Principle I Safe use of AI in language education

Are our uses of AI legally compliant, transparent, and risk-free?

GUIDELINE 1

Comply with legal requirements & institutional standards

Review terms of service and age restrictions before use
Ensure learners can legally consent; seek parental permission where needed
Attribute AI-generated content; protect learner intellectual property
Maintain accountability — teachers remain responsible for outcomes
EU AI Act 2025 prohibits emotion recognition and real-time facial recognition in schools

GUIDELINE 2

Safeguard data security & digital safety of all participants

Understand what data (voice, writing, metadata) AI tools collect
Vet tools for GDPR / FERPA compliance; check retention policies
Minimise personal data in prompts; avoid sharing identifiable work
Protect vulnerable learners (minors, migrants, refugees) from data misuse
Advocate for institutional data-protection policies

Key competences (1–10)

Interpret ToS Verify legal compliance Protect learner IP Maintain accountability Evaluate data practices Identify data collected Assess proportionality Raise awareness Protect vulnerable learners Advocate for policy

Did you know?

Some AI platforms (e.g. ChatGPT) allow users to opt out of model training via account settings → Settings → Data Controls → toggle off "Improve the model for everyone."

Principle II Responsible use of AI in language education

Does our use of AI position teaching as a force for positive change?

GUIDELINE 3

Promote social justice & linguistic and cultural diversity

Balance AI tasks with authentic human interaction
Monitor learner fatigue and disengagement from excessive AI use
Critically evaluate AI outputs for bias, stereotypes and cultural hegemony
Address infrastructure and access inequalities (TPACK development)
Use AI to support under-resourced languages and plurilingual learners

GUIDELINE 4

Foster environmental sustainability

Be aware of AI's carbon, water and energy footprint
Use calibrated, purposeful AI — not routine default use
Prefer open image banks over AI image generation where possible
Web searches use 10–30× less energy than AI-generated content
Push AI vendors to disclose environmental metrics per operation

Key competences (11–18)

Preserve human connection Evaluate knowledge access Promote equitable access Evaluate for bias Advance linguistic diversity Recognise environmental impact Minimise footprint Collective responsibility

Did you know?

Advanced LLMs still exhibit implicit biases — associating negative language with certain racial groups, linking women with humanities over science, and favouring men in leadership contexts (Maslej et al., 2025).

Principle III Purposeful use of AI in language education

How does AI add genuine pedagogical value to teaching and learning?

GUIDELINE 5

Enhance sound language teaching pedagogy

Prioritise quality of AI use over quantity of AI tools
Use AI for personalised, differentiated learning pathways
Support assessment redesign: shift from knowledge artefacts to process
Use the IDEA framework for effective prompt design (Park & Choo, 2024)
Leverage speech-to-text / text-to-speech for inclusive multimodal learning

GUIDELINE 6

Create novel language learning opportunities

Add value — don't just substitute traditional tasks (SAMR framework)
Use AI for first-pass feedback, freeing teachers for deeper interaction
Challenge classroom monolingualism via plurilingual AI scaffolding
Enable context-sensitive, learner-centred bottom-up syllabus design
Avoid tokenistic use — ensure clear pedagogical goals for every AI activity

Key competences (19–27)

Personalise teaching Differentiate learning Effective prompting (IDEA) Ethical assessment Evaluate outcomes Assess instructional value Performative vs transformative Pedagogical intent Retain teacher judgment

IDEA prompt framework

Include essential PARTS (Person, Aim, Recipient, Theme, Structure) · Develop with CLEAR prompts (Concise, Logical, Explicit, Adaptive, Restrictive) · Evaluate and REFINE iteratively · Apply with accountability

Principle IV Reflective use of AI in language education

How can teachers and learners use AI reflectively and maintain professional agency?

GUIDELINE 7

Empower teachers as autonomous, critical agents

Use AI as a source of on-demand microlearning and professional support
Broaden methodological repertoire via AI-generated worked examples
Assign AI the role of "critical colleague" to review lesson plans
Generate CLIL, flipped classroom or differentiated instruction examples
Move from end-user to co-designer of AI tools and policies

GUIDELINE 8

Support agentic use of AI by teachers & learners

Use AI for reflection-for-action: generate and compare lesson variants
Make real-time pedagogical judgements during AI-assisted lessons
Use AI transcripts/analytics to analyse and reflect on completed lessons
Support classroom-based inquiry and teacher-led scholarship
Reflect on how AI use positions language teaching within social values

Key competences (28–35)

Access professional knowledge Microlearning Broaden repertoire AI as mentor Reflection-for-action Reflection-in-action Reflection-on-action Critical positioning

Example reflective prompt

"Assume the role of a critical friend and experienced language educator. Help me reflect on today's lesson … Ask probing questions about: (a) what worked well, (b) what to do differently, and (c) how AI influenced the dynamics."