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

Dutch classrooms are at a tipping point: from Maastricht University's month-long AI programme with hands-on prompting workshops and AI tutors to national coordination by SURF, schools and universities are racing to turn promise into practice while avoiding harm - especially after a recent Dutch study warned that biased algorithms can reproduce educational inequality.

This guide matters because educators need concrete prompts and classroom use cases that boost learning, protect students and align with emerging rules and pedagogy; practical upskilling is already available, from university e‑modules to career-focused training like Nucamp's Nucamp AI Essentials for Work bootcamp syllabus.

Use this list to find tested prompts, assessment safeguards and realistic classroom workflows that match SURF's calls for responsible deployment and the reports urging evidence‑based oversight, so AI helps every student instead of leaving some behind - a small, well‑crafted prompt can save hours of planning and keep academic integrity intact.

For national context and policy conversations see SURF AI in education - Netherlands and the Dutch study on algorithmic bias in schools - NL Times.

Bootcamp	Length	Early bird cost	Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp syllabus - Nucamp

Skills, knowledge and understanding that allow providers, deployers, and affected persons, taking into account their respective rights and obligations in the context of this Regulation, to make an informed deployment of AI systems, as well as to gain awareness about the opportunities and risks of AI and possible harm it can cause.

Methodology blended Dutch policy and classroom evidence with ethical frameworks: selection began by mapping institutional guidance and practical toolkits from Dutch universities (identifying vulnerability of end‑terms and the need to redesign assessments rather than rely on brittle detectors), then prioritised prompts and use cases that appear in real classroom pilots and design examples - for instance essays paired with a reflection appendix and prompt log to make the process assessable - and finally layered in an ethics-first filter using EU‑aligned schemas; sources such as Utrecht University's deep dive on generative AI and assessment helped flag which learning outcomes are at risk and which need process redesign, while the AI Pioneers ethics evaluation schema supplied concrete pillars (diversity, transparency, privacy, sustainability, AI literacy) to judge each candidate prompt or workflow for fairness and long‑term viability.

The result: Top 10 entries only include prompts tested against Dutch assessment advice, classroom design examples, or an explicit ethical check so schools can adopt them with clarity and fewer surprises.

“We must embrace AI technology carefully and strengthen the human factor in education to adapt and deal with the technology responsibly and ethically.”

ChatGPT and Grammarly form a practical, classroom-ready pairing for Dutch educators seeking clearer student writing and faster feedback: ChatGPT can act as “a tireless teaching assistant” that generates drafts, simplifies complex texts for multilingual learners, and even produces transcripts or translated versions of lessons, while Grammarly supplies real‑time grammar, tone and spelling checks plus plagiarism flags that smooth final drafts and emails to parents and colleagues (see the ACE classroom primer on AI tools for teachers for examples).

Used together they free teachers from routine copy‑editing so instruction can focus on argument, evidence and voice, but caution is needed - research and classroom reports warn that overreliance can flatten stylistic nuance and short‑circuit learning, so pair AI checks with explicit grammar instruction, transparent syllabus rules and scaffolded process tasks so students learn to accept, evaluate and eventually outgrow the tool.

For step‑by‑step grammar practice, Khan Academy's guide to AI tutors is a helpful how‑to, and critiques of Grammarly's classroom impact offer a useful counterbalance for policy and pedagogy decisions.

Tool	Classroom use
ACE guide to AI tools for teachers (ChatGPT examples)	Brainstorming, drafting support, simplifying texts for EAL students, transcripts and basic translation
SchoolAI review: Best AI writing tools for personalized learning (Grammarly)	Real‑time grammar/tone suggestions, plagiarism checks and final polishing across platforms

“None of these [AI] devices are independent of insidiousness. If they are not used carefully, they can be as harmful as helpful.”

For Dutch classrooms that run interviews, parent‑teacher meetings or qualitative research, transcription is now a practical time‑saver - but language support matters: Otter.ai interview transcription features for educators bring useful features (real‑time transcripts, AI summaries, Otter Chat) and a generous free tier (300 minutes/month) with a Pro option at 1,200 minutes, yet it currently transcribes only English (US/UK), Spanish and French, which leaves Dutch‑language workflows constrained unless schools reconfigure settings or post‑process translations; see Otter's feature page for educators and its supported‑languages notes for details.

Schools and researchers in the Netherlands that need native Dutch transcription or broader multilingual pipelines should evaluate alternatives that advertise wider language coverage and tighter research features (speaker tagging, timestamps, export formats) or tools that integrate directly with analysis platforms used in qualitative research; Looppanel, for example, lists Dutch among its supported languages and highlights researcher‑friendly exports and time‑stamps.

Pairing a transcription service with a translation step or a tool that exports clean, intelligent‑verbatim transcripts makes thematic coding and student‑voice analysis far faster - turning hours of audio into searchable evidence for curriculum design, a small operational change that can free weeks of staff time across a school year.

ChatGPT and Perplexity can speed Dutch school leaders, curriculum teams and researchers from weeks of reading into crisp executive summaries - think a 30‑page report distilled into a seven‑minute audio or a one‑page brief that decision‑makers actually read - but speed brings tradeoffs: experiments show AI summarization often boosts output and clarity while still producing accuracy and nuance errors that vary by discipline, so human oversight is essential (see the rapid‑summary experiment and scores from a recent AI paper‑writer test).

Practical safeguards for Netherlands classrooms include publishing a short verification checklist alongside any AI‑generated summary and using a tiered workflow where AI does first‑pass screening and staff validate high‑impact claims; experts also stress prompts that elicit uncertainty and explicit limitations to counter overconfident phrasing.

For concrete guidance, Dutch educators should consult verification checklists for AI summaries and the technical best practices that explain when abstractive summaries are most reliable and when to demand full‑text checks.

Evaluation Dimension	Average Score (1–5)
Factual Accuracy	3.7
Comprehensiveness	4.2
Clarity	4.5
Utility for Research	3.9

“This practice serves two purposes: it encourages authors to critically review AI output before dissemination, and it provides audiences with ...” - George Veletsianos, on verification checklists for AI‑generated summaries (verification checklist for AI-generated research summaries by George Veletsianos).

QuillBot and ChatGPT make paraphrasing a classroom-ready shortcut - rewriting dense paragraphs into clearer, more student‑friendly language in seconds - but Dutch educators should treat those rewrites as drafting aids, not final submissions: solid paraphrase practice (read, look away, rewrite, check) still matters for comprehension and integrity, and every AI‑rephrased passage must be traced back to its source and cited.

Use automated rephrasing to help multilingual learners find natural Dutch or English phrasing, then run a short pedagogy loop - student rewrite + teacher check + source citation - to prevent mosaic plagiarism and keep assessment valid; practical how‑to steps from the Purdue OWL Paraphrasing Guide and the Scribbr How to Paraphrase Guide are ideal templates for classroom exercises (Purdue OWL Paraphrasing Guide, Scribbr How to Paraphrase Guide).

For Dutch schools piloting AI workflows, embed these checks into local policy and curriculum plans so paraphrasing tools boost clarity without sacrificing academic standards (see the Nucamp AI Essentials for Work syllabus for related AI-in-workplace guidance: Nucamp AI Essentials for Work syllabus); think of the process as teaching students to edit a machine's first draft into something unmistakably their own - like polishing a rough pebble into a ring that still bears the maker's mark.

"[D]on't read your source as you paraphrase it. Read the passage, look away, think about it for a moment; then, still looking away, paraphrase it in your own words." - Kate Turabian

ChatGPT is a practical engine for Dutch educators designing research, segmenting learners and sparking idea generation: use it to draft research questions, generate segmented learner personas from enrollment data, and brainstorm project-based prompts that map to NL learning outcomes - tasks it handles well according to practical tool rundowns that highlight ChatGPT's strengths in brainstorming, translation and data analysis (ChatGPT use cases overview - brainstorming, translation, and data analysis).

In Netherlands schools this can mean turning a term‑long literature scan into a tight research design, creating teacher‑ready interview scripts for qualitative studies, or producing differentiated lesson seeds for mixed‑ability classrooms; however, effective deployment requires the same data literacy and local collaboration EY and industry reports flag as essential for trustworthy personalization, and Dutch pilots should mirror proven local integrations (for funding and partnership pathways see resources like the Netherlands AI Coalition guide to using AI in education (2025)).

Treat ChatGPT as a rapid first‑draft partner: validate segments against school records, document prompt logs for assessment integrity, and human‑check high‑stakes inferences so AI accelerates planning without outsourcing judgment.

"Artificial intelligence (AI) is rapidly advancing from more than just an opportunity for destination organizations but also a strategic and vital business tool."

ChatGPT paired with AI image and slogan generators turns brand discovery into an iterative classroom-friendly sprint: generate dozens of short, tested taglines and AI‑made logo concepts in seconds, then refine the best candidates to match Dutch values, accessibility and school inspection expectations; platforms that build full branding kits from slogan to colour palette speed this process (see practical branding flows on Produkto school and education slogan ideas and Copy.ai's fast slogan generator for multiple variants and workflows Copy.ai free slogan generator for slogan variants).

Evidence advises caution: University of Minnesota experiments found most AI taglines underperformed experts, yet the top AI options - produced with detailed prompts and a “test for best” workflow - sometimes matched real campaigns, so Dutch schools should A/B test options with stakeholders, check originality and local cultural fit, and treat AI output as first drafts to be human‑edited into something that sings at open days and on municipal websites.

“Nearly every business person I speak with is struggling to figure out how and when they can benefit from AI tools.”

ChatGPT can accelerate analytical insight extraction from Dutch classroom interviews and focus groups by turning raw transcripts into provisional codes and concise summaries, but best practice in the Netherlands stitches it into a secure, replicable workflow: feed transcripts from a research-grade platform (for example Looppanel's AI thematic analysis toolkit that promises “discover insights 10x faster”) into ChatGPT for rapid theme spotting, then validate and formalise codes in QDA software like NVivo or HeyMarvin that offer AI‑assisted coding, exportable quotes and GDPR‑aware pipelines; this hybrid approach frees teams from the drudgery of line‑by‑line coding yet keeps human researchers in the loop to check for bias, hallucinations and context loss.

Practical steps for Dutch schools and researchers: use a transcription + repository (auto‑clip and tag with Looppanel or HeyMarvin), run an initial ChatGPT pass to surface candidate themes, then reconcile those candidates in NVivo's AI Assistant and documented codebooks so findings are auditable for assessments, ethics reviews or municipal stakeholders - imagine turning a semester's worth of parent interviews into a searchable mosaic of verified quotes overnight.

For funding and partnership pathways, link analytic pilots to NL AI Coalition programmes and local data‑governance plans.

Tool	Strength / Feature	Notes
Looppanel AI thematic analysis toolkit	Auto‑transcription, AI‑assisted tagging, video quote extraction	Free 2‑week trial; multi‑language support; affordable plans from $30/month
HeyMarvin AI thematic analysis resources	AI theme detection, sentiment, GDPR/SOC2 compliance	Transcribes 40+ languages; plans for teams and enterprise
NVivo AI Assistant (Lumivero) qualitative data analysis	Structured QDA, AI Assistant, visualization and export	Academic pricing available; AI supports early‑stage coding and review
ChatGPT	Flexible summarization and candidate code generation	Fast first‑pass insights but needs human validation; paid tiers for higher limits

“It will make your team 1000x more efficient – and I'm not exaggerating.”

Section drafting and structured writing support is where ChatGPT shines as a drafting workhorse for Dutch educators and researchers - especially when paired with research-focused tools that keep claims verifiable and citations intact.

Start a section with a tight bullet scaffold (a trick that improves AI output dramatically), then ask ChatGPT to expand each bullet into a paragraph, or pull in a tool like Jenni for outline building, PDF fetch and built‑in citation styles so drafts arrive with source context (Jenni outline builder and PDF fetch for source-based drafting).

For submission‑ready polishing and automatic preflight checks, Paperpal's grammar, citation and submission checks can catch formatting issues before review (Paperpal submission checks and citation manager).

SciSpace's research writer can help surface relevant papers and suggest citationable phrasing for literature sections. In Netherlands classrooms and department teams this hybrid workflow - scaffold + ChatGPT drafting + a citation‑aware assistant - speeds section drafting while preserving academic standards; the vivid payoff is turning a week's worth of scattered notes and PDFs into a readable, referee‑ready section in an afternoon, provided every AI‑suggested claim is human‑verified.

Tool	Feature	Classroom / Research Note
Jenni	Outline builder, PDF fetch, 2,600 citation styles	Good for source-based drafting and export
Paperpal	Submission checks, citation finder, plagiarism checks	Useful pre-submission polishing and formatting
ChatGPT	Flexible section drafting, polishing from bullets	Fast first-pass drafts; human verification required

“using materials generated using artificial intelligence that are turned in without attribution is considered plagiarism.”

Dutch classrooms can turn AI transparency into a learning moment by pairing structured reflection tasks with short AI‑use disclosure statements: ask students to answer the “what? - so what? - now what?” reflection prompts (description, analysis, future use) used in many reflective frameworks, then append a one‑paragraph disclosure that names the tool, the purpose of the AI pass, and what the student changed or learned during revision; this combo supports academic integrity, scaffolds metacognition and makes assessment decisions auditable for teachers and panels.

Build rubrics and exemplars from the reflection guidance at BCcampus Pressbooks and the practical assessment steps in the Gwenna Moss Centre's overview so expectations are explicit, fair to multilingual students, and scalable with tools like Perusall for large cohorts.

For school leaders seeking policy templates or partnership paths in the Netherlands, link classroom practice to national programmes such as the NL AI Coalition to align local disclosure rules with broader funding and governance conversations.

Treated as formative practice rather than a policing exercise, reflection + disclosure turns AI use from a risk into a teachable skill - students learn to interrogate the machine's output and to own the learning that follows.

Reflection is a process that allows the student to consider their learning, break it down into key elements and examine their experience with these elements.

Institutional policy drafting and AI‑resilient assessment design in the Netherlands is moving from ad hoc rules to pragmatic, auditable practices that universities can adopt now: Utrecht University AI policy - model statements and teacher guidance already supplies model AI disclosure statements, conditions of use and teacher‑focused assessment frameworks to anchor local rules, while national oversight bodies warn that adaptive systems and learning analytics carry privacy and fairness risks that must be folded into IT strategy and staff training - advice that schools should take seriously when redesigning summative work: see the Dutch Data Protection Authority guidance on algorithmic and AI risks in education.

Concrete design moves used across Dutch pilots include explicit AI‑use declarations, reworked assessment types (oral defences, in‑class performance tasks and AI‑resistant prompts), and living policy documents that link to training modules so rules evolve with tools - an approach echoed in recent university frameworks that treat GenAI guidance as a living resource.

The practical payoff is simple: clear disclosure templates, documented prompt logs and redesigned assessments protect integrity while keeping innovation on the table, turning an abstract compliance problem into a set of classroom practices that teachers can actually implement.

“We're strict about the AI rate, allowing no more than 40% of AI-generated text in all assignments. Anything higher than 40% will be regarded as misconduct.”

Dutch educators closing this guide should treat the next steps as practical and policy-tight: prioritise AI literacy, clear disclosure and assessment redesign so generative tools help learning without hollowing it out.

Start with a short, public AI policy and model disclosure (see Utrecht University's responsible AI resources) and fold in classroom-level checks - prompt logs, verification checklists and AI‑resistant tasks like oral defences or project artefacts - so integrity and pedagogy travel together; for ethical risk framing and equity concerns consult national summaries and Maastricht University's guidance on GenAI risks and precautions.

Pilot staff training and student modules, link pilots to NL governance channels (the Netherlands' UNESCO-aligned reporting shows this is feasible), and move from one-off bans to teachable workflows - where a one‑line AI‑use statement transforms opaque drafts into auditable learning evidence.

For practical upskilling, consider targeted courses such as Nucamp's AI Essentials for Work syllabus that teach prompting, prompt logs and workplace‑grade verification.

The best checklist is simple: declare the tool, state the purpose, log prompts, human‑verify high‑stakes claims and update policy as tools evolve.

Program	Length	Early bird	Syllabus
AI Essentials for Work	15 Weeks	$3,582	Nucamp AI Essentials for Work syllabus

“We're strict about the AI rate, allowing no more than 40% of AI-generated text in all assignments. Anything higher than 40% will be regarded as misconduct.”