Artificial Intelligence · JHS3 Computing

Lesson notes

Learning Objectives

Indicator: B9.4.4.1.1 - Describe the knowledge-based systems (Expert systems) as the classical Artificial intelligence

By the end of the lesson, learners can:

Define an expert system and explain its three main components (knowledge base, inference engine, and user interface) in their own words.
Trace the steps of an IF-THEN rule through an expert system to show how a query produces an output.
Construct a simple IF-THEN rule set for a given scenario (e.g. diagnosing a crop disease or a common illness) and test it with sample inputs.
Demonstrate how to input a request into a knowledge-based system, such as a telemedicine system, and interpret the output generated.
Explain, with examples, how machine learning (as demonstrated by Google’s Teachable Machine) differs from classical expert systems in the way it acquires knowledge.

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Curriculum details

Strand: Computational Thinking (Strand 4)
Sub-strand: Artificial Intelligence (4.4)
Content standard: B9.4.4.1 - Discuss Artificial intelligence Concepts
Indicator: B9.4.4.1.1 - Describe the knowledge-based systems (Expert systems) as the classical Artificial intelligence
Suggested placement: Term 3, Week 12 (Week 36 of the year)
Our suggestion, laid out in curriculum order across three terms of twelve weeks. NaCCA does not fix the week, so follow your school's scheme of learning.
Curriculum reference: Computing, Common Core Programme (JHS1-JHS3), 2023, p. 56
Transcribed from the official NaCCA publication. Check this page against the source.

Exemplars (from the NaCCA curriculum)

1. Illustrate the use of IF-THEN control structure for querying an expert system
2. Demonstrate how to input a request in any knowledge-based system to generate an output or result (e.g. Telemedicine system)
3. Demonstrate how to go onto the web and use Google's Teachable Machine demo to get a basic understanding of how machine learning works (e.g. Whatisit as an open-source cloud-based app which can identify the object in an image/photo)
NB: Demonstrate how data is collected and the extent to which information can be used. Also discuss thoughts on machine learning. https://teachablemachine.withgoogle.com