Top 10 AI Prompts and Use Cases and in the Education Industry in Luxembourg

Luxembourg is rapidly weaving AI into education: the National Education Training Institute (IFEN) has expanded AI teacher training since 2023 with MOOCs, seminars and tailored school support to demystify generative tools and help teachers apply AI across subjects like ICT, art and language teaching (IFEN ReferNet summary on AI teacher training in Luxembourg).

Higher education and research are matching that momentum - the University of Luxembourg runs interdisciplinary AI courses, MOOCs and projects that connect ethics, multilingual NLP and practical AI skills for students and educators (University of Luxembourg AI education and interdisciplinary courses).

Backed by European initiatives and free resources such as Elements of AI, this ecosystem supports multilingual classrooms (German, French, Luxembourgish) and teacher upskilling; for professionals seeking hands-on prompt and workplace skills, Nucamp's 15-week AI Essentials for Work bootcamp offers a practical pathway into prompt engineering and applied AI for schools and education teams (Nucamp AI Essentials for Work syllabus).

For me, the Europaeum ‘Summer School on AI' at my university in Luxembourg enabled us to learn more about AI technologies in various sectors. Beyond that, the lectures provided insights into the ethnic perspective of AI usage and interesting forecasts for further development of AI systems. Through the exchange with the other participants, we could profit from the multi-disciplinary perspectives that each one of us presented during the Summer School. I would like to thank the organisers for compiling the high-ranked speakers, who presented their research findings and shared their perspectives on AI. The three-day Summer School on AI made clear to me that everyone can work on the further progression of AI systems.

Methodology in Luxembourg's AI-for-education work blends lab-driven research with hands-on teacher and student workshops: IFEN's upskilling programmes are complemented by the University of Luxembourg's AI Robolab, which uses an interdisciplinary, “natural interaction” and societal-impact lens to test tools in real classrooms and community settings (AI Robolab at the University of Luxembourg).

Research projects such as EXPECTATION (personalized explainable AI) and DELIGHT (ethico-legal reasoners) show a preference for explainability and governance alongside technical development, while Scienteens Lab activities (e.g., “Art and Artificial Intelligence”) illustrate a practice-first pedagogy that brings code, creativity and evaluation into the same lesson.

Practitioners also foreground prompt engineering and ethical use in short, interactive workshops - often with demos that let students meet a ChatGPT-powered human-like robot - so that learning is concrete and testable rather than purely theoretical; that practical bias mirrors Luxembourg's national AI strategy, which stresses human-centric, data-aware deployment for public benefit (FNR feature on ChatGPT and education, Luxembourg's AI strategic vision).

"Chat GPT is revolutionary in the way that it allows users to summarize, converse, ask questions, and generate new content." - Dr Sana Nouzri, Post-doctoral researcher at the AI RoboLab

Turn IFEN's classroom support into a practical, reusable prompt: ask an assistant to

Create a 45–60 minute lesson plan for a multilingual Luxembourg lower‑secondary class (Luxembourgish/French/German) that lists clear content and language objectives, pre‑teaches 6 key vocabulary items with ELL‑friendly definitions, builds background knowledge, and includes three scaffolded pathways (newcomer, developing, fluent) with visuals, graphic organizers and sentence frames.

Grounded steps from Colorín Colorado - identify standards and separate content vs.

language objectives, pre‑teach vocabulary and use cognates - ensure peer strategies like Think‑Pair‑Share and cooperative group tasks so language practice happens while learning content (Colorín Colorado lesson planning strategies for English language learners).

Add differentiation checklists and rubrics adapted from HMH's differentiated‑instruction guidance to make assessment formative and actionable (HMH differentiated instruction lesson planning guide).

Finally, package the prompt for teacher CPD so schools can pair this with practical AI literacy workshops and reskilling pathways aimed at classroom prompts and oversight (AI literacy workshops for Luxembourg schools), turning one‑page prompts into repeatable, classroom‑ready lessons - imagine a poster of cognates on the wall that students point to as they explain a science concept, bridging language and content in one simple gesture.

Turn IFEN's “generate formative assessments with rubrics” prompt into a practical classroom shortcut: ask an assistant to produce 3–5 low‑stakes formative tasks that each map to clear learning objectives, then draft an accompanying analytic or single‑point rubric (teacher chooses type) that lists 4–6 student‑friendly criteria, distinct performance levels and brief descriptors so feedback is actionable and time‑saving for multilingual Luxembourg classrooms.

Ground the prompt in assessment design best practice - define outcomes first, align each task to those outcomes, pilot the rubric on sample work and refine before sharing with students - and package the result for Moodle or paper distribution so rubrics double as learning roadmaps and peer‑review guides.

For teachers pressed for time, a one‑page rubric drafted this way can shrink marking load while making revision cycles visible to students; more teachers report clearer feedback and fewer grade disputes when rubrics are explicit.

For templates and stepwise guidance, see rubric best practices and assessment design guides linked below.

A rubric is an evaluation tool that outlines the criteria for an assignment or learning outcome.

For a classroom-ready prompt inspired by AI RoboLab practice and Dr. Sana Nouzri's outreach style, ask an assistant to build a two‑lesson, hands‑on explainer of neural networks that combines a role‑play game, visual simulations and scaffolded activities for multilingual Luxembourg classrooms: base the plan on the DAILy “Neural Network” lesson (two 45‑minute lessons) with clear learning objectives (label training steps, locate where “learning” happens, and explain purpose‑specific training data), pre‑teach key vocabulary (neuron, input/hidden/output layer, feedforward, backpropagation), and include an exit ticket and printable materials such as the lesson's 34 colored notecards so students can physically act out weights and signals; pair that with the Google ML Crash Course interactive widgets for short computer exercises to show parameter and hyperparameter effects, and offer NetLogo simulation options for older students who can run perceptron/multi‑layer experiments.

Package the prompt for teacher CPD and link the final materials to local AI literacy workshops so schools can pilot, assess and iterate easily (Everyday AI neural networks lesson plan, Google ML Crash Course interactive neural network exercises, AI literacy workshops for Luxembourg - coding bootcamp guide (2025)).

A practical CPD module that IFEN and AI4Teachers could adopt focuses on prompt engineering as a teacher workflow - short, hands‑on sessions that show educators how to use prompts to simplify lesson planning, improve differentiation, generate assessments and draft policies while foregrounding ethics and human oversight; model elements can be drawn from CPD College's approachable 20‑hour online “AI for teachers” syllabus, TeachAI's AI Guidance for Schools Toolkit for policy and readiness framing, and EdTechTeacher's hands‑on workshop formats that leave participants with ready‑to‑use prompt libraries and leadership playbooks for school rollout.

Keep the design modular (one- to two‑hour micro‑modules for different staff roles), pair practice with reflective coaching and peer review, and finish with a printable, poster‑size prompt cheat‑sheet or a five‑card prompt deck teachers can shuffle during planning - simple, repeatable artefacts that make the “so what?” immediate: less editing time, clearer differentiation pathways and a shared language for AI use across multilingual Luxembourg classrooms.

“Now is the time to embark on this transformative path, where technology becomes an invaluable ally in the pursuit of empowering our students and creating enriching educational experiences, a roadmap to reclaiming time, enhancing learning outcomes, and embracing the future of education”.

For a CHATWISE / University of Luxembourg prompt that really fits Luxembourg's classrooms and schools, ask the assistant to generate multilingual content (Luxembourgish, French, German, plus English) that flags idioms, offers culturally aware alternatives and provides certified‑ready phrasing for high‑stakes domains such as finance, legal and tech - sectors PoliLingua highlights as especially sensitive to mistranslation - because Luxembourgish, spoken by roughly 400,000 people and only standardised relatively recently, contains idiomatic and syntactic traps that machine outputs can mishandle (PoliLingua Luxembourgish–English translation guide, Overview of Luxembourg's multilingual translation needs).

Build the prompt to produce a) a clear source text, b) three parallel translations (literal, idiomatic, and certified/legal wording), c) a short glossary of tricky terms and cognates, and d) a QA checklist for human reviewers so language teams can apply the quality‑assurance practices Nucamp recommends when shifting staff from manual tasks into higher‑value roles - remember: one mistranslated idiom in a financial notice can turn a routine bulletin into a puzzling headline, so the so what here is concrete: robust prompts protect clarity, compliance and trust across Luxembourg's multilingual public sphere (Quality assurance for translations in multilingual education).

Designing a student‑facing CHATWISE assistant for Luxembourg classrooms begins with a tight, role‑based script: tell the bot its persona (for example, a patient multilingual “MathMentor” that answers in Luxembourgish/French/German/English), set tone and output format, and specify curriculum files or glossaries to anchor answers so outputs stay curriculum‑aligned; platforms like OpenAssistantGPT make this practical - upload .docx/.pdf materials, choose GPT‑4, and you can have an embeddable homework helper running in as little as 10–15 minutes with a floating widget students tap after school (OpenAssistantGPT tutorial: build an AI homework helper for students).

Pedagogy matters: script the assistant to provide step‑by‑step explanations, short quizzes and flashcards, and clear “what I did/what you should try next” prompts so students learn, not copy; SchoolHub.ai's classroom examples show how bots can role‑play historical figures, act as language partners, or generate differentiated practice for mixed‑ability groups (SchoolHub.ai examples: create AI chatbots for education).

Safeguards are essential - embed privacy rules, encourage students to keep chatlogs, and use supervision protocols inspired by AI‑assisted revision workflows so AI supports student ownership rather than replacing it.

Turn the AI RoboLab Smart Photo Booth idea into a crisp project brief for an Art + AI workshop in Luxembourg: start with learning goals (creative prompt‑writing, ethical use and consent, basic image pipelines) and a short schedule that pairs a live capture session with hands‑on generative editing and critique; core activities can include AI background replacement, stylization, hybrid generative portraits and “trading‑card” keepsakes so each student leaves with a shareable artwork - an unforgettable, teachable moment when a classmate's selfie becomes a tailor‑made cyberpunk portrait or watercolor collage.

Use proven toolchains and pedagogy - capture raw images, prompt and iterate with Midjourney/DALL‑E/Firefly, refine in Photoshop Beta and consider upscaling/retouch workflows described in professional trainings - to teach both craft and the legal/ethical checkpoints photographers now cover in AI workshops.

Frame assessment as a short reflective sketchbook entry plus a rubric for creativity, prompt craft and attribution, and build CPD time for teachers to run the booth and manage privacy.

For inspiration on audience-facing activations see the slick, interactive experience write‑up on AI photo booths and for local upskilling tie-ins reference reskilling and prompt‑engineering guides for Luxembourg schools to turn one event into sustained teacher capability-building (AI photo booth activations interactive experience write-up, Reskilling and AI in Luxembourg education guide).

Medienkompass can become the practical bridge between Luxembourg classrooms and the EU's DigComp 2.2 by converting curriculum units into mapped learning outcomes, assessment items and quick teacher checklists that speak the same digital language as Brussels: ask an assistant to list each lesson's knowledge–skills–attitudes, tag it to one of DigComp's five areas and 21 competences, recommend one of the eight proficiency levels, and generate 2–3 formative tasks plus scoring criteria that foreground AI literacy and multilingual accessibility.

DigComp 2.2 already supplies 250+ concrete examples for curriculum designers and examples for AI‑aware competence, so a Medienkompass prompt that produces side‑by‑side translations (Luxembourgish/French/German), a reviewer QA checklist and a printable “unit → competence → task” poster makes classroom adoption low‑friction and audit‑ready (EU DigComp 2.2 framework overview (Digital Competence Framework for Citizens)).

Plan for continuity: the JRC has signalled a DigComp 3.0 release in late 2025 that will remain backwards compatible, so include metadata in mappings (DigComp 2.2 code + suggested 3.0 adjustments) to future‑proof school materials and CPD rolls (JRC update on DigComp 3.0 developments (2024–2025)).

The “so what”: a one‑page Medienkompass mapping can turn an abstract digital skill into a classroom routine teachers use every week, not just another policy document.

For Luxembourg schools a practical “Excellium Services” draft policy should read like a tight playbook: define exactly which student data an AI tool may collect and why, insist on data minimisation plus encryption and role‑based access, require vendor Data Processing Agreements that forbid resale or model‑training on school data, and bake in retention‑and‑deletion schedules and parental consent workflows so families in Luxembourg's multilingual communities know what's happening and why; ground every requirement in GDPR basics - lawful basis, purpose limitation, explainability - and include DPIA triggers and audit timelines to keep governance testable (AI and the GDPR: foundations of compliance for schools).

Use the SchoolAI checklist - who accesses PII, how it's stored, breach timelines - to vet vendors, and consider automated DPIA tools to turn slow assessments into auditable, education‑ready workflows for districts and multi‑school pilots (SchoolAI: key privacy questions before implementing AI in schools, Automated DPIA tools for education compliance).

The “so what” is concrete: a teacher pasting a student essay into a consumer chatbot can become an international compliance incident overnight, so approved‑tool lists, staff training, human‑in‑the‑loop rules and clear escalation paths are non‑negotiable for safe AI use in Luxembourg classrooms.

“Finally, an AI tool that works with our compliance framework rather than against it. Staff confidence has transformed because they know every interaction is safe.”

Turn prompt engineering from a theory into a fast, repeatable skill for Luxembourg classrooms by adapting the 20‑minute, small‑group “Prompt Engineering Challenge” into staff CPD and student labs: use the IdeeasLab activity cards and worksheet template so mixed‑discipline teams iterate basic→advanced prompts, record exact queries and compare results, then link those exercises to classroom scenarios (language translation, math problem sets, lab write‑ups) to make the practice immediately useful (Prompt Engineering Challenge teaching resource (IdeeasLab)).

Pair that hands‑on set with a concise security workbook that teaches model limits and real risks - AIXEducation flags how even simple prompting patterns can reveal training‑data leakage - so prompts are practised alongside privacy checklists and human‑in‑the‑loop rules rather than in isolation (Prompt Engineering for Education security guide (AIXEducation)).

For Luxembourg schools, fold this into local upskilling and reskilling pathways so one short activity becomes part of a curriculum‑ready prompt library and policy‑aware habit: imagine teachers leaving a 45‑minute CPD session with three discipline‑specific challenge cards, a completed worksheet and a one‑page safety checklist they can pin in the staffroom (Reskilling programs in Luxembourg for education and schools).

Luxembourg's next steps are pragmatic and coordinated: scale IFEN's teacher CPD and multilingual classroom supports while piloting proven tools so schools see immediate gains (for example, the University of Luxembourg's MoU with AWS shows how generative AI can free teachers from repetitive tasks and create personalised materials University of Luxembourg–AWS memorandum on generative AI pilot); adopt AI‑enhanced, quality‑assured assessment pipelines like the LIST–OAT partnership to speed item authoring without sacrificing accessibility or trust (LIST and OAT AI‑powered assessments partnership); and pair every rollout with clear GDPR‑aligned governance and CNPD‑style AI literacy so human oversight remains central.

Practical reskilling matters: short, applied programmes that teach prompt‑craft, curricular alignment and classroom workflows - such as a 15‑week pathway for workplace AI skills - can move staff from manual tasks into higher‑value roles while keeping classrooms multilingual and student‑centred (Nucamp AI Essentials for Work 15‑week bootcamp).

Together these actions - CPD, tested pilots, assessment quality assurance and targeted reskilling - turn policy momentum into everyday practice that saves teachers time and deepens learning across Luxembourg's multilingual system.

“This collaboration focused on innovative technologies benefits students and researchers, and ultimately society. It is a perfect example of the positive impact that public and private partnerships can bring” - Marie-Hélène Jobin, Vice Rector for Partnerships and International Relations, University of Luxembourg