Project Nº: 2024-1-PL01-KA220-SCH-000256498
Target Age Group
11–14 years (primary differentiation for 7–10 years noted where applicable)
Estimated Duration
3 sessions of approximately 50–60 minutes each (total: approx. 165 minutes)
This module is grounded in the CLIL methodology, where alongside the constructivist and socio-cultural learning theory, it recognizes that meaningful learning occurs when pupils actively create, explore, and reflect within authentic social contexts. For migrant pupils navigating new educational environments, the theme of future skills and creativity offers a powerful entry point: it focuses on potential and possibility rather than deficit, building confidence and agency alongside language competence.
The module integrates BICS (Basic Interpersonal Communication Skills) and CALP (Cognitive Academic Language Proficiency) development through progressively complex activities. Early scenarios prioritise accessible, conversational language around familiar concepts such as ‘What is creativity?’ and ‘What jobs might exist in the future?’, before building towards more demanding analytical and evaluative language in Scenario 3. Vocabulary scaffolding, visual supports, and sentence frames are embedded throughout to support language acquisition at all levels.
The module also incorporates principles of Digital Multimodal Composing (DMC), enabling pupils to combine visuals, symbols, oral language, gestures, and short written text to communicate ideas even when their proficiency in the host language is still emerging. By reducing dependence on extended written production, the module lowers cognitive overload and allows pupils to demonstrate creativity, reasoning, and participation through multiple communicative modes.
Alignment with the TELMS framework is reflected in the relational approach to mentoring, the integration of digital tools as both creative and analytical instruments, and the emphasis on pupils’ own voices and perspectives. The module also draws on the DigComp 2.2 framework (particularly Areas 1, 2, and 5: Information & Data Literacy, Communication & Collaboration, and Problem Solving) and on Content and Language Integrated Learning (CLIL) principles, ensuring that conceptual and linguistic development are mutually reinforcing.
Throughout this module, the mentor functions simultaneously as a language model, creative facilitator, and emotional scaffold. In Scenario 1 (imagination and creativity), the mentor adopts an open, exploratory stance — modelling curiosity and validating diverse responses to encourage participation from pupils who may feel linguistically or culturally marginal. The mentor introduces and practises key vocabulary through demonstration and visual anchoring before pupils engage independently.
In Scenario 2 (collaboration and problem-solving), the mentor transitions to a facilitation role, structuring small-group work, monitoring group dynamics, and intervening with language prompts (‘How might you explain that differently?’, ‘Can you give an example?’) when communication barriers arise. The mentor actively models inclusive team behaviour, particularly important for pupils whose collaborative learning norms may differ from the host-country classroom culture.
In Scenario 3 (evaluation and digital citizenship around AI and future skills), the mentor acts as a critical thinking guide, provoking reflection through Socratic questioning and ensuring that pupils’ interactions with AI-generated content remain critically mediated. Throughout all three scenarios, the mentor maintains a safe, emotionally supportive environment, checking in individually with pupils who show signs of disengagement or language frustration.
Consistent with the TELMS framework, the mentor acts as a ‘More Knowledgeable Other’ who carefully balances cognitive challenge with emotional support. Scaffolding is intentionally intensified during the introduction of unfamiliar digital tools or CALP-oriented tasks and gradually reduced as pupils gain confidence and independence. Where appropriate, mentors may encourage translanguaging practices, allowing pupils to brainstorm or clarify ideas in their home language before reformulating them in the target language.
Before sessions, the mentor may use an AI text generator (e.g., ChatGPT or a school-approved equivalent) to produce differentiated reading texts on future jobs and creativity, calibrated to different CEFR proficiency levels (A1–B1). The mentor also uses AI image generation tools (e.g., Adobe Firefly or Canva AI) to prepare visual stimulus materials representing ‘jobs of the future’. During sessions, the mentor may use AI-assisted transcription (e.g., Otter.ai) to capture pupils’ spoken ideas during brainstorming phases, allowing for later language review and vocabulary reinforcement.
In Scenario 2, pupils use a generative AI chatbot (mentor-supervised, with pre-set prompts) to explore ideas for a creative invention, practising formulating questions and evaluating AI-generated suggestions critically. In Scenario 3, pupils analyse two AI-generated texts about a ‘future skill’ (one accurate and balanced, one containing errors or biases) to develop fact-checking and critical evaluation competences. Throughout, the mentor ensures that all AI interactions are framed, discussed, and reflected upon — never used as a replacement for pupil thinking or language production.
Throughout the module, AI use is framed critically and transparently. Pupils are encouraged to understand that AI systems generate responses based on patterns in data rather than genuine understanding, and that AI outputs may contain inaccuracies, stereotypes, or biases. Mentors should explain in age-appropriate language how digital systems collect and process information, reinforcing responsible digital citizenship and safe interaction with online technologies.
| Competence Area | Specific Competences |
| Digital Literacy (DigComp 2.2) | Area 1 – Browsing and evaluating digital information; Area 2 – Participating in online collaboration; Area 5 – Identifying creative uses of digital tools; critically assessing AI-generated content. |
| Language (BICS/CALP) | Conversational fluency in discussing opinions and ideas (BICS); academic vocabulary for describing skills, processes, and evaluations; structured written and oral argumentation (CALP). |
| Social / Personal | Creative thinking and imagination; collaborative problem-solving; self-awareness and future-orientation; resilience and openness to diverse perspectives; critical reflection on technology and society. |
| Tool Name | Purpose / Description of Use |
| Padlet | Collaborative digital wall used in all three scenarios for brainstorming, sharing ideas, and displaying creative outputs. Free tier available; accessible on tablets and computers. |
| Canva (free) | Used by pupils in Scenario 1 to design ‘Future Job’ visual cards, and by the mentor to prepare visual stimulus materials. Free education account available. |
| ChatGPT / Gemini (supervised) | Used in Scenario 2 (pupils, with mentor guidance) to generate and evaluate ideas for a creative invention. Also used by mentor for material preparation. |
| Kahoot! / Mentimeter | Used at the opening of Scenario 1 and closing of Scenario 3 for formative check-ins, vocabulary activation, and exit polls. Both offer free basic plans. |
| Google Slides / PowerPoint | Used in Scenario 3 for group presentations on a chosen future skill. Widely available in school settings; offline-compatible version recommended as fallback. |
| Wizer.me | Used for creating differentiated digital worksheets across all three scenarios. Free educator plan supports multimedia-embedded activities. |
Target Age Group
11–14 years (adaptable to 7–10 years with simplified vocabulary and visual-dominant tasks)
Estimated Duration
50–55 minutes
Scenario Summary
Pupils explore the concept of creativity and imagine jobs that may exist in the future. Using visual stimuli, discussion, and a Canva design activity, they create a ‘Future Job Card’ describing an invented profession. This scenario activates prior knowledge, builds thematic vocabulary, and invites pupils to express their identities and aspirations in a low-stakes creative context.
The Scenario relies on Digital Multimodal Composing (DMC), combining visuals, keywords, and oral interaction to support meaning-making.
Linguistic Objectives (BICS/CALP)
To use descriptive and aspirational vocabulary (e.g., ‘In the future, I want to…’, ‘This job involves…’); to produce short written descriptions of an imaginary profession; to develop CALP skills through structured written output.
Digital Objectives
To use Canva to create a simple digital card; to navigate a visual design platform; to evaluate digital images for relevance and accuracy when selecting visuals for their card.
Personal / Social Objectives
To express personal aspirations and creativity; to develop a sense of future agency and self-efficacy; to share ideas respectfully in a group context.
| Tool / Material | Purpose / Notes on Use |
| Kahoot! / Mentimeter | Warm-up vocabulary activation quiz — pupils match images of existing and emerging jobs to their names. |
| Padlet | Whole-class brainstorm board — pupils post sticky notes with words or phrases they associate with ‘creativity’ and ‘the future’. |
| Canva (free education) | Main activity — pupils design a ‘Future Job Card’ including a job title, three skills required, and one sentence about why it matters. |
| Printed sentence frame sheet | Language scaffold — mentor-prepared handout with key sentence frames (‘This job requires…’, ‘The person who does this job must be able to…’). |
Opening Phase (Warm-up) — 10 min
The mentor opens with a Kahoot! quiz showing images of real and imaginary future jobs (e.g., space tour guide, AI ethicist, vertical farm manager). Pupils guess the job name, activating curiosity and vocabulary. The mentor then writes three words on the board — ‘creativity’, ‘skill’, ‘future’ — and invites pupils to share their first associations on Padlet (anonymous posting enabled to lower affective filter). The mentor models one example: ‘When I think of creativity, I think of… music, colour, problem-solving.’
Core Learning Phase — 30–35 min
Activity A — Class Brainstorm (10 min): Mentor leads a structured discussion: ‘What makes someone creative?’ and ‘What kinds of jobs might exist in 20 years?’ Pupil ideas are captured on Padlet. Mentor introduces and practises five key vocabulary items: inventor, innovator, sustainable, artificial intelligence, collaboration — using images, definitions, and example sentences.
Activity B — Future Job Card Design (20–25 min): Pupils open Canva (or use printed template as fallback) and design their own ‘Future Job Card’. The card includes: (1) a job title, (2) three skills this job requires, (3) one sentence explaining why this job matters. Mentor circulates, providing language scaffolding using the sentence frame sheet and prompting pupils with questions (‘What would this person do every day?’, ‘Who would they help?’). Pupils are encouraged to combine images, icons, colour symbolism, keywords, and short oral explanations to communicate meaning multimodally. This DMC-based approach allows learners with emerging language proficiency to participate meaningfully in the creative task without relying exclusively on extended written text.
Pupils who finish early are invited to add a visual or tagline.
Closing Phase & Formative Assessment — 10 min
Pupils share their Future Job Cards in pairs, describing their invention to each other using the sentence frames. Two or three volunteers share with the class via a projected view. Mentor facilitates brief peer responses: ‘One thing I liked about this job…’. Exit question (Mentimeter poll): ‘What is one word that describes your future self?’ Mentor notes vocabulary gaps and engagement patterns for use in planning Scenario 2.
Adaptation Notes
For pupils aged 7–10 or with very limited language proficiency: reduce the written requirement to one sentence and a drawing; offer a word bank rather than full sentence frames; allow use of home language on Padlet with a translation. For pupils with SEN: pre-select a Canva template rather than open design; pair with a more language-confident peer for the sharing activity. If technology is unavailable, provide a printed card template for the design activity.
Reflection Routine
Use the ‘I used to think… Now I think…’ routine at the close: pupils complete the prompt verbally or in writing (‘I used to think creativity was only for artists. Now I think…’). This connects directly to the scenario’s objective of broadening pupils’ self-concept around innovation and skill, and provides a formative snapshot the mentor can return to in Scenario 3.
Pupils can describe an imaginary future job using at least three target vocabulary items and one full sentence. Pupils can navigate Canva to produce a simple digital card. Pupils demonstrate willingness to share creative ideas in a group context and show emerging awareness of the connection between skills, creativity, and future employment.
Tool
Wizer.me
Activity Description
A digital matching worksheet in which pupils connect images of future jobs to short descriptions. After matching, pupils answer two open questions: ‘Which job would you most like to do and why?’ and ‘What skill do you already have that could be useful in the future?’ Pupils submit responses individually; the mentor reviews prior to Scenario 2.
Content
Six images of future job roles (AI doctor, climate engineer, drone traffic controller, etc.) with corresponding text descriptions; two open-response question boxes with word-count guidance (2–3 sentences per answer).
Language Focus
Job-related nouns and verb phrases (to design, to monitor, to collaborate, to solve); present conditional (‘I would like to… because…’); descriptive adjectives (creative, innovative, sustainable).
Tool
Canva (printable template) / Printed handout
Activity Description
A structured ‘Future Job Card’ template for pupils to complete by hand or digitally. Pupils fill in: (1) Job Title, (2) Three required skills, (3) One sentence about the job’s importance, (4) A small illustration or symbol. Completed cards are photographed and uploaded to the class Padlet, creating a shared gallery of future job ideas.
Content
Blank card template with four labelled sections; a word bank of 20 skills-related adjectives and verbs (e.g., empathetic, analytical, to engineer, to communicate); a model example card completed by the mentor.
Language Focus
Descriptive noun phrases (e.g., ‘a person who…’, ‘an expert in…’); modal verbs for ability and necessity (must, should, can); vocabulary for skills and professions.
Tool
Google Forms / Printed handout
Activity Description
A self-assessment worksheet in which pupils reflect on the vocabulary introduced in this scenario. Pupils rate their own confidence with five target words (1 = not sure, 3 = confident), write their own sentence using two of the words, and identify one word they want to practise more. The mentor uses responses to differentiate vocabulary practice in Scenario 2.
Content
A 5-item confidence rating scale; two open-response sentence-writing boxes; one ‘my word to practise’ box with space for a drawing or translation in home language.
Language Focus
Formative self-assessment vocabulary (e.g., ‘I feel confident using…’, ‘I am not sure about…’); target module vocabulary: inventor, innovator, sustainable, artificial intelligence, collaboration.
Target Age Group
11–14 years (adaptable to 7–10 years with simplified challenge brief and role scaffolds
Estimated Duration
55–60 minutes
Scenario Summary
Pupils work in small mixed-proficiency teams to design a creative solution to a real-world local challenge (e.g., reducing loneliness among elderly people, improving recycling in school). They use AI as a brainstorming tool under mentor supervision, evaluate the AI suggestions critically, and then develop and present their own solution. This scenario deepens collaboration skills, extends CALP language production, and introduces structured critical engagement with AI.
The Scenario relies on Digital Multimodal Composing (DMC), combining visuals, keywords, and oral interaction to support meaning-making.
Linguistic Objectives (BICS/CALP)
To use problem-solution language structures (‘The problem is…’, ‘One solution could be…’, ‘We decided to… because…’); to practise oral negotiation and explanation in a small-group context; to produce a short written group summary of their solution (3–5 sentences).
Digital Objectives
To interact responsibly with an AI chatbot under mentor guidance; to evaluate AI-generated suggestions using simple criteria (useful / not useful / needs changing); to use Padlet for collaborative note-taking during group work.
Personal / Social Objectives
To collaborate effectively in a small group, respecting different roles and contributions; to practise active listening and constructive feedback; to develop awareness of how communities can use innovation to solve social problems.
Padlet
Collaborative note-taking during group brainstorm; each group has a dedicated column on a shared class Padlet.
ChatGPT / Gemini (supervised)
Groups pose a structured prompt to the AI chatbot and receive three suggestions, which they evaluate using a simple 3-criteria rubric provided by the mentor.
AI Evaluation Rubric (printed)
Mentor-prepared card with three evaluation questions: Is this idea realistic? Is it kind to people and the environment? Could our group actually do this?
Google Slides / PowerPoint
Groups record their chosen solution on two slides: Slide 1 — the problem; Slide 2 — their solution and why they chose it.
Timer (projected)
Visible countdown timer displayed during group work phases to support time management and smooth transitions.
Opening Phase (Warm-up) — 10 min
The mentor recaps Scenario 1 by displaying three Future Job Cards from the class gallery on Padlet. Brief discussion: ‘All these jobs involve solving problems for other people — what problems do you notice in your community?’ Mentor introduces the session challenge: each group will receive a real local problem and must invent a creative solution. Groups are formed (3–4 pupils, mixed proficiency). Mentor introduces four teamwork vocabulary items: collaborate, evaluate, suggest, decide — with visual definitions and a quick ‘turn and tell’ with a partner.
Core Learning Phase — 30–35 min
Activity A — Challenge Brief & AI Brainstorm (15 min): Each group receives a printed Challenge Card describing a local problem. Groups spend 5 minutes discussing initial ideas on Padlet. Then, mentor demonstrates how to formulate a prompt for the AI chatbot: ‘We are students trying to help [problem]. What are three creative ideas we could try?’ Groups take turns submitting one prompt each to the chatbot (teacher account, projected or shared device). They receive three AI suggestions and use the printed AI Evaluation Rubric to rate each suggestion. The mentor explicitly reinforces that AI suggestions are starting points for human thinking rather than final answers. Groups are encouraged to challenge, adapt, combine, or reject AI-generated ideas where necessary. This supports the development of critical digital literacy and positions pupils as active decision-makers rather than passive technology users.
Activity B — Solution Design (15–20 min): Groups select or adapt their favourite idea (which may be one of the AI suggestions, a modification, or an entirely new idea inspired by the AI output). They record their solution on two Google Slides: Slide 1 describes the problem; Slide 2 presents their solution with at least three reasons why they chose it. Mentor circulates providing language scaffolding: sentence starters, vocabulary cards, and individual prompts to quieter pupils to ensure all voices are represented.
Closing Phase & Formative Assessment — 10 min
Each group gives a one-minute verbal summary of their solution to the class (no full presentation required — a spoken summary from notes). Peers respond with one positive comment (‘I liked…’) and one question (‘I was wondering…’). Mentor records key language errors non-intrusively for later feedback. Exit question: ‘What was one moment in your group where someone had a really good idea? How did that happen?’ Pupils respond on an exit slip or verbally to the mentor.
Adaptation Notes
For younger or lower-proficiency pupils: provide role cards (e.g., ‘Writer’, ‘Speaker’, ‘AI checker’, ‘Timer’) to scaffold group participation; reduce the Google Slides output to a drawn poster with labels; provide a sentence frame for the AI evaluation rubric (‘This idea is useful because…’). If internet access is limited: pre-load three AI-generated suggestions on printed cards so the group can still engage in evaluation without live AI access. Heterogeneous grouping is strongly recommended; ensure no group is entirely composed of very early-stage language learners.
Reflection Routine
Use ‘One thing I contributed, one thing I learned from my team’. This connects to the scenario’s focus on collaborative roles and validates individual contributions within group work, which is especially important for pupils who may habitually defer to more language-confident peers. The mentor can collect and read these slips as an additional formative source.
Pupils may use their home language during brainstorming or peer clarification before reformulating ideas in the target language.
Pupils can explain a problem and a proposed solution using target language structures in both written and spoken form. Pupils demonstrate ability to evaluate AI-generated suggestions using structured criteria. Pupils show evidence of collaborative behaviour — turn-taking, listening, and incorporating others’ ideas — during group work. Groups produce a two-slide digital summary of their innovation.
Tool
Wizer.me
Activity Description
A digital worksheet presenting three brief AI-generated suggestions for a community challenge (pre-loaded by the mentor). Pupils read each suggestion and rate it on three criteria (realistic, kind, achievable) using a sliding scale. They then write one sentence explaining their highest-rated suggestion. This worksheet can be completed individually or as a group on a shared device.
Content
Three short AI-generated text paragraphs (approx. 40 words each); a three-criteria rating slider for each; one open-text response box; a word bank of evaluative adjectives (realistic, impractical, innovative, harmful, achievable, original).
Language Focus
Evaluative adjectives and adverbs; hedging language (‘I think this idea is… because…’, ‘This might not work because…’); comparative structures (‘This idea is better than… because…’).
Tool
Printed handout / Google Docs
Activity Description
A group solution planning sheet divided into four sections: (1) Our problem (one sentence); (2) Three ideas we considered; (3) The idea we chose and why (two to three sentences); (4) One challenge we might face and how we would deal with it. Groups complete this sheet collaboratively during the core activity, then use it as the basis for their Google Slides. It serves as both a planning scaffold and a formative artefact.
Content
Four clearly labelled text boxes with sentence starters printed inside each; a word bank of transition words (first, then, because, however, therefore); a small ‘team roles’ box where each pupil writes their name and role.
Language Focus
Cohesive devices and connectives; causal and justification language (‘We chose this because…’, ‘One challenge is… but we could…’); collaborative discourse markers (‘We agreed that…’, ‘We decided to…’).
Tool
Google Forms / Printed
Activity Description
A peer feedback form used after the group summaries. Each pupil completes one form for one other group. The form includes three sentence-completion items (‘Their idea was creative because…’, ‘One question I have is…’, ‘One improvement could be…’) and one rating item (How clearly did they explain their solution? 1–3 stars). Completed forms are shared with each group by the mentor after the session as written feedback.
Content
Three sentence-completion items with prompt starters; one emoji-based or star rating scale; optional: a ‘best word they used’ field to reinforce vocabulary noticing.
Language Focus
Evaluative and constructive feedback language; comparative structures; politeness conventions in written feedback (‘I really liked how…’, ‘It would be even stronger if…’).
Target Age Group
11–14 years (modifications for 7–10 years provided in Teacher Notes)
Estimated Duration
55–60 minutes
Scenario Summary
Pupils investigate a future skill of their choice (e.g., coding, emotional intelligence, systems thinking, multilingualism) by reading two AI-generated texts about it — one balanced and accurate, one containing errors or biased framing. Working in pairs, they identify differences, verify claims using a trusted website, and create a short presentation slide explaining why their chosen skill matters. This scenario develops critical digital literacy, argumentation, and academic language.
The Scenario relies on Digital Multimodal Composing (DMC), combining visuals, keywords, and oral interaction to support meaning-making.
Linguistic Objectives (BICS/CALP)
To use evaluative and argumentative language (‘This text claims that…’, ‘However, this is not accurate because…’, ‘In my view, this skill is important because…’); to read and compare two short texts for accuracy and bias; to produce a structured spoken and written argument.
Digital Objectives
To identify features of reliable versus unreliable digital content; to use a trusted website to fact-check a specific claim; to critically evaluate AI-generated text using structured criteria; to present findings using a digital tool.
Personal / Social Objectives
To develop media literacy and responsible digital citizenship; to practise evidence-based argumentation; to reflect on one’s own learning journey across the module and articulate personal future aspirations.
Two AI-generated texts (mentor-prepared)
Core reading materials for the critical evaluation task — one accurate, one containing a factual error or biased claim. Levelled for A2–B1 proficiency.
Fact-Check Guide (printed card)
Mentor-prepared mini-guide with three steps: (1) Find the main claim; (2) Search one trusted site (e.g., BBC Bitesize, European Commission for Education); (3) Compare what you found.
Google Slides
Pairs create one summary slide: their chosen skill, two reasons it matters, and one fact they verified. Used for a brief gallery share at the end.
Mentimeter
Opening warm-up word cloud and closing exit poll (‘One skill I already have that the future needs…’).
Padlet (module gallery)
Final upload point for all three sessions’ outputs — Future Job Cards, Solution Slides, and Skill Slides — creating a whole-class ‘Innovators of Tomorrow’ portfolio.
Opening Phase (Warm-up) — 10 min
Mentor opens a Mentimeter word cloud: ‘What skill do you think will be most important in 20 years?’ Pupils submit one word each; results displayed in real time. Mentor leads a brief discussion: ‘Why do you think people disagree about this?’ Introduce the session focus: today we will learn to check whether what we read about the future is actually true — a skill called fact-checking. Introduce five vocabulary items: claim, evidence, reliable, bias, verify — with definitions, examples in context, and a quick pair-practise activity. The mentor may briefly introduce the idea that online platforms and algorithms often prioritise content that attracts attention rather than content that is necessarily accurate or fair. This helps pupils understand why misinformation and biased AI-generated content can spread quickly in digital environments.
Core Learning Phase — 30–35 min
Activity A — Text Comparison (15 min): Each pair receives two short texts (approx. 120 words each) about the same future skill, both labelled as ‘AI-generated’. Text A is accurate; Text B contains one factual error and one subtly biased claim. Pupils read both and complete a simple comparison frame: ‘Both texts say…’, ‘Only Text A says…’, ‘I think Text B might not be accurate because…’. Mentor models one example before independent work.
Activity B — Fact-Checking (10 min): Using the Fact-Check Guide card, each pair selects one claim from Text B and searches one trusted website to verify it. They record their finding in one sentence: ‘We checked [claim]. We found that [evidence]. So [claim] is [accurate / not accurate].’ Mentor circulates, supporting search strategies and reading comprehension. Activity C — Skill Slide Creation (10 min): Pairs choose a future skill (from their own interest, the opening word cloud, or their Scenario 1 Future Job Card) and create one Google Slide: skill name, two reasons it matters, one verified fact about it. Slide is uploaded to the class Padlet module gallery.
Closing Phase & Formative Assessment — 10 min
Gallery walk (physical or digital) — pairs view three other groups’ Skill Slides and leave one written sticky note per slide (‘This skill matters because…’ or ‘A question I have is…’). Mentor facilitates a brief whole-class closing reflection: ‘Looking at our gallery — which skills appear most? What does that tell us about what people value?’ Final Mentimeter exit poll: ‘One skill I already have that the future needs.’ Mentor collects responses and uses them to personalise end-of-module feedback for each pupil.
Adaptation Notes
For pupils aged 7–10 or with limited proficiency: simplify both texts to A1–A2 level; replace the written comparison frame with a yes/no/maybe graphic organiser; replace independent fact-checking with a guided whole-class version using a pre-selected website. For SEN pupils: provide a highlighted version of Text B with the inaccurate sentence underlined, so the task focuses on explaining why it might be wrong rather than finding the error independently. If devices are limited: pairs share one device; alternatively, the mentor leads fact-checking as a class activity using a projected screen. The digital gallery walk can be replaced with a physical display of printed slides.
Reflection Routine
Use ‘My Future Self Letter’: pupils write (or dictate to the mentor) a 2–3 sentence letter to themselves in the future, naming one skill they are already developing and one thing they hope to learn. This synthesises the module’s three thematic threads (creativity, collaboration, critical evaluation) and creates a meaningful personal artefact. Letters can be sealed and ‘posted’ to be re-read at the end of the academic year.
Pupils may use their home language during brainstorming or peer clarification before reformulating ideas in the target language.
Pupils can identify at least one inaccuracy or biased claim in an AI-generated text and support their reasoning with evidence from a trusted source. Pupils produce a structured one-slide argument about the importance of a future skill, using target vocabulary. Pupils demonstrate critical digital literacy by applying a simple fact-checking process. Pupils articulate personal future aspirations in spoken and/or written form, connecting their own identity and skills to the module’s themes.
Tool
Wizer.me
Activity Description
A digital worksheet presenting the two AI-generated texts side by side. Pupils drag and drop selected sentences into two categories: ‘Probably accurate’ and ‘Needs checking’. They then write one sentence explaining their most important categorisation choice. The drag-and-drop format supports low-proficiency engagement while the written response extends higher-proficiency pupils.
Content
Two AI-generated texts (approx. 120 words each); a drag-and-drop sorting area with two category columns; 6–8 pre-selected sentences from the texts for sorting; one open-response box with sentence starter (‘I think this sentence needs checking because…’).
Language Focus
Evaluative language and hedging (‘I think…’, ‘This might not be…’, ‘According to…’); reading for main claims vs. supporting detail; connectives for reasoning (because, however, therefore).
Tool
Printed handout / Google Docs
Activity Description
A structured fact-checking record sheet. Step 1: Write the claim you are checking (copied from Text B). Step 2: Write the name of the website you used. Step 3: Write what you found. Step 4: Write your conclusion (accurate / not accurate / not sure) with one supporting sentence. This sheet provides a transferable fact-checking scaffold that pupils can use beyond the module.
Content
Four sequentially numbered boxes with clear labels and sentence starters inside each; a short list of three recommended trusted websites (pre-approved for the national context); space for a URL to be copied; a ‘conclusion’ box with three radio options and one open line.
Language Focus
Reporting language (‘The website says…’, ‘According to [source]…’); factual present tense; accuracy and uncertainty markers (accurate, incorrect, unclear, according to, however).
Tool
Google Slides / Canva
Activity Description
A single-slide ‘Future Skill Showcase’ template. Pupils fill in: (1) Skill name and a visual; (2) ‘This skill matters because…’ (two bullet points); (3) ‘One verified fact: [fact] — Source: [website]’; (4) ‘I already use this skill when I…’ (one sentence connecting to their own life). The completed slide is uploaded to the Padlet module gallery as part of the end-of-module portfolio.
Content
Pre-designed slide template with four labelled text boxes; an image placeholder with instructions to select a relevant visual from Canva or a royalty-free source; a colour scheme matching the CARE module visual identity.
Language Focus
Argumentative and justification language (‘matters because…’, ‘for example…’); vocabulary for skills and qualities (essential, beneficial, increasingly important); first-person reflection (‘I already use this when…’).
Throughout all three scenarios, the mentor observes four key dimensions: (1) Language use — the range and accuracy of vocabulary pupils produce spontaneously, the structures they attempt, and the moments where communication breaks down; (2) Digital engagement — pupils’ confidence with tools, their problem-solving strategies when technology does not behave as expected, and any signs of digital anxiety or disengagement; (3) Social participation — the balance of contribution in group work, signs of exclusion or over-dominance, and the quality of peer-to-peer support; (4) Critical thinking — particularly in Scenario 3, whether pupils move beyond surface reading to question or challenge information.
Observations are recorded informally using a simple class roster with three columns per scenario: Language, Digital, Social. The mentor uses symbols (tick = strong, circle = developing, dash = needs support) rather than narrative notes during sessions, reserving brief written notes for immediately after each scenario. The Padlet gallery and slide outputs serve as artefactual records of learning that complement these observations.
Special attention should be given to participation equity within multilingual groups. Mentors should observe whether certain pupils consistently dominate collaborative tasks while quieter or less language-confident learners withdraw from interaction. Observation should therefore include not only language accuracy, but also emotional safety, confidence-building, and evidence of increasing willingness to contribute ideas publicly.
Each scenario closes with a structured exit question or self-reflection prompt, designed to be accessible across proficiency levels:
| Scenario | Exit Question / Self-Reflection Prompt |
| Scenario 1 | Mentimeter poll: ‘One word that describes your future self.’ Reflection routine: ‘I used to think… Now I think…’ (written or spoken). |
| Scenario 2 | Exit slip: ‘One thing I contributed. One thing I learned from my team.’ (2 sentences max — oral or written). |
| Scenario 3 | Mentimeter poll: ‘One skill I already have that the future needs.’ Final letter to future self (2–3 sentences). |
The mentor reviews exit slips and poll results before the next session, using them to adjust vocabulary focus, grouping, or scaffolding intensity. Responses are never graded or shared without pupil permission.
Peer assessment is embedded in each scenario in a low-stakes, structured form:
Scenario 1 — Pair sharing of Future Job Cards: pupils practise a structured ‘one thing I liked’ response, guided by mentor modelling. This is primarily a confidence-building exercise rather than evaluative.
Scenario 2 — Group solution summaries: peers ask one question and make one positive observation. The Peer Feedback Form (Worksheet 3, Scenario 2) provides written feedback that groups receive after the session.
Scenario 3 — Gallery walk with sticky notes: pupils leave written responses on three other groups’ Skill Slides on Padlet. The mentor reviews all responses before they are made visible to ensure they are constructive and respectful, removing or privately redirecting any unhelpful comments.
All peer assessment activities are introduced with explicit norms: we say something true, something kind, and something useful. For pupils who find public feedback anxiety-provoking, anonymous Padlet responses are enabled.
After each scenario, the mentor completes the Teacher Reflection Form with particular attention to three questions: (1) Did the AI integration support or distract from the learning objective? Were there moments where pupils became more focused on the technology than on the thinking? (2) Was the language scaffolding sufficient? Which pupils struggled despite the scaffold, and what additional support might be needed? (3) Was the activity design inclusive of the full range of language proficiency and cultural backgrounds present in the group?
These reflections directly inform adjustments to subsequent sessions within the module: for example, if Scenario 1 exit slips reveal that many pupils are unfamiliar with digital design tools, the mentor introduces a 5-minute Canva walkthrough at the beginning of Scenario 2. If Scenario 2 observations reveal unequal participation in group work, the mentor introduces explicit role cards for Scenario 3. This iterative, reflective practice is central to the TELMS approach.
More reflective prompts that could be employed:
The theme of ‘future skills and creativity’ carries different cultural valences across communities. In some contexts, pupils and their families may prioritise vocational stability over creative exploration; the module’s framing should acknowledge this by emphasising that creativity is a skill within any profession, not a luxury or an alternative to ‘serious’ work. Mentors are encouraged to make space for pupils to connect the module’s themes to the professional traditions and skills valued in their own family cultures (e.g., craftsmanship, agricultural knowledge, multilingualism as a skill).
The use of AI tools requires sensitivity. Pupils and families may have varying levels of familiarity, comfort, or concern regarding AI, particularly in communities where data privacy is a significant issue. Mentors should explain briefly — in accessible language — that the AI tools used in this module are supervised, do not collect personal data in classroom use, and are used as thinking tools, not authorities. If parental permission for AI tool use is required in the national context, this should be obtained before the module begins.
Attention should also be given to the gendered dimensions of ‘future skills’ discourse: mentors should actively counter any emerging stereotyping in discussions about who does which jobs, using diverse examples and, if possible, inviting a guest speaker (in person or via recorded video) from an underrepresented background in technology or innovation.
Creativity Across Cultures
Mentors should recognise that expressions of creativity vary across cultural contexts. Some pupils may associate creativity primarily with artistic expression, while others may connect it to practical problem-solving, entrepreneurship, craftsmanship, or family/community responsibilities. The module should therefore validate multiple forms of innovation and intelligence.
Digital Divide
Levels of familiarity with digital platforms and AI technologies may differ considerably between pupils. Mentors should avoid assuming prior digital competence and should provide structured technical onboarding, visual demonstrations, and low-tech alternatives where needed.”
Future Orientation & Emotional Safety
For some migrant pupils, imagining the future may evoke uncertainty or anxiety connected to displacement, interrupted education, or family instability. Mentors should therefore frame future-oriented activities around empowerment, possibility, and resilience rather than pressure or performance.
This module is designed to connect flexibly to national curricula across CARE partner countries. The competences addressed — digital literacy, critical thinking, collaborative communication, and creative problem-solving — are present in most European national curriculum frameworks. Mentors are encouraged to identify the specific curricular anchors in their national context. Relevant cross-curricular connections typically include: ICT/Digital literacy subjects; Citizenship and Social Education; Language Arts (reading non-fiction, constructing arguments); and, in some systems, STEM-integrated modules. The module’s formative-only assessment approach is compatible with most national primary and lower secondary assessment frameworks.
This module is designed to connect flexibly to national curricula across CARE partner countries. The competences addressed — digital literacy, critical thinking, collaborative communication, and creative problem-solving — are present in most European national curriculum frameworks. […]
Spain (national). This module also connects to the Spanish national curriculum (LOMLOE) across several competence areas: the key competence “Competencia digital” (Real Decreto 157/2022) develops critical evaluation of digital and AI-generated content, directly relevant to Scenario 3’s fact-checking activities; the compulsory ESO subject Tecnología y Digitalización (Real Decreto 217/2022) develops computational thinking and creative, sustainable technological problem-solving, corresponding to Scenario 2’s collaborative invention task; Educación en Valores Cívicos y Éticos develops critical and autonomous thinking and responsible citizenship, aligning with the module’s digital citizenship focus; and the key competence Competencia Personal, Social y de Aprender a Aprender (CPSAA) develops resilience, self-awareness, and future-oriented lifelong learning strategies, directly matching the module’s Personal/Social objectives. The area of Lengua Castellana y Literatura additionally supports the oral and written argumentation required in Scenario 3’s evaluative tasks.
Catalonia (regional). This module also connects to the Catalan curriculum (Decret 175/2022): the CD (Digital) key competence requires safe, critical, and creative use of digital tools, including AI; Tecnologia i Digitalització at ESO level develops computational thinking and explicitly requires the responsible, critical, and ethical use of artificial intelligence; Educació en Valors Cívics i Ètics develops critical and autonomous thinking, including explicit reflection on the ethical challenges of AI; and the CPSAA key competence supports resilience, self-regulation, and a personal model of reflection and action, matching the module’s future-skills and creativity focus.
Poland. This module also connects to the Polish national curriculum (podstawa programowa): the informatyka core curriculum develops computational thinking, programming, and the critical evaluation of online sources and information reliability, corresponding to Scenario 3’s fact-checking activities; the core curriculum’s emphasis on teamwork, creativity, and social participation (consistent with the European Key Competences for Lifelong Learning) supports Scenario 2’s collaborative problem-solving task; and the Prawo oświatowe’s provisions on preparation for active participation in social life align with the module’s citizenship and future-orientation themes.
Croatia. This module also connects to the Croatian national curriculum: the Kurikulum nastavnog predmeta Informatika, together with the CARNET experimental curriculum “Umjetna inteligencija: od koncepta do primjene,” develops critical understanding of AI systems and their ethical and social implications, directly relevant to Scenario 3; the cross-curricular theme Građanski odgoj i obrazovanje develops critical thinking and communication skills for responsible social participation; and the cross-curricular theme Učiti kako učiti supports self-regulation, resilience, and the trialling of different learning strategies, matching the module’s future-skills orientation. The Hrvatski jezik curriculum’s “language and communication” strand additionally supports the structured argumentation required in Scenario 3.
The Netherlands. This module also connects to the Dutch curriculum framework: the new statutory kerndoelen digitale geletterdheid include explicit “AI-geletterdheid” (AI literacy), requiring pupils to understand how AI systems work and to engage critically with AI-generated content, directly relevant to Scenario 3’s fact-checking task; the parallel kerndoelen burgerschap (Society and Democracy; Societal Issues domains) frame critical engagement with digital systems and collaborative problem-solving as foundations of responsible citizenship; and self-regulated learning, treated as a foundational cross-curricular skill in Dutch primary pedagogy, supports the module’s emphasis on resilience and future-oriented learning strategies.