Hands-On Learning

Simulate real-world teaching and institutional scenarios with guided AI prompts, case studies and interactive activities.

Education-Focused Insights

Explore best practices and real examples of AI integration in pedagogy, curriculum design and student support.

Flexible, Self-Paced Learning

Work through structured, on-demand modules at your own pace, with resources tailored to your teaching and leadership goals.

About the Course

Explore how AI can transform assessment workflows by guiding you through generative design of aligned assessment formats, AI-crafted rubrics and marking guides, and automating feedforward and personalised feedback. Learn to leverage diagnostic and formative AI-driven tools to support learners in real time, while critically evaluating the validity and integrity of AI-generated assessment instruments. By the end of this module, you will be equipped to design, personalise and safeguard robust assessment and feedback processes that enhance learning outcomes and maintain academic rigour.

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

9 Chapters · 66 Lessons

    1. Welcome to the Course Free preview
    2. How This Course Works Free preview
    3. Legal Disclaimer & Terms of Use Free preview

    1. 3.1.1 Aligning Assessments with Learning Outcomes Using Generative AI Free preview
    2. 3.1.2 Expanding the Range of Assessment Formats with Generative AI Free preview
    3. 3.1.3 Scenario-Based and Authentic Assessment Design with Generative AI Free preview
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      3.1.4 Formative Feedback and Low-Stakes Assessment Loops with Generative AI

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      3.1.5 Personalised Task Generation and Learner Choice with Generative AI

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      3.1.6 Key Takeaways

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      3.1.A Practical Use Cases

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      3.1.B Learning Activities

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      3.1.C Prompt Templates

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      3.1.D Innovative Use Cases

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      3.1.E Reflection & Discussion

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      3.1.F Productivity Tips

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      3.2.1 From Learning Outcomes to Rubric Criteria: Co-Designing with AI

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      3.2.2 Designing for Inclusion, Accessibility, and Multilingual Use

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      3.2.3 Generating Performance-Level Examples: Making Rubrics Transparent

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      3.2.4 Integrating Student Voice Through AI-Supported Co-Development

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      3.2.5 Auditing Rubrics for Bias and Alignment with Regulatory Standards

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      3.2.6 Key Takeaways

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      3.2.A Practical Use Cases

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      3.2.B Learning Activities

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      3.2.C Prompt Templates

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      3.2.D Innovative Use Cases

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      3.2.E Reflection & Discussion

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      3.2.F Productivity Tips

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      3.3.1 Rethinking Feedback as Feedforward

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      3.3.2 Personalisation for Inclusion and Motivation

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      3.3.3 Streamlining and Scaling with AI Feedback Libraries

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      3.3.4 Maintaining Quality and Consistency with Feedback Audits

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      3.3.5 Feedback Across Time: Longitudinal Tracking and Growth

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      3.3.6 Key Takeaways

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      3.3.A Practical Use Cases

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      3.3.B Learning Activities

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      3.3.C Prompt Templates

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      3.3.D Innovative Use Cases

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      3.3.E Reflection & Discussion

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      3.3.F Productivity Tips

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      3.4.1 Foundations of Formative Assessment in the AI Era

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      3.4.2 AI-Driven Diagnostic Tools for Early Risk Identification

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      3.4.3 Conversational Check-ins and Chat-Based Self-Assessment

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      3.4.4 Simulated Failure and Adaptive Feedback in Safe Environments

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      3.4.5 Student Dashboards and Formative Data Visualisation

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      3.4.6 Key Takeaways

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      3.4.A Practical Use Cases

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      3.4.B Learning Activities

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      3.4.C Prompt Templates

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      3.4.D Innovative Use Cases

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      3.4.E Reflection & Discussion

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      3.4.F Productivity Tips

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      3.5.1 Understanding Validity in AI-Generated Assessments

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      3.5.2 Auditing AI-Generated Tasks: Clarity, Bias, and Accessibility

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      3.5.3 Student Involvement in Assessment Integrity

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      3.5.4 Embedding AI in Meta-Assessment and Reflection

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      3.5.5 Building Institutional Frameworks for AI Assessment Integrity

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      3.5.6 Key Takeaways

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      3.5.A Practical Use Cases

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      3.5.B Learning Activities

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      3.5.C Prompt Templates

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      3.5.D Innovative Use Cases

    11. (Included in full purchase)

      3.5.E Reflection & Discussion

    12. (Included in full purchase)

      3.5.F Productivity Tips

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      Knowledge Check: Quiz

    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.

£49.00

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