Lesson Plan

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Lesson Plan
Grade: Date: 25/02/2026
Subject: Information Communication Technology ICT
Lesson Topic: Know and understand characteristics, uses and purpose of expert systems including mineral prospecting, car engine fault diagnosis, medical diagnosis, chess games, financial planning, route scheduling for delivery vehicles, plant and animal identifica
Learning Objective/s:
  • Describe the key characteristics of expert systems and how they differ from general software.
  • Explain how knowledge bases and inference engines collaborate in domains such as mineral prospecting and medical diagnosis.
  • Evaluate the advantages and limitations of expert systems and suggest appropriate real‑world applications.
  • Apply a simple rule‑based reasoning example to solve a domain‑specific problem.
Materials Needed:
  • Projector and screen
  • Whiteboard and markers
  • Handout summarising characteristics, advantages & limitations
  • Case‑study worksheets for mineral prospecting and car engine diagnosis
  • Computers with internet access for a short demo video
  • Exit‑ticket slips
 Introduction:

Begin with a 2‑minute video showing an expert system diagnosing a car engine fault to capture interest. Ask learners what they already know about decision‑making software and link it to the lesson’s success criteria: students will identify core components of expert systems, discuss their uses, and critique their limitations.
Lesson Structure:
  1. Starter – video clip & quick discussion (5')
  2. Mini‑lecture: architecture of expert systems (knowledge base, inference engine, UI) with slides (10')
  3. Group activity: analyse a mineral‑prospecting case using provided data; fill worksheet (15')
  4. Whole‑class debrief: share group findings and map them to key characteristics (10')
  5. Think‑pair‑share: list advantages and limitations across all examples (10')
  6. Exit ticket: write one real‑world use and one limitation of expert systems (5')
Conclusion:

Summarise how expert systems combine domain knowledge with reasoning to support decision‑making, highlighting both strengths and constraints. Collect exit tickets to gauge understanding, and assign homework: each student researches an additional expert system in a field of interest and prepares a brief summary for the next class.