A subject lesson with visible language support
The content objective remains central. Vocabulary, sentence frames or models help students reach it.
CLIL stands for Content and Language Integrated Learning. Students learn meaningful subject content through an additional language while receiving deliberate support for the language they need to access, discuss and demonstrate that learning. It is not a language lesson with a subject-related theme.
A computer science teacher teaches network topologies in English using diagrams, six essential terms, sentence frames and structured comparison. Students learn the technical content and the language needed to justify a design choice.
The content objective remains central. Vocabulary, sentence frames or models help students reach it.
Learning subject words alone does not replace meaningful subject understanding and application.
Students compare, sequence, explain, solve, justify or create through the additional language.
Translation may support access, but it does not by itself create interaction, cognition or language growth.
Support responds to a barrier and helps students move towards greater independence.
A learner's current English level is not a measure of subject knowledge or thinking ability.
Plan for Content, Communication, Cognition and Culture.
Define the subject knowledge or skill students will develop.
Planning questionWhat should students understand or be able to do?
ExampleIdentify and compare network topologies.
Make the language needed to learn and explain the content visible.
Planning questionWhat words, structures and functions will students need?
Example“One advantage of a star topology is…”
Choose the thinking students will perform with the content.
Planning questionWill they compare, justify, solve, evaluate or design?
ExampleJustify which topology best suits a small workplace.
Notice perspectives, contexts and assumptions that shape the task.
Planning questionWhose context is represented or assumed?
ExampleCompare how cost and user needs influence network design in different workplaces.
Students compare three network topologies (Content), use technical terms and comparison frames (Communication), evaluate constraints and justify a recommendation (Cognition), then consider how workplace size, resources and user needs change the decision (Culture).
Plan for the language students need before, during and through the task.
Subject vocabulary and structures needed to understand the content.
Examples: database, primary key, relationship; “A primary key identifies…”
Language needed to compare, describe, justify, sequence, ask questions and collaborate.
Examples: “Can you explain…?” “Our group chose…” “I agree because…”
New language that emerges while students think, interact and refine understanding.
Example: a student realises that efficient is needed to justify a design choice.
State what students should understand, apply or produce. Keep this goal visible when adding language support.
Choose a meaningful process such as comparing, sequencing, solving, explaining, evaluating or designing.
Note essential technical terms and the language students need to participate and show their reasoning.
Use a diagram, short glossary, model, sentence frame, rehearsal or structured role where it opens access to the task.
Choose evidence that fits the content goal and clarify whether language is being formally assessed.
Select six to ten essential terms, explain them in context and recycle them during the task. Do not pre-teach every unfamiliar word.
Provide precise sentence frames, a model response and private rehearsal time before public speaking or writing.
Compare it with the permitted source. Restore technical terms, qualifications, causal relationships, numbers and process order before use.
Keep a shared content goal and vary text density, scaffolds, preparation time or output support rather than assigning unrelated work.
Use structured pair or group roles with a clear subject product and language that each student must use to contribute.
Decide what evidence of content understanding matters and whether language is a goal or mainly the means of showing that understanding. Avoid penalising one language difficulty several times.
Check and adapt AI drafts before using them with your class.
An AI-generated CEFR estimate is an approximate planning aid, not an objective language assessment.
The selected references in each handbook identify the sources used for the CLIL and responsible-AI guidance.