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 is designed to help educators, assessment designers, and academic leaders critically evaluate AI-generated assessments. From foundations of validity and reliability to institutional QA processes and continuous feedback loops, you will gain the knowledge and skills needed to ensure quality, fairness, and integrity in AI-supported assessment systems. Whether you are experimenting with AI in assessment design or seeking to embed it within institutional practice, this course offers structured insights, practical strategies, and ethical guidance to support responsible adoption.

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. 8.1.1 Understanding validity in the HE assessment context Free preview
    2. 8.1.2 Types of reliability and their application Free preview
    3. 8.1.3 Threats to validity in AI-generated assessments Free preview
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      8.1.4 Benchmarking and cross-checking AI outputs

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      8.1.5 Aligning AI use with academic quality standards

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      8.1.6 Key Takeaways

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      8.1.A Practical Use Cases

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      8.1.B Learning Activities

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      8.1.C Prompt Templates

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      8.1.D Innovative Use Cases

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      8.1.E Reflection & Discussion

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      8.1.F Productivity Tips

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      8.1.G Prompt Library

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      8.2.1 Rubric-based evaluation of AI-generated assessments

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      8.2.2 Human review and moderation workflows

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      8.2.3 Using AI to self-assess and revise its own outputs

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      8.2.4 Triangulation with subject matter experts

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      8.2.5 Common pitfalls in AI-designed questions

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      8.2.6 Key Takeaways

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      8.2.A Practical Use Cases

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      8.2.B Learning Activities

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      8.2.C Prompt Templates

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      8.2.D Innovative Use Cases

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      8.2.E Reflection & Discussion

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      8.2.F Productivity Tips

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      8.2.G Prompt Library

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      8.3.1 Detecting and mitigating bias in AI-generated content

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      8.3.2 Representation and equity in question design

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      8.3.3 Language sensitivity and accessibility

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      8.3.4 Evaluating impact on underrepresented groups

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      8.3.5 Audit processes for inclusive assessment design

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      8.3.6 Key Takeaways

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      8.3.A Practical Use Cases

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      8.3.B Learning Activities

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      8.3.C Prompt Templates

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      8.3.D Innovative Use Cases

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      8.3.E Reflection & Discussion

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      8.3.F Productivity Tips

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      8.3.G Prompt Library

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      8.4.1 Integrating GenAI into QA frameworks

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      8.4.2 Mapping AI workflows to academic approval stages

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      8.4.3 Data handling and compliance issues

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      8.4.4 Collaborative validation panels

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      8.4.5 Documenting transparency and decision-making

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      8.4.6 Key Takeaways

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      8.4.A Practical Use Cases

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      8.4.B Learning Activities

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      8.4.C Prompt Templates

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      8.4.D Innovative Use Cases

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      8.4.E Reflection & Discussion

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      8.4.F Productivity Tips

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      8.4.G Prompt Library

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      8.5.1 Using student input to refine AI-generated tasks

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      8.5.2 Staff review and revision cycles

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      8.5.3 Monitoring AI drift over time

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      8.5.4 Institutional reporting and improvement dashboards

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      8.5.5 Building adaptive and responsive QA practices

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      8.5.6 Key Takeaways

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      8.5.A Practical Use Cases

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      8.5.B Learning Activities

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      8.5.C Prompt Templates

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      8.5.D Innovative Use Cases

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      8.5.E Reflection & Discussion

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      8.5.F Productivity Tips

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      8.5.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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