Learning, Teaching & Assessment with AI Series: Ethical Use of AI [Exercise 1] – Coordinator Reviews Course Outline

Learning, Teaching & Assessment with AI Series: Ethical Use of AI [Exercise 1] – Coordinator Reviews Course Outline

Wednesday, September 30, 2026

The Learning, Teaching and Assessment with AI series entails exemplars by Professor Derek Yu, specifically focused on assisting first-year students (at the start of their academic journey) in ethically using AI. The following case highlights how thoughtful prompting, combined with pedagogical judgment, can strengthen curriculum delivery in a first-year undergraduate module.

Case: Coordinator Reviewing Course Outline for ECO151 - First-Year Microeconomics

Context: Initial Planning before turning to AI tools
Tumelo is coordinating ECO151: First-Year Microeconomics for the first time. Upon reviewing last year’s course outline, he noticed that only four lectures were allocated to the ‘Elasticity’ chapter. Given the complexity of the topic—particularly the mathematical calculations and interpretation of results—he decided to expand the chapter to six lectures to allow for deeper conceptual understanding and more practice. Before turning to AI, Tumelo carefully considered:

• The key concepts students must master
• The balance between theory, calculation, and interpretation
• The relative importance of subtopics (e.g., prioritising price elasticity of demand)
• The available teaching time (6 lectures, 45 minutes each)

Reflection and Construction prior to prompting AI tools 

Only after this reflection did he construct a detailed and structured prompt for ChatGPT, clearly outlining:

• The number and duration of lectures
• The full list of required topics
• The level of students (first-year undergraduate)
• The need to prioritise certain concepts over others

Structured Prompt, Pedagogically Aligned AI Output

Using his carefully designed prompt, Tumelo asked ChatGPT to:

• Develop a structured 6-lecture lesson plan
• Allocate time appropriately across topics
• Suggest teaching strategies and examples
• Balance conceptual understanding with quantitative skills

ChatGPT responded with a well-organised lesson plan that included:

• Clear lecture-by-lecture objectives
• Logical sequencing of topics
• Suggested time breakdowns within each lecture
• Teaching strategies (e.g., real-world examples, graphs, think-pair-share activities)
• Appropriate weighting of topics, with emphasis on price elasticity of demand

AI-generated plan demonstrated strong pedagogical alignment

• Scaffolding from basic concepts to more complex applications
• Integration of conceptual explanations with calculations
• Use of relatable, real-world examples to build intuition
• Inclusion of formative assessment opportunities (e.g., quick quizzes, practice problems)

At this stage, the AI output provided a solid and usable teaching plan.

Further Human-Led Refinement and Contextual Adaptation

Despite the quality of the AI-generated lesson plan, Tumelo did not adopt it without modification. He refined the plan by:

• Adjusting pacing based on his teaching style and student cohort
• Incorporating institution-specific examples relevant to South African students
• Aligning activities with assessment expectations in ECO151
• Adding opportunities for student engagement (e.g., additional problem-solving exercises)
• Ensuring consistency with departmental teaching approaches

Final Lesson Plan: Human-AI Collaboration

The final lesson plan was therefore:

• More contextually relevant
• Better aligned with student needs
• Pedagogically stronger than both the previous year’s plan and the raw AI output

Reflection: Lessons on Using AI for Lesson Planning

This case highlights several important principles:

• AI works best when prompts are detailed, structured, and context-specific
• Lesson plans generated by AI should be treated as drafts, not final products
• Effective teaching requires alignment with student context and curriculum goals
• Topic prioritisation remains a human, disciplinary decision
• Mathematical and conceptual topics require careful pacing and reinforcement

By making use of AI visible in teaching practice, we can shift the focus from efficiency alone to improved learning design, deeper engagement, and better student outcomes. We encourage colleagues to continue sharing discipline-specific examples of AI use in teaching and learning.