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

Finland is turning AI from a tech headline into classroom practice: the Finnish National Agency's 2025 guidance helps schools adopt AI responsibly and the clear, teacher-facing Finnish National Agency AI education legislation and recommendations are paired with practical support like the downloadable AI Guide for Teachers (downloadable), which explains capabilities, limits and AI pedagogy.

Early childhood to vocational training are covered - children as young as three begin exploring the digital world - so ethics, GDPR-aligned data protection and AI literacy are front and center.

For Finnish educators and school leaders needing hands-on skills, short practical programs such as Nucamp AI Essentials for Work 15-week bootcamp syllabus teach usable prompts, tool workflows and classroom-ready applications that map directly to national recommendations and pilot evidence showing substantial learning gains.

Metric	Change	Source
Academic performance	+25%	Eduten pilots
Student engagement	+30%	Gamified tools
Teacher workload reduction	−40%	Helsinki schools

“The surface technology [of AI] which is developing at high speed, doesn't take away the need for basic critical understanding of how media works.” - Leo Pekkala, KAVI

The top 10 were chosen by triangulating three practical filters that matter in Finland: alignment with national AI guidance (transparency, accountability and inclusivity), measurable classroom impact, and strong pedagogical grounding and data‑protection safeguards.

Tools had to demonstrate or be backed by Finnish pilots or research - examples include adaptive platforms tied to reported gains (a 25% lift in academic performance and a 30% surge in engagement) and programs that reach teachers with hands‑on auditing and training - while also fitting the AuroraAI/Guidelines framework for explainable algorithms and mandatory DPIAs; see the detailed national analysis at AI in Finland education analysis - The AI Track and the classroom research showing children co‑designing image‑classifier apps and learning to spot algorithmic bias at the AI education research - University of Eastern Finland.

Preference went to solutions used in Finnish schools or vetted by Finnish projects (Eduten pilots, Edudata.io audits), those that scale with teacher support, and those that include practical safeguards (parental consent, anonymization and regular audits).

The result is a shortlist of tools and prompts that are not tech for tech's sake but demonstrably classroom‑ready, ethically aligned, and backed by local evidence - think of a fourth‑grader who builds an image classifier in a single workshop and suddenly understands algorithmic bias: that concrete moment was weighted heavily in selection.

Selection Criterion	What was checked	Source
Ethical alignment	Transparency, accountability, inclusivity	AI in Finland education analysis - The AI Track
Measured impact	Academic gains & engagement (+25% / +30%)	AI in Finland education analysis - The AI Track
Pedagogical evidence	Hands‑on workshops, student co‑design of AI apps	AI education research - University of Eastern Finland

“AI in Finland must enhance - not replace - critical thinking.” - University of Oulu policy (cited in The AI Track)

Eduten brings Finnish math pedagogy into the classroom with AI-driven, personalized learning paths that adapt exercise difficulty and sequencing to each child's mastery, freeing teachers from hours of marking while giving them the “learning analytics” that spotlight who needs intervention and why; the platform - endorsed by the Finnish National Agency as a digital solution for math - blends gamification (students collect trophies and get safe chances to correct mistakes) with rigorous research showing up to 45% improvement in learning results after 15 years of study, a massive content library of over 200,000 tasks, and deep teacher support so lessons fit any curriculum.

Used widely in Finland and proven in university pilots, Eduten scales from individual differentiation to whole‑class dashboards, reducing teacher workload and math anxiety while delivering classroom‑ready personalization that aligns with national guidelines.

Explore the platform at Eduten official website - personalized math learning platform and see the Finnish National Agency's listing of Eduten as a recommended digital solution for maths.

Metric	Value	Source
Learning improvement	Up to 45%	Eduten official website - math learning research and results
Penetration in Finnish schools	Used in 56% of schools	NewsVoir press release: Eduten adoption in Finnish schools
Content library	>200,000 tasks	Business Standard press release: Eduten content library details

Carnegie Learning's MATHia reads like a patient second teacher for grades 6–12: its AI studies not just final answers but the exact steps a student takes, using a 25‑year research base to tailor just‑in‑time hints, Skillometer progress indicators, and teacher dashboards that surface who's in “productive struggle” versus “unproductive struggle.” For Finnish schools aiming for transparent, pedagogically sound AI, MATHia's LiveLab alerts and the APLSE predictive report turn raw interaction data into clear next steps - helping teachers prioritise timely interventions and track mastery at the skill level rather than reteaching what's already known.

Large third‑party analysis (the EMERALDS study) also shows intensive use of MATHia workspaces is associated with meaningful algebra gains, an effect that can help equity goals by accelerating learning for students who enter behind.

Explore the platform's design and classroom features in the Carnegie Learning MATHia adaptive math software overview Carnegie Learning MATHia adaptive math software overview and read the efficacy findings in the EMERALDS third-party study on MATHia efficacy EMERALDS third-party study on MATHia efficacy for concrete impact data - imagine a Finnish math teacher receiving a live signal that pinpoints the tiny misconception blocking a student's next breakthrough.

Metric	Value	Source
Grade range	6–12	Carnegie Learning MATHia product page
Predicted improvement (median student)	+16 percentile points (with ~30 extra workspaces)	EMERALDS third-party study on MATHia efficacy
Research base	25+ years of learning science & data	How MATHia uses AI (Carnegie Learning blog)

“Most companies use AI to make computers smarter; we use AI to make students smarter.” - Dr. Steve Ritter, Carnegie Learning

Gradescope streamlines assessment in ways that matter for Finnish classrooms and higher‑education: AI‑assisted answer grouping and dynamic rubrics let teachers grade paper, code and bubble‑sheet exams far faster while keeping feedback consistent and data‑rich, and built‑in analytics surface per‑question gaps so instructors can target lessons rather than re‑teaching whole units; explore the platform at the Gradescope AI-assisted grading platform Gradescope AI-assisted grading platform.

It supports scanned handwritten work and programming autograders, integrates with common LMSs, and - crucially for Finnish schools focused on compliance - operates under Turnitin's enterprise controls with SOC2 and GDPR assurances Turnitin Gradescope compliance & integrations.

The productivity gains are tangible: instructors report grading hundreds of answers in minutes (one example: 10 multiple‑choice questions for ~250 students in 15 minutes), freeing time for pedagogy, regrades and the human coaching that AI should enable rather than replace.

Metric	Value	Source
Questions graded	700M+	Gradescope official statistics
Institution adoption	2,600+ universities	Gradescope institutional adoption
Reported grading time reduction	Up to 80%	Turnitin Gradescope product page

“Gradescope has revolutionized how instructors grade I don't use that word a lot, but once you've used this tool, there's no going back.”

Edudata.io and similar predictive‑analytics services can convert the mess of administrative spreadsheets and periodic surveys Finnish principals already use into actionable, early‑warning insights for students - if those tools are designed for the local realities uncovered in recent research.

A qualitative study of four Finnish principals found analytics are most often used for timetables, budgets and well‑being surveys rather than routine performance monitoring, with large schools (one participant manages ≈1,200 students) especially strained by manual processes and lone‑analyst workloads; read the full findings at the Educational Data Mining conference proceedings Principals' use of data analytics in Finnish schools - Educational Data Mining 2024 proceedings.

Practical uptake therefore depends less on flashy models and more on integration, automated data flows, shared dashboards, teacher training and DPIA‑ready workflows - the same roadmap that pilots and compliance projects recommend for Finnish deployments Pilot, DPIA, and teacher training roadmap for Finnish AI deployments.

When built to those specs, predictive signals (attendance trends, well‑being declines, early subject‑choice risk) can move schools from reactive firefighting to timely, targeted support before problems escalate.

Observed uses	Reported challenges
Timetables, budgets, well‑being surveys	Lone responsibility for data analysis
Occasional student performance checks (weekly/monthly)	Limited training and time to learn tools
Tools cited: Vilma, Primus, Google Forms, Excel	Privacy/regulatory constraints and lack of integration

Labster's immersive virtual labs give Finnish STEM courses a practical lift by letting students rehearse experiments in a safe, engaging digital environment before they ever touch real kit - an approach that University of Eastern Finland pilots show raised course pass rates by 16% and that Turku lecturers have used to expand remote access to biomedicine labs; see the full evidence review at the Labster evidence guide on virtual labs effectiveness and the University of Eastern Finland case study on Labster virtual labs for Finnish results.

By combining curriculum‑matched simulations, automated scoring and unlimited retries, Labster turns gateway classes from bottlenecks into springboards: across multiple studies virtual labs cut DFW rates by about 34%, drive very high engagement (roughly 74–82% highly engaged), and help lower‑performing students make meaningful pre‑to‑post gains, so instructors spend lab time coaching and probing deeper questions instead of babysitting equipment.

For Finnish schools focused on inclusion and GDPR‑conscious pilots, these simulations also support accessibility features and LMS integration, making them a pragmatic option in the national roadmap from pilot to classroom scale.

Metric	Value	Source
UEF pass‑rate change	+16%	University of Eastern Finland Labster case study on virtual labs
DFW (drop/fail/withdraw) reduction	−34%	Labster evidence guide 2024 on virtual labs efficacy
Student engagement	74–82% highly engaged	Labster evidence guide 2024 on student engagement with virtual labs

“In all our correlation models, we observed that Labster had a strong influence on students' learning output. Labster provides the best virtual environment with experiments that motivate students and pedagogically meaningful tasks that result in meaningful learning.” - Vesa Paajanen, Senior Lecturer, University of Eastern Finland

Generative assistants such as ChatGPT are already being folded into Finnish classrooms as curriculum co‑pilots, provided they follow the national emphasis on transparency and teacher oversight: The AI Track notes that University of Oulu workshops have trained teachers to audit generative tools (reaching some 85% of staff) and that educators using ChatGPT are required to submit ethical reviews, underscoring the accountability baked into rollout plans (AI Track analysis of AI in Finnish education).

For early years and busy primary teachers, task‑focused assistants can be pragmatic - tools like Elina promise

“customized, curriculum‑aligned lesson plans in seconds,”

turning a pile of classroom odds‑and‑ends into a printable activity that matches learning goals and parental communications (Elina AI assistant for educators - curriculum-aligned lesson plan generator).

But sensible pilots and privacy workstreams remain non‑negotiable: start with a pilot, a DPIA and teacher training roadmap so generative text models boost creativity and reduce workload without trading away GDPR or pedagogical control (pilot, DPIA and teacher training roadmap for AI in education).

A vivid classroom image: a teacher turning craft scraps and a short prompt into a tailored, multilingual activity pack before morning break - precisely the kind of time‑saving, curriculum‑aligned support Finland's guidelines aim to scale.

Duolingo's AI suite - powered by adaptive engines that predict what a learner will master next and NLP that reads spoken and written responses - offers Finnish classrooms a low‑friction route to more speaking practice and stronger personalization without forcing teachers to become engineers.

Features like Explain My Answer, Roleplay and the GPT‑4–backed Duolingo Max tier bring just‑in‑time feedback and simulated conversation practice (now even video calls with Lily), which can help learners practice production - the learning move research shows yields big gains - while the app's habit nudges (think: the green owl pinging at lunchtime) keep short daily routines consistent.

For Finland's GDPR‑forward rollout plans, these tools are most useful when run as structured pilots with DPIAs and clear teacher oversight so recordings and model updates meet local privacy rules; see the Duolingo Max overview and recent reporting on Video Call for technical and privacy details and pair that with a pilot/DPIA roadmap before scaling in schools.

“It provides the kind of learning opportunity that was previously only available to those who can afford to travel or hire a tutor.” - Luis von Ahn, Duolingo

Codento's playbook for Finland's schools and education services is a practical one: start small, cut friction, then scale responsibly - beginning with free, two‑hour AI workshops that in 1.5 years reached managers across 104 Finnish organisations and surfaced 677 concrete use‑case ideas focused overwhelmingly on operational wins like process automation and cost reduction.

The result for education leaders: low‑risk, high‑value starting points such as custom chatbots and admin automations that routinise timetables, speed student services, and free staff for pedagogy rather than paperwork; Codento's long‑term software partnership with the University of Helsinki shows how those pilots can evolve into robust, compliant systems (study‑sector integrations, cloud analytics and crisis tools) that support national reforms and research platforms - read the full Codento report on popular AI use cases in Finland and the University of Helsinki case study for concrete examples and lessons learned.

With a Google Cloud Partner award and a promise to deliver “at least one wild, growth‑oriented” AI idea per workshop, Codento frames chatbots not as flashy toys but as pragmatic levers for efficiency and eventual innovation in Finnish education.

“Finnish organizations strongly want to understand how artificial intelligence can be used to reduce costs, time and risks and to develop current operations, but it is easy to forget that growth can and should be built with the help of artificial intelligence.” - Anthony Gyursanszky, Codento CEO

Gamified platforms such as DreamBox and Smart Sparrow translate well to Finland's classrooms because game mechanics - points, badges, leaderboards and quests - turn repetition into low‑stakes practice and make productive failure visible so students reattempt without embarrassment; a 2025 mixed‑methods study even shows leaderboard‑based gamification can boost calculus performance at university level (How gamification boosts learning in STEM higher education), while practitioner reviews report large retention and engagement uplifts (roughly +40% retention in some summaries) that cut math anxiety and free teacher time for coaching (Ways games make learning coding, math and science more fun).

For Finnish schools the

so what?

is practical: when combined with a DPIA‑ready pilot and teacher training roadmap, gamified modules can be run GDPR‑consciously to increase daily practice, surface exactly which skills need reteaching, and nudge reluctant learners into measurable progress - start small, measure, then scale (pilot, DPIA and teacher training roadmap).

Metric	Value	Source
Leaderboard benefit (STEM study)	Enhances university calculus performance	International Journal of STEM Education (2025)
Retention uplift	~40% (reported in practitioner review)	Hurix Digital blog
Participation increase (case example)	~60% in one study cited	Park University gamification review

In Finland the ethical use of AI in schools starts with data protection: with an estimated 200–1,000 digital services touching each school and children's profiles easily accruing a permanent “digital footprint,” a thorough Data Protection Impact Assessment (DPIA) is not optional but central to bias mitigation, transparency and GDPR compliance.

Practical national guidance from the Data Protection Ombudsman lists the kinds of high‑risk processing (biometrics, profiling, large‑scale monitoring, sensitive data, location tracking) that trigger a DPIA, and the law (Article 35 GDPR) expects assessment before new AI features or systems go live - so schools that want to pilot generative assistants, analytics or video analysis must treat the DPIA as a living safeguard.

Metric	Detail	Source
Apps per school	200–1,000 (each can collect student data)	Edudata.io DPIA service
When DPIA required	High‑risk processing (profiling, large‑scale, sensitive data, new tech)	Finnish DPO / Ombudsman list
Practical offering	Ready‑made Wilma DPIA template (~50–100 pages), expert support, annual review	Edudata.io DPIA service

For Finnish education leaders looking for pragmatic support, Edudata.io offers an “extensive DPIA” service (ready‑made Wilma templates, expert review and annual updates) to speed compliance and reduce risk while preserving pupils' rights; pair that work with stakeholder consultation and routine DPIA refreshes to keep bias mitigation and data minimisation front and centre.

Practical next steps for Finnish educators are clear: start from the new national playbook - use the Finnish National Agency's "Artificial intelligence in education – legislation and recommendations" as the procurement and DPIA baseline, then test tools in short, tightly scoped pilots that include teacher training, measurable learning goals and a living DPIA so privacy and bias checks happen before scale.

Pair those pilots with hands‑on staff upskilling (short courses on prompts, workflows and classroom uses), measure impact (the national pilots show gains like +25% academic performance and −40% workload in some cases), and favour vendors who document GDPR‑compliant data flows and explainable models.

For schools ready to move faster, embed a teacher roadmap (pilot → DPIA → audit → scale) and consider practical training such as the Nucamp AI Essentials for Work syllabus to turn policy into classroom routines.

Share results publicly to meet the Guidelines' transparency and inclusivity goals and to help rural or smaller providers replicate effective practice.

Step	Action	Source
Groundwork	Use national guidance and DPIA templates before procurement	Finnish National Agency for Education – AI in Education legislation and recommendations
Pilot & train	Run short pilots with teacher workshops and measurable KPIs	AI Track analysis of AI in Finland education and teacher training
Build capacity	Offer practical prompt/tool training for staff	Nucamp AI Essentials for Work syllabus - practical AI training for educators

“AI in Finland must enhance - not replace - critical thinking.” - University of Oulu policy (cited in The AI Track)