Lesson Notes By Weeks and Term v4 - JHS 1
ARTIFICIAL INTELLIGENCE
Download the Lessonotes Mobile Ghana app for faster lesson access on Android and iPhone.
ARTIFICIAL INTELLIGENCE
Download the Lessonotes Mobile Ghana app for faster lesson access on Android and iPhone.
Subject: Computing
Class: JHS 1
Term: 3rd Term
Week: 13
Grade code: B7.4.4.1.1
Strand code: 4
Sub-strand code: 4
Content standard code: B7.4.4.1
Indicator code: B7.4.4.1.1
Theme: COMPUTATIONAL THINKING
Subtheme: ARTIFICIAL INTELLIGENCE
This page supports the lesson note with a companion video and a short classroom-ready summary.
For class groups and homework, share this lesson page so learners also get the summary, objectives, and full lesson context.
Artificial Intelligence (AI) is a rapidly growing field of computing that is changing our world. It is the ability of computers and machines to think, learn, and solve problems like humans. From the recommendations we see on YouTube to the way farmers can monitor their crops, AI is already present in our lives in Ghana. This lesson will introduce learners to the fundamental concepts of AI, its different types, and how it is being used to solve problems and create opportunities in our society. Understanding AI is crucial for becoming a digitally literate citizen in the 21st century.
Introduction to AI
Start with a simple question: "Have you ever used a phone to take a picture and seen it automatically focus on someone's face? Or have you asked Google a question with your voice? How does the computer know what to do?"
This is the work of Artificial Intelligence (AI). Definition: Artificial Intelligence is a branch of computer science that deals with creating smart machines capable of performing tasks that typically require human intelligence. Think of it as making computers think, learn, and make decisions like humans. Key Technologies in Artificial Intelligence (General Definitions Only)
We will look at some of the important "building blocks" or types of AI. Machine Learning (ML) Explanation: This is the most common type of AI. Instead of giving the computer instructions for every single step, we "teach" it by showing it a lot of examples (data). The computer then learns to recognize patterns and make predictions on its own. Analogy: Imagine you want to teach a small child the difference between a mango and an orange. You don't write a long list of rules. You just show them many mangoes and many oranges. After seeing enough examples, the child learns to identify them correctly. Machine Learning works in a similar way for computers. Ghanaian Example: A bank in Ghana could use ML to look at thousands of loan applications. By showing the computer which loans were paid back and which were not, the computer learns to predict if a new applicant is likely to pay back their loan. Deep Learning (DL) & Artificial Neural Networks (ANN) Explanation: Deep Learning is a more advanced and powerful type of Machine Learning. It uses something called an Artificial Neural Network (ANN), which is designed to work like the human brain with its many connected neurons (brain cells). These layers of "neurons" help it learn from huge amounts of data. Analogy: If Machine Learning is like teaching a child to recognise a mango, Deep Learning is like the child's brain automatically learning the concept of "fruit" and being able to identify a new fruit it has never seen before, like a pawpaw, by recognising its features (shape, colour, texture). Example: Voice assistants like Siri or Google Assistant use Deep Learning to understand the complex patterns in your speech. Data Mining and Analytics Explanation: This is the process of "digging" through very large amounts of information (data) to find useful patterns, trends, and hidden treasures of knowledge. Analogy: Imagine you are a detective searching for clues in a huge, messy room. Data Mining is like having a special tool that can instantly find all the important clues and tell you what they mean. Ghanaian Example: A company like MTN or Vodafone can analyse call records (without seeing the content) to see which areas have a lot of network traffic. This data helps them decide where to build their next phone mast to improve service. Virtual Reality (VR) and Augmented Reality (AR) Virtual Reality (VR): This technology creates a completely artificial, computer-generated world that a user can step into and interact with. You usually need a special headset. Analogy: VR is like being transported inside a video game or a movie. The real world is completely blocked out. Example: A student could take a virtual tour of the Elmina Castle or the Kakum National Park canopy walk without ever leaving the classroom. Augmented Reality (AR): This technology overlays computer-generated images, sounds, or information *onto* the real world as we see it, usually through a smartphone camera. Analogy: AR is like adding stickers or information on top of the real world. You can still see everything around you. Example: Snapchat and Instagram filters that put funny ears or glasses on your face are a popular form of AR. Gamification Explanation: This is the technique of using game-like elements (like points, badges, leaderboards, and challenges) in non-game activities to make them more fun and engaging. Analogy: It's like turning your homework into a game where you score points for every correct answer and can "level up" to the next topic. Example: A mobile money app could give you badges or reward points for making a certain number of transactions, encouraging you to use the service more. Uses and Importance of AI in Society