Hands-On Learning

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

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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-Supported Moderation and Assessment Calibration course is designed to help educators and academic leaders integrate AI responsibly into assessment quality processes. Whether you are new to AI in assessment or seeking to refine your moderation strategies, this course provides a structured curriculum covering principles, workflows, collaboration, fairness, and institutional QA. Through practical examples and ethical guidance, you’ll gain the capability to apply AI critically and creatively in moderation, ensuring your assessments remain fair, transparent, and future-ready.

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. (Included in full purchase)

      Download: Universal AI Practice Workbook

    1. 9.1.1 The role of moderation in academic standards Free preview
    2. 9.1.2 Common moderation models and practices Free preview
    3. 9.1.3 Challenges in large-scale and remote settings Free preview
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      9.1.4 Maintaining consistency across disciplines

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      9.1.5 Introducing AI into moderation workflows

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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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      9.2.1 Generating comparative samples with AI

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      9.2.2 Clustering responses for review

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      9.2.3 Flagging anomalies and inconsistencies

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      9.2.4 Training AI models on moderation criteria

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      9.2.5 Monitoring algorithmic suggestions

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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

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      9.3.1 Supporting distributed teams with shared AI tools

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      9.3.2 Digital annotation and discussion of scripts

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      9.3.3 Building shared understanding through AI prompts

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      9.3.4 Integrating moderator feedback across locations

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      9.3.5 Consensus building with AI-supported analytics

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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

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      9.3.G Prompt Library

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      9.4.1 Reducing unconscious bias in marking and review

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      9.4.2 Comparing human and AI interpretations

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      9.4.3 Triangulating moderator decisions

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      9.4.4 Auditing fairness in high-stakes assessments

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      9.4.5 Mitigating over-reliance on AI judgements

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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

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      9.5.1 QA policies and AI in moderation processes

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      9.5.2 Moderation reporting and documentation

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      9.5.3 Scaling with institutional systems

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      9.5.4 Feedback loops from moderation to design

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      9.5.5 Evolving moderator roles in the AI age

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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

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      9.5.G Prompt Library

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      Course Complete: Share Your 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.

£49.00

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