Turkey - AI in Education Guide

Overview

The Ministry of National Education published an interactive teacher guide in July 2025 titled "Yapay Zeka ve Eğitim: Öğretmenler İçin Uygulamalı Prompt Mühendisliği ve Üretken Araçlarla Yenilikçi Öğrenme Stratejileri" that presents practical, classroom‑oriented methods to use generative AI. The document is available from the Ministry and YEĞİTEK portals: see the Ministry announcement and the downloadable guide. The guide's objective is to strengthen teacher capacity to select, design and moderate AI‑enabled learning activities while protecting learners’ rights and ensuring pedagogical value. It groups AI uses into planning and content creation, learning activity design, research/data analysis, and assessment/feedback. The guide aims to increase technology literacy, encourage ethical and lawful use of tools, and provide immediate, replicable examples for diverse subjects. Full text (PDF) and indexed announcement pages are published on the Ministry of Education web resources; primary publication notices appear on the Ministry site and the YEĞİTEK portal. For the original release and download, see the Ministry news release and the YEĞİTEK publication page: MEB announcement and YEĞİTEK announcement, and the guide file hosted by YEĞİTEK: Teacher Guide (PDF).

Definitions

Key terms used in the guide are defined in a teacher‑friendly manner: "Generative AI" (models producing text, images, audio, or video from prompts), "prompt engineering" (crafting input instructions to obtain useful, accurate model outputs), "student data" (any personally identifiable information, assessment records, or work products), "model provider" (third‑party commercial or open‑source AI service), and "human‑in‑the‑loop" (teacher oversight of AI outputs before student use). The guide distinguishes low‑risk pedagogical uses (idea generation, draft feedback) from higher‑risk operations (grading, individualized profiling) and clarifies what constitutes sensitive data in education contexts.

Governance and Institutional Framework

The guide situates accountability within existing MEB structures, recommending that schools establish local governance arrangements involving school principals, IT coordinators, YEĞİTEK school leads, and data protection focal points. It recommends school‑level policies on account provisioning (favor institutional accounts where possible), password hygiene, access controls, and vendor review. Implementation is coordinated with the Ministry's YEĞİTEK unit; see the YEĞİTEK announcement for contact and operational details. The document advises formalizing procurement checks for AI services (security, retention policies, CV of model provider), clarifying responsibilities for vendor contracts and reviewing Terms of Service for data uses. The guide further recommends integrating AI use into school improvement plans and suggests roles for provincial directorates and Ministry teams in oversight, capacity building and tool evaluation. For Ministry-level dissemination and contact, see YEĞİTEK announcement and the official press note on MEB's site: MEB announcement.

Key Focus Areas

The guide identifies four primary pedagogical domains for generative AI application: 1) Planning and effective content production — using AI to produce differentiated lesson resources, multimedia, rubrics and scaffolded exercises; 2) Teaching and learning activity design — using AI for simulation prompts, role playing, problem‑based scenarios, adaptive scaffolding and formative feedback; 3) Research and data analysis — employing AI for classroom action research, summarizing curriculum materials, and analyzing assessment trends while ensuring anonymization; 4) Assessment, measurement and feedback — employing AI to produce quick feedback and item banks but explicitly discouraging sole reliance on automated high‑stakes grading without human review. For each domain the guide provides subject‑specific examples (language arts, STEM, social studies, arts), sample prompts and class flow templates that show how a teacher frames an activity, solicits AI output, moderates results, and integrates student reflection. Practical guidance includes eight prompt formulas (e.g., 'Context + Role + Instruction + Constraints + Output Format') and troubleshooting tips where outputs are biased, factually inaccurate or inappropriate. The guide emphasizes pedagogical alignment — AI outputs should be judged against learning objectives, not used for convenience alone. It also discusses inclusion practices: adapting prompts to learners with special educational needs, ensuring accessibility of AI‑generated multimedia, and promoting digital citizenship through classroom conversations about accuracy, bias and authorship.

Implementation Framework

The guide provides stepwise implementation guidance: initial awareness and policy alignment; pilot projects in volunteer classes; teacher training modules on prompt design and moderation; procurement and technical set‑up (institutional accounts, network restrictions, privacy configurations); routine documentation and lesson logging; and expansion with continuous evaluation. It recommends short micro‑learning modules for teachers (2–3 hours) and longer certification pathways for YEĞİTEK school leads. Institutional readiness checklists include infrastructure (devices and bandwidth), secure identity management (prefer institutional e‑mail accounts), and data handling rules consistent with KVKK (Personal Data Protection Law). The guide suggests simple risk assessments before pilots (data types, student ages, lesson stakes) and a decision matrix to choose between on‑device, hosted or cloud model deployments. Schools are advised to create consent procedures for involving students under age thresholds and to provide opt‑out options for families where appropriate.

Monitoring and Evaluation

Monitoring guidance recommends collecting qualitative and quantitative indicators: teacher confidence metrics, student engagement and learning outcome changes, incidence reports (errors, harms, privacy near‑misses), and technical logs (tool usage, data flows). Evaluation cycles should be short and iterative (6–12 week pilot windows) with clearly defined success criteria tied to curriculum goals. The guide suggests peer review of exemplar lessons, Ministry‑level aggregation of pilot outcomes, and a shared repository for validated prompts and lesson plans maintained by YEĞİTEK. It also recommends establishing reporting lines for unexpected harms and periodic review of vendor data‑handling practices.

Penalties, Liability, and Appeals

The guide itself is advisory and does not create new statutory penalties; however it instructs schools to use existing Ministry disciplinary procedures and data breach processes where misuse occurs. It recommends that incidents involving unlawful data disclosure be reported to the school authority, provincial directorate and, where appropriate, to the Personal Data Protection Authority (KVKK). For professional misconduct stemming from misuse of AI (e.g., exposing student sensitive data), the guide signals potential referral to established teacher discipline frameworks. It also advises clear remediation steps (revocation of tool access, mandatory retraining, documented corrective plans) and suggests an appeals process through school management and provincial directorates for contested decisions.

Relationship to Other Instruments

The guide is intended to complement existing national instruments: KVKK (Personal Data Protection Law No. 6698), MEB curricula and assessment rules, and broader Ministry AI policy initiatives. It refers to prior and concurrent MEB outputs on AI ethics and YEĞİTEK publications. The guide is not a statutory regulation but a practical implementation instrument aligned with national education policy priorities. It encourages coordination with institutional data protection officers and references standard procurement and contract management practices when engaging third‑party vendors.

International Alignment

Content is framed to be consistent with international best practices in AI in education, echoing widely adopted principles such as transparency, accountability, privacy by design and human oversight. The guide encourages alignment with emerging international guidance (for example, EU‑level AI ethics frameworks and UNESCO recommendations on AI in education) and suggests that YEĞİTEK monitor international regulatory developments to update technical recommendations and vendor evaluation criteria. Teachers are advised to follow global best practices when adopting open-source transformers or commercial platforms and to document cross‑border data flows where necessary for compliance with national rules.

Implementation Timeline

Sources and References