Understanding AI as an Educational Literacy

Artificial intelligence is increasingly present in search engines, translation tools, writing assistants, recommendation systems and educational software. Teachers need more than a list of popular applications: they need a clear understanding of what AI can do, where it can fail and how to help learners use it critically.

This five-day professional development course introduces AI literacy through accessible explanations, practical experimentation and classroom-focused discussion. Participants do not need programming knowledge or previous experience with AI tools. The emphasis is on informed professional judgement rather than technical complexity.

Teachers begin by examining familiar examples of AI in everyday life and education. They distinguish between systems that classify, recommend, predict and generate content. Small-group activities explore why an AI response can sound convincing while being inaccurate, incomplete or inappropriate for a particular learner.

A key workshop output is an illustrated AI literacy glossary that teachers can adapt for colleagues or students.

Exploring AI Tools Through Pedagogical Questions

Instead of treating AI adoption as an objective in itself, participants learn to begin with a teaching problem.

For example, a teacher may want to explain a difficult scientific concept to students with different reading abilities. Participants compare an AI-generated explanation with a trusted curriculum resource, identify inaccuracies, adjust the language and decide whether the result improves access to the concept.

Another workshop examines AI-generated discussion questions. Teachers evaluate whether the questions promote reasoning, encourage superficial answers or reproduce stereotypes.

Participants use a tool evaluation matrix covering instructional purpose, accuracy, age suitability, accessibility, cost and practical classroom constraints. The matrix also asks whether a simpler, non-AI method could achieve the same goal.

This approach helps teachers make deliberate choices rather than adopting technology because it is new.

Recognising Bias, Hallucinations and Hidden Assumptions

AI literacy includes understanding how data, design choices and user prompts can shape outputs.

Participants investigate examples involving gender stereotypes in career guidance, cultural assumptions in historical descriptions and unequal representation in generated classroom materials. They compare responses, identify patterns and discuss how to challenge questionable content.

In a source-verification exercise, groups receive AI-generated explanations containing a mixture of correct and incorrect claims. They verify information using reliable sources and annotate the material to show which statements require correction.

Teachers then design short classroom exercises that encourage learners to ask: Who created this information? What evidence supports it? Which perspectives are missing? What should be verified independently?

These questions can support critical media literacy across subjects.

Privacy, Copyright and Responsible Use

Responsible AI use requires careful treatment of personal information, intellectual property and professional accountability.

The course introduces relevant principles from the GDPR and the EU AI Act, while distinguishing general awareness from institution-specific legal compliance. Participants examine scenarios involving student work, assessment information, photographs and sensitive classroom circumstances.

Teachers practise rewriting prompts to remove personal information and explore safer alternatives such as fictional student profiles and locally approved resources.

Copyright discussions address AI-generated images and text, attribution, licensing, third-party materials and uncertainty around ownership. Participants are encouraged to verify the terms of any service before using or publishing generated content.

An important principle runs throughout the training: teachers retain responsibility for educational decisions, and AI-generated output requires human review.

Making AI Literacy Inclusive

AI literacy should be accessible to students with different language backgrounds, abilities and levels of digital confidence.

Participants adapt the same AI-related concept into multiple learning formats, such as a short reading, a visual explanation, a collaborative sorting task and an oral discussion.

A practical workshop focuses on multilingual learners. Teachers compare AI-supported translations and simplified explanations, checking whether important subject vocabulary and meaning have been preserved.

Participants also examine accessibility issues such as screen-reader compatibility, visual complexity, reading demands and unequal access to devices.

Activities are designed with offline alternatives so that responsible AI education does not depend on every student having an individual account or device.

Developing Classroom Policies and Student Agency

Teachers work collaboratively to create age-appropriate guidance for classroom AI use.

Possible rules address when AI assistance is permitted, how students should acknowledge its use, which information must never be entered into external systems and when independent work is required.

Groups analyse realistic scenarios: a student submits an AI-generated essay, a teacher uses AI to draft feedback, or a learner relies on an AI chatbot instead of checking sources.

Rather than focusing only on prohibition, participants develop strategies that encourage transparency, independent thinking and responsible decision-making.

The resulting framework can be adapted to existing school policies and local requirements.

From Training to Classroom Practice

During the final workshop, each participant develops a small-scale implementation plan. The plan identifies a suitable learner group, a specific AI literacy objective, a classroom activity, safeguards and simple evidence of learning.

Participants present their plans in peer-review groups and revise them using structured feedback.

Classroom-ready takeaways: an AI literacy glossary, tool evaluation matrix, bias-detection activity, student guidance template, privacy-aware prompting checklist and an individual implementation plan.

The course is designed to help teachers approach AI with informed curiosity, professional confidence and an appropriate degree of caution.