Computing & AI

• All projects include detailed manuals and experiment instructions.

• A complete set covering seven focus areas is designed for four to six students.

• Mathematics integration: Mathematical references have been added to each kit to strengthen the connection between mathematics and computer science.

• Curriculum alignment: The experiments are aligned with NGSS, national curricula (including German curricula) and PISA standards to meet the highest educational requirements.

• Classroom practicality: Each kit contains a manageable number of projects that are easy to integrate into everyday school life.

• All kits are supplied with complete materials, instructions and digital resources, including offline-capable software, to make learning engaging and effective.

Your Benefits

• Innovative stackable box system — modular, clearly organised and expandable

• Strong, age-appropriate integration of mathematics

• High durability and classroom practicality for schools

• Alignment with international and national standards

• Step-by-step build-up of a complete physics laboratory

Covered core areas:

Experience Code & Logic · Decode the World of Data · Build Your Own AI · Bring Robots to Life · Everything Smartly Connected · Safe & Responsible in the Digital World · A Look Inside the Computer

Topics: algorithmic thinking, block- and text-based programming, control structures, algorithms, software development

• Programming with loops and conditions.

• Drawing and moving objects on a coordinate grid.

• Designing and testing everyday algorithms such as searching and sorting.

• Creating a program using functions and lists.

• Structuring a larger program with data sets and modules.

• Testing, debugging and improving a program through the software development process.

Topics: data representation (binary, hexadecimal, text, image, sound), data collection, data analysis, databases

• Representing numbers and text in binary.

• Capturing and cleaning a real data set.

• Encoding images and sound in hexadecimal and comparing compression.

• Creating charts and dashboards.

• Building and querying a simple database using SQL.

• Analysing data and identifying trends.

Topics: how machines learn, classification, neural networks, deep learning, generative AI, AI agents, AI ethics and society

• Training a simple image or speech classifier.

• Exploring decision trees using real-world examples.

• Investigating how a neural network weights inputs.

• Critically evaluating generative AI outputs and identifying misinformation.

• Building and testing a simple AI agent that responds to its environment.

• Designing and optimising your own AI model, from data preparation to inference.

• Exploring the basic idea of large language models and knowledge representation.

• Comparing deep learning with unsupervised and reinforcement learning using a small example.

• Assessing the impact of AI on society and the labour market.

Topics: sensors and actuators, physical computing (micro:bit, Arduino), control loops, robot programming, automation

• Building and programming a mobile robot.

• Reading sensor values and responding to them.

• Implementing a closed control loop, for example line following.

• Programming a robotic arm for a sequence of movements.

Topics: computer networks, the internet, protocols and addressing, the Internet of Things, connected systems

• Setting up a small local network and exchanging messages.

• Connecting a sensor to an IoT platform.

• Exploring how the internet works: protocols, layers and IP and MAC addressing.

• Comparing network topologies and measuring data transmission.

Topics: cybersecurity, encryption, data protection and data protection law, copyright, information systems, digital ethics and human–AI collaboration

• Investigating data protection in everyday apps.

• Exploring how passwords and keys protect data.

• Encrypting and decrypting messages using classical methods.

• Discussing and documenting responsible use of AI.

• Understanding and building a small information system, such as a class database or a booking system.

• Examining copyright, licences and data protection rules for software and data.

• Designing a human–AI collaboration workflow and evaluating the distribution of roles.

Topics: computer architecture (processor, memory, storage), Boolean logic and logic gates, operating systems and system software

• Exploring the components of a computer and how data flows between the processor, memory and storage.

• Building simple logic circuits using AND, OR and NOT.

• Investigating how the processor executes a program and how memory and storage work together.

• Exploring the role of the operating system and system software.