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PGCert in AI in Teaching and Learning

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  1. Learning Outcomes

  2. Module 1: Foundations of AI in Education

    1.1. Understanding AI in Education
  3. 1.2 Current Applications and Challenges
  4. 1.3. Video: The Evolution of AI in Education
  5. Template: AI Literacy Checklist for Educators
  6. 1.5. Generative AI Tools for Educators
  7. 1.6 Prompt Engineering and Use Cases
  8. 1.7. Video: How ChatGPT, Gemini, and Copilot Work
  9. 1.8. Building AI Literacy in the Classroom
  10. Template: Prompt Strategy Canvas
  11. 1.9. Building AI Literacy in the Classroom
  12. 1.10. Video: Defining AI Literacy for Staff & Students
  13. 1.11. Designing AI Literacy Workshops
  14. Template: AI Literacy Curriculum Map
  15. 1.12. Ethics, Bias and Responsible AI Use
  16. 1.13. Bias in Data and Models
  17. 1.14. Video: Academic Integrity and Responsible AI Use
  18. Case Study: “The Misused Essay Generator”-analysing AI ethics breach
  19. 1.15. AI Governance and Policy in Higher Education
  20. 1.16. Understanding Institutional AI Policy
  21. 1.17. Creating an AI Use Framework for Educators
  22. Template: AI Policy Development Framework
  23. Template: AI Ethics Checklist
  24. AI Literacy Self-Assessment Tool
  25. Module 2: Designing AI-Enhanced Learning Experiences
    2.1. Curriculum Mapping for AI-Enabled Pedagogy
  26. 2.2. Mapping Learning Outcomes to AI Capabilities
  27. 2.3. Video: Integrating AI in Programme Design
  28. Template: Curriculum-AI Alignment Matrix
  29. 2.4. Using AI for Content Creation and Lesson Design
  30. 2.5. Using AI to Generate Interactive Content
  31. 2.6. Reviewing and Editing AI Outputs Responsibly
  32. Template: AI Lesson Plan Builder
  33. 2.7. Designing Active and Adaptive Learning Experiences
  34. 2.8. Video: Adaptive Learning Pathways
  35. 2.9. AI-Driven Engagement Tools
  36. Case Study: “SmartTutor: AI-Enhanced LMS in Action”
  37. 2.10. Personalisation through Learning Analytics
  38. 2.11. Student Profiling and Data Ethics
  39. 2.12. Video: Designing Personalised Learning Journeys
  40. Template: Personalised Learning Blueprint
  41. 2.13. Embedding AI in Course Delivery and Feedback
  42. 2.14. Using AI Chatbots and Co-Pilots in Teaching
  43. 2.15. Video: Managing Student Perceptions and Change
  44. Template: AI Integration Implementation Plan
  45. Template: AI-Ready Lesson Design Canvas
  46. Template: Personalised Learning Journey Map
  47. Mini Reflection: “How AI Changed My Course Design Thinking”
  48. Module 3: AI-Based Assessment, Feedback and Learning Analytics
    3.1. Rethinking Assessment in the AI Era
  49. 3.2. Assessment Challenges in an AI World
  50. 3.3. Authentic Assessment Principles
  51. Case Study: “AI in Essay Grading: Opportunity or Risk?”
  52. 3.4. AI-Supported Feedback Systems
  53. 3.5. Using AI for Draft Feedback and Feedforward
  54. 3.6. Designing Rubrics for AI-Assisted Feedback
  55. Template: AI Feedback Rubric Builder
  56. 3.7. Automating Assessment and Grading Responsibly
  57. 3.8. AI-Assisted Grading Tools
  58. 3.9. Video: Ensuring Human Oversight
  59. Template: AI Assessment Governance Checklist
  60. 3.10. Learning Analytics for Decision Making
  61. 3.11. Video: Using AI Dashboards for Monitoring Student Progress
  62. 3.12. Data Interpretation and Intervention Planning
  63. Template: Learning Analytics Dashboard Planner
  64. 3.13. Developing Your AI-Enhanced Assessment Strategy
  65. 3.14. Building an AI Assessment Policy
  66. 3.15. Integrating Insights into Teaching Practice
  67. Template: Assessment Innovation Roadmap
  68. Template: AI-Enabled Assessment Plan
  69. AI Integration Strategy Document

Quizzes

Lesson 1 of 69
In Progress

Learning Outcomes

November 16, 2025

By the end of the programme, participants will be able to:

  1. Critically evaluate AI applications in education through ethical and pedagogical lenses.
  2. Design AI-enhanced learning experiences that promote personalisation and engagement.
  3. Develop AI-supported assessment strategies ensuring integrity and inclusivity.
  4. Implement AI-based analytics to improve teaching quality and learner success.
  5. Apply reflective and evidence-based approaches to integrate AI into professional practice.
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