Learning StudioIBDS · Standard Level

Operation Get a 7

Digital systems.
Human consequences.

Understand how technology works. Test what the evidence supports. Explain what should happen next.

Find your next step ↓
Trace the system, question the evidence, then defend a judgment.

One task at a time

Start with the task your teacher assigns.

This page shows the resources currently released for the class. More sections will appear as the course progresses.

01

Understand the target.

Read the task and its criteria. Identify the knowledge and thinking you need to demonstrate.

02

Keep the evidence.

Save source details, working notes and your decisions. Explain how you reached your answer.

03

Improve, then transfer.

Act on feedback. Show the improvement on a different question or changed situation.

Current sprint

Sprint 4 · When the service goes offline

Learn how computers and networks work, diagnose failures from evidence, and decide what a public service should restore first.

Published student workbook

Continue your current sprint

Open the workbook for all eleven lessons, lab assets, success criteria and released submission links.

Open Sprint 4 workbook — When the service goes offline

Choose your assigned practice

Older practice resources. Open the task your teacher assigns; these are separate from the current Sprint 4 workbook above.

Case study · Paper 1-style practice

Who owns your face?

Investigate facial recognition, power and privacy. Build an evidence-supported response to a real-world issue.

Open practice — Who owns your face?

Know what strong work does

Both paper styles begin in Sprint 1. Learn the criteria, practise with support, then show what you can do independently on a new task.

Paper 1 · Explain, apply, evaluate

Make the reasoning visible.

  • Use precise knowledge and explain the digital mechanism.
  • Apply it to the actual scenario and people affected.
  • Develop a judgment that weighs evidence, alternatives and conditions when the question asks for evaluation.

Short questions use task-specific marking. Extended responses use the applicable markband. Naming every concept is not a substitute for answering the question.

Paper 2 · Interpret, connect, synthesize

Make the sources work together.

  • Interpret what a source supports and where it is limited.
  • Explain agreements or tensions across sources.
  • Combine source evidence and relevant knowledge into an argument organized by ideas.

We start with a small source comparison and build toward sustained synthesis. A guided paragraph is practice, not a full-paper score.

Your feedback loop: see the criteria → attempt the task → identify one important improvement → try a fresh question. Your teacher records achievement separately from the support you used. Follow each task’s AI and access conditions; independent assessments require your own reasoning.

The course pathway

A one-year SL pathway. Your teacher releases the detailed assignments as they are ready.

01–07

Build knowledge through cases

Mechanisms, data, networks, AI, media and the physical impacts of digital systems. Paper 1 and Paper 2 practice throughout.

08–10

Practise inquiry and test transfer

A practice inquiry followed by Paper 1 and Paper 2 diagnostics, feedback and repair.

11–13

Develop your own inquiry project

Protected research, analysis, production and permitted feedback time.

14–16

Demonstrate readiness

Fresh full papers, targeted repair and a focused final revision route.

Sprint 02 · Age assurance and policy judgment

Sprint 02

How can a platform protect young users while limiting new data and access costs?

What you will learn

Verification, estimation and inference; policy objectives; impact versus implication; conditional judgment.

What you will work toward

An age-assurance recommendation supported by mechanism comparison, source synthesis and changed-context transfer.

Open workbook ↗

Sprint 03 · Data, algorithms and recommendation

Sprint 03

Who benefits when a feed optimizes attention?

What you will learn

Data lifecycle, databases, algorithm components, ranking, feedback loops, scale and algorithmic dilemmas.

What you will work toward

Paper recommender, theme synthesis and an independently redesigned ranking rule.

Open workbook ↗