Lesson Series
Teacher AI Tutorial Pack
Course for Teachers on Practical Use of AI in the Classroom, from Prompt Optimization to AI-Resistant Tasks.
Didactic Concept
The lesson series provides a structured introduction to the didactically reflected use of AI in the classroom and systematically develops competences in handling prompting, evaluation, and school implementation. The progression follows a clear line from analyzing basic AI functionality through concrete application scenarios to evaluation and governance. Methodically, the series connects prompt optimization, critical analysis of AI outputs , and developing robust task formats with practical teaching references. Theory and application are closely linked, so that results can be transferred directly to school contexts.
For teachers, the series offers a clear structured sequence of building blocks with transparent competence development. The modular design allows for flexible integration into existing teaching or training formats and supports systematic further development of one’s own teaching practice.
Competence development
- Development of more precise prompts and application of structured prompt frameworks to control AI outputs
- Analysis and evaluation of AI-generated content based on defined quality criteria
- Designing differentiated tasks, feedback processes, and lesson plans with AI support
- Development of process-oriented and AI-resistant task formats as well as evaluation rubrics
- Application of procedures for fair performance assessment and transparent documentation
- Planning and implementation of school-based AI strategies including regulations and implementation processes
Structure of the series
Module 1: What AI can – and cannot do
Learn to create precise prompts for teaching and critically evaluate AI outputs.
This module lays the foundation for the entire course by systematically working out central differences between vague and precise prompts. Participants develop an understanding of quality criteria and learn to critically analyze and control AI outputs.
Module 2: AI for lesson preparation
A compact learning unit for teachers: You create four practical prompt templates (differentiation, feedback, quick planning, text adaptation) and learn to review AI outputs based on clear criteria and iteratively refine them.
Building on the basics, concrete use cases for lesson preparation are developed. The focus is on creating structured prompt templates and iteratively improving results in terms of teaching requirements.
Module 3: KI-resistant tasks & rubrics
Goal: Teachers design task formats that make student effort visible by systematically incorporating thinking steps, intermediate products, proof obligation, and process-related evaluation in prompts.
In this module, task formats are developed that focus on thought processes and verifiable results. The connection between task assignment and evaluation is systematically designed so that student effort becomes visible and evaluable.
Module 4: Fair diagnostics & performance evaluation
This learning unit guides teachers through four consecutive prompt building blocks for fair diagnostics and performance evaluation.
The module expands the series with diagnostic and evaluation-related aspects. Procedures are developed that enable a differentiated analysis of performances and at the same time ensure transparent and verifiable evaluation processes.
Module 5: AI Governance from Conversation to Implementation Plan
This course guides educators step by step through central prompt templates for school AI governance.
The focus then shifts to the institutional level. The module supports the development of rulebooks, communication strategies, and implementation plans for handling AI in schools.
Contents at a Glance
Module 1: What AI Can Do – and What It Can’t
| Content | Focus | Duration |
|---|---|---|
| Prompting in the Classroom: Vague vs. Precise Prompts Compared | Comparison of Prompts and Derivation of Quality Features, as well as Targeted Improvement | 15 minutes |
| RCFG in Practice: Quickly Improving Weak Prompts | Optimization of Prompts Based on Structured Criteria and Evaluation of Effectiveness | 15 minutes |
| Have KI-Texts Reviewed: Create First, Then Critically Analyze | Creation and Critical Review of KI-Texts with Verification Questions | 12 min -> @@ITEM_0001@@12 minutes |
Module 2: AI for Lesson Preparation
| Content | Focus | Duration |
|---|---|---|
| Diverse Tasks with a Prompt (3 Levels, No Sample Solutions) | Creation of differentiated task formats with clear structures and constraints | 15 min |
| Module 2.2: Formative feedback without solutions (Prompting) | Development of structured feedback prompts with clear boundaries and prioritization | 15 min |
| Module 2.3: Rapid lesson planning in the Prompt format (Prompting) | Creation of compact lesson plans and targeted improvement of individual elements | 15 min |
| Module 2.4: Adapting texts to target levels without new facts | Adaptation of subject texts to different target levels while maintaining content | 12 min |
Module 3: KI-resistant tasks & rubrics
| Content | Focus | Duration |
|---|---|---|
| Process-oriented tasks: Prompts that make thinking steps visible | Designing tasks with visible thought processes and intermediate products | 15 min |
| Module 3.2: Material-bound worksheets with proof obligation | Creating material-bound tasks with clear proof obligations and structure | 12 min |
| Module 3.3: Evaluation rubrics that honor thinking paths (including KI use) | Developing transparent evaluation rubrics with process and content criteria | 12 min |
Module 4: Fair diagnostics & performance assessment
| Content | Focus | Duration |
|---|---|---|
| Style indicators fairly describe: Prompt-Template with evidence, alternatives, and non-statements | Description of style features with evidence and alternative explanations | 12 minutes |
| Module 4.2: Fairly comparing two texts (without authorship statements) | Comparing texts with clear separation between observation and interpretation | 15 min |
| Module 4.3 — Neutral questions for oral clarifications | Creating neutral questions to clarify services without assumptions | 12 minutes |
| Module 4.4: Evaluation documentation as a prompt | Developing structured and traceable evaluation protocols | 12 minutes |
Module 5: KI Governance from conversation to implementation plan
| Content | Focus | Duration |
|---|---|---|
| Module 5.1: Neutral conversation guide for KI suspicion (Prompting) | Developing neutral conversation guides without accusations | 12 minutes |
| Module 5.2: KI usage rules in two versions (traffic light logic) | Creating differentiated rule sets for KI use | 12 min |
| Module 5.3: KI Risk-Chance Matrix in the school context prompt | Analyzing chances and risks with structured measures | 12 min |
| Module 5.4: Communication and implementation plan (2 prompts) | Creating implementation plans and communication formats | 14 min |
The series supports a systematic integration of AI into teaching and school development through clearly structured building blocks and transparent goals.
You can use the modules flexibly, adapt them, and test them in your own educational context.