Data, Information and Data Protection

Learning Objectives

• Distinguish between data and information.
• Name common sources of data.
• Explain how data becomes information.
• Describe personal data and how to protect it.

Data and Information

Data is raw, unprocessed facts and figures. It can be numbers, words, images or sounds, and on its own it does not tell you anything useful. The numbers 85, 72, 90, 68 and 77 are just numbers until you know what they represent.

Information is data that has been processed, organised and presented in a way that gives it meaning. When a teacher writes Student Names and Science Test Scores above those numbers, they become information. The same data can give different information depending on how it is processed.

Sources of Data

Data comes from many sources. Forms and questionnaires collect data when people fill in registration or hospital forms. Surveys and interviews collect data by asking questions. Sensors and instruments collect data automatically, such as weather stations recording temperature.

Other sources are online transactions, school records, social media activity and government records such as a population census. Every time you fill a form, take a test or browse a website, you generate data.

Structured data means data arranged in a clear format such as a table.

Unstructured data means data with no fixed format, such as photos or voice notes.

How Information is Produced

Data becomes information in four steps. First, raw data is collected from a source. Second, it is organised in a logical order, such as sorting scores from highest to lowest. Third, it is processed by calculating, sorting or grouping. Fourth, the result is presented in a useful form, such as a chart or a report.

A hospital collects patient temperatures, organises them by time, processes them to spot fever cases and presents the information to doctors for decisions.

Primary source means a source where data is collected first hand.

Secondary source means a source that provides data collected by someone else.

Personal Data

Personal data is any information that can be used to identify a person. It includes your full name, date of birth, address and phone number; financial data such as bank details; educational data such as results; health data such as medical records; and online data such as passwords and browsing history.

Personal data is valuable and must be kept safe, because criminals can use it to steal money or pretend to be you.

Data Protection

Data protection is the practice of keeping personal data safe from unauthorised access, loss or misuse. Organisations should collect only the data they need, keep it secure, use it only for the stated purpose, delete it when it is no longer needed, allow people to see their own data and obtain consent before collecting it.

In Nigeria the Nigerian Data Protection Regulation, or NDPR, requires organisations to protect the personal data they collect. Schools, banks and hospitals must follow these rules.

Protecting Personal Data and Responsible Handling

To protect personal data, use strong passwords, turn on two factor authentication, keep software updated, avoid sharing personal details publicly and back up important files. On shared computers, sign out when you finish.

Responsible handling means treating other people's data with care. Do not post a classmate's results without permission, use survey data only for the school project, delete old files holding personal information and report any misuse of data.

Practical Work

1. Collect the marks of ten pupils and turn the raw data into information by finding the average and the highest score.
2. List five sources of data and give one example of each from your school.
3. Write three rules of data protection and explain each in one sentence.
4. State three ways to protect your personal data online.

Scenario-Based Questions

1. A school collects students' names, dates of birth and home addresses on a registration form. Classify this as data or information and explain the difference.
2. A hospital records a patient's temperature, blood pressure and weight. A doctor then writes a diagnosis. Explain how the raw measurements become useful information.
3. A social media app asks for a new user's location, contacts and photo gallery. Explain why this raises concerns about personal data.
4. A classmate posts another student's exam results in the class group without permission. Explain why this is wrong, using data protection ideas.
5. A company keeps customer records only on one laptop. The laptop is stolen and the records are lost. Explain why both a cloud backup and an offline backup are important.
6. Give two ways a school could follow the NDPR when collecting student information.
7. Give two ways to protect your personal data online.

Lesson objectives

By the end of the week, learners should be able to:

1. Distinguish raw data from information and explain why context matters.
2. State four principles of data protection such as minimisation and consent.
3. Classify learner information as sensitive and non-sensitive.
4. Apply the four data-protection principles to a sample dataset.
5. State three rights learners have over their own data.

Key vocabulary

• Raw data: facts taken straight from a source without interpretation.
• Information: processed data made meaningful by context.
• Context: the circumstances that give data meaning.
• Data protection principle: a rule governing how data may be handled.
• Minimisation: collecting only data strictly necessary.
• Consent: permission granted by the data owner.
• Sensitive data: data about health, location or financial status.
• Rights: legal entitlements holders have over their own data.

Common misconceptions

• "Raw data and information are interchangeable." Raw data needs interpretation to become information.
• "More data collected is always safer." Excess data increases risk rather than reducing it.
• "Consent means just ticking a box." Consent must be informed and freely given.

Teacher activities

1. Starter: hold up a list of scores and a cleaned averages list and ask which is information.
2. Define raw data and information by contrasting them with an example each.
3. Name four data-protection principles and explain each briefly.
4. Model classifying learner information into sensitive and non-sensitive categories.
5. Apply the four principles to a sample dataset on the board.
6. Close with the exit question and a five-item recall quiz.

Student activities

1. Answer the starter and explain why context turns data into information.
2. Name four data-protection principles with one example each.
3. Classify learner information into sensitive and non-sensitive groups.
4. Apply the four principles to a sample dataset and note the outcome.
5. State three rights learners have over their own data.
6. Complete the five-item recall quiz and mark their own answers.

Practical / learning evidence

A raw-data-versus-information worksheet, a four-principle application worksheet and a three-right learner-rights sheet. Submit all three for marking.

Resources and preparation

Sample datasets, printed application templates and a rights-reference card. Offline route: paper versions, no device needed. Warn learners not to process real learner information in any task.

Assessment for learning

Inspect the data worksheet for correct raw versus information separation. Mark the application worksheet for sensible application of all four principles. Check the rights sheet for three concrete entitlements. Flag any learner who thinks more data is safer.

Inclusion and homework

Provide sample datasets preclassified as raw and processed for learners who need scaffolding. Allow oral completion of the principles worksheet. Extend confident learners with five principles. Homework: name one right learners have over their own data and state why it matters.