Lesson Note – 2nd Term JSS 1 Computer Week 2

Introduction to Lesson Note – 2nd Term JSS 1 Computer Week 2

I wrote this Lesson Note – 2nd Term JSS 1 Computer Week 2 based on the newly revised Nigerian 9-Year Basic Education Curriculum (UBE Edition). Particularly, I used the New Junior Secondary School Teaching Schemes of Work. The various state ministry of education and the Education Resource Centre, Abuja developed the teaching schemes between 2014 and 2016. Click here to download the most recent schemes of work for Pre-primary through Senior Secondary Schools. These schemes are the same for the 36 states of the federation and the FCT. Hence, this lesson note is suitable for use in any Nigerian school that adopts the National Curriculum.

Complete Lesson Objectives

As with the rest of our notes, the primary focus of this lesson note is to present an enriched content for the topic. This lesson notes, also like the rest, provide guide for teachers on how to deliver the content to attain the topic objectives. In this regard, I adopt the subject-specific modern teaching style in the FTS manual.

 Unlike most lesson notes which focuses majorly on cognition, I brought out and set objectives to cover other domains of education – affective and psychomotor. This is to ensure a balanced learning experience for the learners.

Leading Guide To Adapting This Lesson Note

I wrote this lesson note in outline of standard lesson plans. However, I advise teachers that want to use this note for official purpose – i.e. to create their lesson plans which they will submit to their supervisors – to get our Lesson Plan Template. The layout of the template makes it easy for teachers to write a professional lesson plan and easily.

REMARK: If you find the terms lesson plan and lesson notes confusing, click here to quickly read my article on their differences.

Term: Second Term

Class: Junior Secondary School (JSS) 1

Week: 2

Curriculum: NERDC Revised 9-Year Basic Education Curriculum (BEC)

Topic: Data Processing

Sub-topic: Meaning of Data


At the end of the lesson, the students should be able to:

  • state the meaning of data

Step 1: Introduction

The teacher introduces the lesson in the following steps:


  1. Formulate stimulating sentences that cut up into component words equal to the number of students in the class. For example, below are two sentences. The total number of words in both sentences is 17. Therefore, these sentences are ideal for a class of 17 students.
    1. There, is a packet of biscuits.
    1. The first person to reach my desk will have it all.

Note that none of the words in both sentences make total sense when you say only it to someone.

  • Write out each word in the sentences on a piece of card.


  • Tell the students that you will give them an instruction. Successful completion of the instruction has a reward. The first student to carry out the instruction wins the reward.
  • After that, randomly give a card on which you have written a word from the sentence(s) to each of the students. Then tell them that you have now given the instruction to them.
  • Give them a moment to figure out the instruction and to complete the task. This may be 2-3 minutes. You may act absent while the students attempt to do this.
  • Once the time elapse, recall the students’ attention. Then, ask if any of them was able to figure out the instruction in the information you gave them. It is very likely none will. So, request them to keep their card save and that by the time the lesson is ended, they would have figured it out.
  • Follow this up with by showing the students a live dataset for any daily transaction or activity. I recommend Binance market chart. Let the students watch the numbers for a while. Afterwards, ask them if they make a sense out of the number series. They probably will not. Therefore, proceed with the introductory explanation thus:
Introductory Text
Information we learn from Instruction

Information is part of our life. We receive countless amount of information every day. We get some kinds of information from the people that we live, meet and interact with. For example, when people ask us a question; or gives us instructions; tell us a meaningful story; or when they just let us to know something useful like a teacher.

Information we learn by deduction

However, there are other kinds of information that we do not get from people. Instead, we deduce (find them out) from our observations. For example, when you visit a friend and s/he does not want you around. That friend may not tell you to go, but you will deduce his/her intentions from what you observe – the body language.  Another example of information we deduce is your parents’ or siblings’ favourites. They may not tell you their favourite colour, food or drink. But after you observe their fondness of it, you know what they like and dislike.

Importance of Information

Both kinds of information are very important to us in life. Everything we know which helps us to become what we are today and what we will become in future is through the information that we get/have. Good kinds of information make us good and bad information makes us bad. Most importantly, having the right information helps us to make right decisions. Be it our choice of school, what we will buy, places to go or not to go, what to do or not to do, etc. are all as a result of the information we have.

Data Analyst & Data Analysis

In fact, life is almost impossible without information. As a result, we have to be able to get all the information we can. Getting the kind of information that people tell us is not difficult. But getting information from what we observe (just like the live dataset and card) has more work. Not many people can do it. In fact, we have to be trained to be able to do it easily and faster. The people that learn this skill of getting useful information from what we observe are called Data Analyst. So, Data Analysis is the “subject” that teaches us how to get useful information from pieces of observation. Data Analyst is one of the most in-demand and highest paying job in the world right now and will continue to be in future. As at January 2023, Data Analyst in Nigeria earn between 2 to 15 million naira per year or 150,000 to 1.2 million per month (Payscale).

Conclusion of Introduction

  • After the introductory explanation above, ask the students who would like to become a data analyst.
  • Further, tell the students that one of the things that data analyst do is called data processing. Hence, explain that data processing is the step-by-step work of getting useful information from the pieces of our observations.
  • Finally, tell the students that they shall learn about, and acquire the skill of data processing in the next 3 weeks. Tell that if they master the skills, you will teach them, they could even put up for part-time data entry jobs when they get to JSS 3. After that, tell them that the first thing they will learn about data processing is the meaning of key terms – data, data processing & information. Finally, list the objectives of the lesson on the screen/board and explain each to the students.

Step 2: Meaning of Data

  1. Briefly recap/describe the tasks of data scientist: getting useful information from our pieces of observations.
  2. Ask the students what they think data is in relation to the meaning above.
  3. At the end of the ensuing discussion, project/write the definition of data on the screen/board. Then, explain the definition thoroughly as follows:

Definition of Data

Data is a character or a collection of characters for expressing fact or a collection of raw facts; which may not make complete sense but can be processed to get better information.

Explanation of the meaning of data

  1. Read out the definition a few times.
  2. Help the students to memorize the definition. Ask them one after another or randomly (focusing more on average to slow learners).
    1. You may help them to be able to write it by dictating it while they write in their jotter.
    1. Tell them to write it down offhand.
  3. Once you ascertain that the students are able to say and write the definition of data, explain thoroughly. Below is the text of explanation to guide you.
A Character as Data to Computer

In computer, a character is a letter (alphabet), number or a mark (sign) that has a known meaning. A character is also called a symbol. Examples of characters are:

  1. Letters (alphabets) A – Z and letters a – z.
  2. All numbers including negatives and fractions
  3. Punctuation marks like comma, full-stop, question mark, etc.
  4. Special symbols like @, #, $, %, +, -, /, etc.
  5. Whitespace (empty spaces like when you press spacebar, tab and enter keys).

Data as a character means that any of the characters above is data to computer. When you press letter A on a computer, you have given it data. And a major characteristic of data is that it may not make a complete sense. In other words, we may not totally understand it until we have done some sort of work on it – that is processing. Similarly, computers do not instantly understand the letter A you pressed on the keyboard. As such, it cannot store or retrieve it until it has performed some sort of work on it.

In this case, the work that the computer performs on letter A is changing it to binary (zeros and ones). This is because binary is the only language the computer understands – the only thing it really knows and operate with. They will learn how the computer does this in JSS 2 – Data Representation.

A Character as Data to Human Being

Just as a character is data to computer, it is also data to human being. How? Imagine you just awake from sleep in the morning. Then a stranger hand you a character (say number 2) without saying any word. Will you be able to make sense out of it? Absolutely not or even if you do, not with certainty.

To make complete sense out of the character that the stranger gave to you, you have to do some sort of work on it. That work may be asking the stranger what the (number) character means or what it is for. It is only when the stranger has explained this that you will know that the character (number 2) which s/he gave to you represents 2 beautiful cars that s/he has just gifted you.

Hence, the character is data because to make complete sense out of it, we have to do some sort of work.

Data as a Collection of Characters

Not only is a single character data but a collection of characters also constitute data both to computer and to human being.

Examples of data as a collection of character are:
  1. Words and sentences – two or more letters written together. E.g., at, am, etc. It is important to note that computer understands a word different from how it understands each of the component letters in the word.
  2. Numbers (figures) – 20, 400, etc. Just as words, a two- or more-digit figure is different from its component digits to the computer.
  3. Alphanumeric characters – characters that contains a combination of alphabets, numbers and symbols. E.g., Vehicle plate number (RN234), Email (yourname@something.com), Units (100ºC).

Generally, a group of characters comprising of letters, numbers and special symbols are called a text. Each of these collections of characters are series on zeros and ones the computer.

Images, Audios & Videos as Data to Computer

When we talk of a collection of characters as data, this is how computer sees images, audios and videos. Computer does not see images as pictures like we do. More so, computers do not understand audio as sound nor video as sound and moving images.

Instead, within computers, each of these are huge collections of characters (zeros and ones). So, whenever you see/hear or work with images, audios and videos on a computer; the computer has to first of work on them – i.e., change to and from zeroes and ones – before the computer can understand and manipulate these kinds of data.

Hence, images, audios and videos are data in computers.

Similarly, images, audios and videos may be data to human beings. If they do not make complete sense but are expressing facts and can be processed to make more meaning out of them; then such is data.

For example, the sound produced by different rocks when a geologist hits them is data. Why? This is because the geologist listens to the sound to get more information about the rocks.

Other examples of images, audio and videos data are:

  1. Sound/images showed by reCAPTCHA which a user gets verification code from.
  2. Ultrasound scans and X-ray images which medical personnel study to understand a health issue better.
  3. CCTV footage (images/videos) which security agents watch to trace a breach.
  4. Murals or drawings on ancient walls and inside caves which an archaeologist studies to get information about something or a people.
  5. Evidence presented at a court proceeding which the jury listen to or watch to get more information about a situation.
  6. Etc.
Data as Representation of Facts

Now that you know what constitute data, it is also important to know that not all writings, sound, images and videos qualify as data to human beings. One cannot just formulate any arbitrary character or combination of characters to form valid data. Within human context, data has to express or represent facts or concepts that the originator observes.

A fact refers to anything whose existence or occurrence can be proven or is a consensus (known or agreed upon).

For example, X-ray images can be proven. Say when it shows a foreign object in a body, a surgeon proofs this when s/he performs operation on that part of the body and retrieves the foreign object.

NOTE: At this point, the teacher introduces an aspect of information literacy to the students by teaching them to verify new information before propagating it.

Therefore, whatever data you formulate for human consumption should be capable of producing more meaning. This means it should have some sort of explanations. For example, writing a thousand different numbers without telling what it represents may not fit in the definition of data. However, I can turn it into valid data by titling it as ages of 1,000 people. Of course, each of the ages is raw fact.

Data As a Collection of Raw Facts

So far, we have seen what data means to computer – just about anything you feed it and it has to work on. The general work that computer performs on all data is conversion to streams of zeros and ones (binary). It is only when computers convert data to binary that it understands it and it can save and retrieve it.

We know that data may be just one character like letter “A” alone. We also know that many characters like a words, letters, figures and sentences are also data. Finally, we learned that images, audios and videos are also data.

Now, we have to understand that data processing does not stop at the way computers process data internally – i.e., conversion to binary (and) for manipulation. In fact, what data means to computers is not the same as what it means to data analysts.

While computers consider just about any character or simple set of characters as valid data, data analysts see data differently.

To data analyst, and in general human business; data is a collection of raw facts which we can work on to get more meaning or better understanding. This means that to data analysts and in business, valid data may already have some sort of meaning. Basically, we have to know what the data represent. For instance, the various ages of all the people in a class is data.

Examples of valid data

Other examples of valid data to data analyst and in business are:

  1. The list of sports that a group of 50 students play.
    1. Gender of all the students in a school.
    1. Political parties of all senators in Nigeria.
    1. Number of times that each teacher goes to class in a day.
    1. The population of people in a country over a period of ten years. Etc.

All of these are valid data to a data analyst and in business.


After these examples, the teacher engages the students:

  1. First, ask if any student can tell at least two features that all these examples have in come. Once a they do, or if they couldn’t; point these out to them as features of valid data in business:
    1. Each of the examples is a collection. That is, each represent data we collect from many actors. For instance, the list of sports in the first example is collected from many (50) students not one student. Also, the gender in the second example is for many students; political parties in example 3 is from many senators.
    1. The second feature of valid data in business is that it has common definition. By this, I mean that even though the data is a collection from many actors; we still describe all of the collections under one title. For instance, in the first example; the 50 different collections are all list of sport. Also, in the second example; the collections from all the students are all gender.
  2. Basing on the features of valid data in business, ask the students to give more examples of valid data in business. You may need to re-elaborate the features of valid data in business as guide for the students to give more examples of.
  3. Subsequently, tell the students that their ability to state examples of data in business shows that they understand the meaning of data. Thus,
  4. Project/Write a brief note on the meaning of data on the screen/board for the students to copy into their notebooks – if applicable.

Check back for note summary

  • In conclusion, read the notes with the students and revisit any necessary explanations. Thereafter, reveal to the students that even though the examples of data they have seen makes some sense, we can obtain further understanding from the data after we work on it. So, display some data sample and ask the students to say what the data sample tells them.

Succeeding this, reiterate that to get more meaning from data, we have to do some work on it. Example of work we can perform on data is re-arranging or sorting. Then, reveal to them that if they put all the cards which you gave them at the introduction together and arrange it, they will make meaning of the data.


Prior to concluding the lesson, the assesses the students’ understanding of the lesson. Check back for evaluation questions.


Conclude the lesson by revising the contents and linking it to the next topic.