Hands-On Learning

Apply generative AI to real research tasks with guided prompts, use cases, and interactive activities.

Research-Focused Instruction

Learn from in-depth, interdisciplinary examples rooted in academic and applied research practice.

Flexible, Self-Paced Study

Work through structured lessons at your own pace, with tools to support your current research projects.

About the Course

Our course on Generative AI for Evidence Synthesis & Systematic Reviews is designed to equip researchers with practical, structured guidance for integrating AI into review workflows. From literature screening to summary writing, you’ll learn where and how AI can support speed, consistency, and insight—while maintaining academic rigour and transparency. Whether you're new to systematic reviews or refining an established process, this course offers the tools and critical perspective needed to work effectively with generative AI.

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. 4.1.1 Using AI to Automatically Screen Research Papers for Systematic Reviews Free preview
    2. 4.1.2 AI Tools for Conducting Thematic Analysis of Existing Research Free preview
    3. 4.1.3 Identifying Key Patterns and Extracting Relevant Findings from Large Datasets Free preview
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      4.1.4 Automating the Process of Categorising Research for Easier Review

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      4.1.5 Using AI to Support Robust and Comprehensive Evidence Synthesis

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      4.1.6 Key Takeaways

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      4.1.7 Knowledge Check

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      4.1.A Practical Use Cases

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      4.1.B Learning Activities

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      4.1.C Prompt Templates

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      4.1.D Innovative Use Cases

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      4.1.E Reflection & Discussion

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      4.1.F Productivity Tips

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      4.2.1 How AI Helps in Structuring Systematic Reviews Using Pre-Built Templates

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      4.2.2 AI’s Role in Summarising Research Findings and Identifying Areas of Consensus

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      4.2.3 Automating the Organisation and Synthesis of Research Data for Reviews

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      4.2.4 Using AI to Ensure Consistency and Accuracy in Systematic Review Formats

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      4.2.5 AI Tools for Creating Clear and Reproducible Systematic Reviews with Minimal Human Input

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      4.2.6 Key Takeaways

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      4.2.7 Knowledge Check

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      4.2.A Practical Use Cases

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      4.2.B Learning Activities

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      4.2.C Prompt Templates

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      4.2.D Innovative Use Cases

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      4.2.E Reflection & Discussion

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      4.2.F Productivity Tips

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      4.3.1 Leveraging AI Tools to Automate Data Extraction from Research Papers

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      4.3.2 AI’s Role in Critical Appraisal of Study Quality and Evaluating Bias

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      4.3.3 Using AI-Driven Insights to Assess the Credibility and Relevance of Studies

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      4.3.4 Ensuring Methodological Rigour and Consistency in AI-Assisted Reviews

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      4.3.5 How AI Enhances the Quality of Data Extraction from Large-Scale Studies

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      4.3.6 Key Takeaways

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      4.3.7 Knowledge Check

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      4.3.A Practical Use Cases

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      4.3.B Learning Activities

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      4.3.C Prompt Templates

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      4.3.D Innovative Use Cases

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      4.3.E Reflection & Discussion

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      4.3.F Productivity Tips

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      4.4.1 How Conversational AI Generates Clear and Concise Summaries for Systematic Reviews

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      4.4.2 Ensuring Accuracy and Coherence in AI-Generated Summaries of Research Findings

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      4.4.3 Cross-Referencing AI-Generated Summaries with Primary Sources for Consistency

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      4.4.4 Tools for Generating Accessible Summaries for a Non-Expert Audience

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      4.4.5 Customising AI-Generated Content to Fit Review Scope and Intended Audience

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      4.4.6 Key Takeaways

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      4.4.7 Knowledge Check

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      4.4.A Practical Use Cases

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      4.4.B Learning Activities

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      4.4.C Prompt Templates

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      4.4.D Innovative Use Cases

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      4.4.E Reflection & Discussion

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      4.4.F Productivity Tips

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      4.5.1 Best Practices for Ensuring Reproducibility When Using AI in Systematic Reviews

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      4.5.2 How to Address Potential Biases in AI Outputs for Transparent Research

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      4.5.3 Ensuring Transparency in AI-Assisted Reviews to Maintain Scientific Integrity

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      4.5.4 Methods to Keep AI-Assisted Reviews Consistent and Reliable Across Different Datasets

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      4.5.5 Documenting AI-Driven Processes to Allow Easy Replication of Reviews

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      4.5.6 Key Takeaways

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      4.5.7 Knowledge Check

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      4.5.A Practical Use Cases

    9. (Included in full purchase)

      4.5.B Learning Activities

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      4.5.C Prompt Templates

    11. (Included in full purchase)

      4.5.D Innovative Use Cases

    12. (Included in full purchase)

      4.5.E Reflection & Discussion

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      4.5.F Productivity Tips

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      Course Complete: Share Your Feedback

    1. (Included in full purchase)

      End of Course Survey

Unlock Your Research 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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