Mapping the full assessment lifecycle

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      10.1.2 Understanding interdependencies and actors

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      10.1.3 Identifying AI opportunities across phases

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      10.1.4 Building system-aware assessment strategies

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      10.1.5 Case studies from institutional pilots

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      10.1.6 Key Takeaways

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      10.1.A Practical Use Cases

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      10.1.B Learning Activities

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      10.1.C Prompt Templates

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      10.1.D Innovative Use Cases

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      10.1.E Reflection & Discussion

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      10.1.F Productivity Tips

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      10.1.G Prompt Library

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      10.1.H Applying the AI Capability Framework

  3. 3

    10.2 Workflow Design from Assignment to Feedback

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      10.2.1 Designing seamless AI-supported assessment pipelines

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      10.2.2 Triggering feedback from performance data

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      10.2.3 Combining multiple AI tools in assessment flow

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      10.2.4 Synchronising student and staff touchpoints

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      10.2.5 Ensuring flow is pedagogically grounded

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      10.2.6 Key Takeaways

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      10.2.A Practical Use Cases

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      10.2.B Learning Activities

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      10.2.C Prompt Templates

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      10.2.D Innovative Use Cases

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      10.2.E Reflection & Discussion

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      10.2.F Productivity Tips

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      10.2.G Prompt Library

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      10.2.H Applying the AI Capability Framework

  4. 4

    10.3 Ethics, Risk, and Governance in Full-System Design

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      10.3.1 Identifying institutional risks and mitigations

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      10.3.2 Designing with transparency and fairness in mind

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      10.3.3 Involving stakeholders in design review

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      10.3.4 Mitigating system-wide bias

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      10.3.5 Compliance with local and international guidelines

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      10.3.6 Key Takeaways

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      10.3.A Practical Use Cases

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      10.3.B Learning Activities

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      10.3.C Prompt Templates

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      10.3.D Innovative Use Cases

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      10.3.E Reflection & Discussion

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      10.3.F Productivity Tips

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      10.3.G Prompt Library

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      10.3.H Applying the AI Capability Framework

  5. 5

    10.4 Scaling and Sustaining AI-Driven Systems

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      10.4.1 Change management for academic teams

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      10.4.2 Institutional capacity building and resourcing

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      10.4.3 Technical integration with LMS and QA systems

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      10.4.4 Continuous improvement and impact evaluation

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      10.4.5 Long-term cultural shifts in assessment design

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      10.4.6 Key Takeaways

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      10.4.A Practical Use Cases

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      10.4.B Learning Activities

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      10.4.C Prompt Templates

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      10.4.D Innovative Use Cases

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      10.4.E Reflection & Discussion

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      10.4.F Productivity Tips

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      10.4.G Prompt Library

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      10.4.H Applying the AI Capability Framework

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    10.5 Future-Ready Assessment: Innovation and Foresight

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      10.5.1 Anticipating future capabilities of GenAI

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      10.5.2 Scenario planning in curriculum teams

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      10.5.3 Designing for agility and rapid adaptation

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      10.5.4 Co-designing with students and industry

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      10.5.5 Policy implications for the next decade

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      10.5.6 Key Takeaways

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      10.5.A Practical Use Cases

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      10.5.B Learning Activities

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      10.5.C Prompt Templates

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      10.5.D Innovative Use Cases

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      10.5.E Reflection & Discussion

    12. (Included in full purchase)

      10.5.F Productivity Tips

    13. (Included in full purchase)

      10.5.G Prompt Library

    14. (Included in full purchase)

      10.5.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

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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