Active learning ideas
In an era of mass data collection, understanding privacy and security is a vital life skill. This topic covers how personal data is harvested, the ethics of data monetization, and the technical measures used to protect information. Students explore the tension between convenience and security, aligning with NCCA Learning Outcomes 1.6 and 1.7 regarding digital citizenship and ethical data use.
Activity 01
Students 'pay' for free apps using tokens representing their personal data (location, contacts, browsing history). At the end, the teacher 'sells' this data to mock advertisers to show how much information was traded for a simple game.
Who owns the data we generate online?
Activity 02
A fictional tech company is on trial for a data leak. Students take roles as lawyers, engineers, and affected users to argue whether the company took 'reasonable' steps to protect user data according to GDPR principles.
What are the ethical implications of mass data collection?
Activity 03
In pairs, students examine the permissions requested by popular apps on their phones. They categorize these as 'essential' or 'excessive' and present their findings on why an app might want access to data it doesn't seemingly need.
How can citizens protect their digital privacy?
A few notes on teaching this unit
Watch Out for These Misconceptions
I have nothing to hide, so data privacy doesn't matter to me.
Use a role-play scenario to show how 'innocent' data can be used to influence insurance rates or job opportunities. This helps students see that privacy is about control and protection from misuse, not just hiding secrets.
Incognito mode or private browsing makes me completely anonymous.
Explain that these modes only hide history from the local device, not from the ISP or the websites visited. A quick diagrammatic activity can show the path data takes to clarify what is actually hidden.
Methods used in this brief
Designing for Marginalised Users
Understand the importance of inclusive design and how to create software that supports marginalised groups.
8 methodologies
Artificial Intelligence and Future Societies
Discuss the rapid advancement of AI and its potential impact on future employment, ethics, and daily life. Debate the moral responsibilities of software developers in creating autonomous systems.
8 methodologies