Where language and technology come together, the field of Natural Language Processing (NLP) emerges. Using machine learning techniques, such as training models to recognize text, images, or sound frequencies, we can enable computers to intelligently work with language. Well-known NLP applications of machine learning include translation programs, voice control systems, or virtual assistants like Siri, and chat robots.

We explore questions like How can we automatically understand, translate, and even write texts?, Can a computer recognize emotions or irony in text?, and especially How important is data?. Students in the second and third grades of secondary education gain insight into the NLP domain and take their first steps into the world of programming with Python.

Scientific Research

In the field of Natural Language Processing (NLP), researchers rely on algorithms to examine texts. They use both knowledge-based and data-based artificial intelligence for this purpose. Through sentiment analysis, for example, they can determine whether people express themselves positively or negatively about certain products, companies, or individuals on social media. Based on writing style, they try to identify who wrote a particular text. They also investigate how they can distinguish personality types based on language. A good knowledge of linguistics, computer science, and psychology is indispensable for this; NLP is an interdisciplinary field.

Developments in language technology provide new tools to detect fake news, combat crime, and make healthcare more efficient; there are also numerous applications in the business world.


To process natural language, artificial intelligence is used. Students explore natural language processing systems for applications such as sentiment analysis, cyberbullying detection, and author recognition. These systems do not deal with raw data; the texts are prepared before the computer analyzes them. Students gain insight into the principles of computational thinking, which are clearly illustrated here, such as decomposition, pattern recognition, abstraction, and algorithms. They learn about the possibilities and limitations of knowledge-based and data-based systems.


More and more companies and organizations place a chatbot on their website with a view to better service. Thanks to NLP and considering user expectations, these automatic conversation partners are becoming increasingly pleasant to use. Chatbots are used for customer service, HR, providing information, and in various domains such as healthcare, entertainment, the business world, politics, and education. Students experience the limitations of a rule-based chatbot themselves, making them more media-savvy, as most chatbots in commercial applications today still primarily operate on a rule-based basis.

Sentiment Analysis

The popularity of the internet not only led to the rise of social media but also gave rise to a new research domain: detecting feelings and opinions in texts. Sentiment analysis has already proven its importance for the business world, industry, and society. Automatically assigning a sentiment score to online customer reviews, tweets about politics, or a chatbot conversation, it all happens with artificial intelligence: NLP applied in both a knowledge-based (using rules) and data-based (using machine learning) manner.

Learning paths

No learning paths could be found with your preferences.


Project Sheet Chatbot Download This is a brief overview of the Chatbot project with project structure and characteristics.
BrAInfood Chatbots Download In this BrAInfood - aimed at young people - the Knowledge Center Data & Society provides more information about chatbots. The BrAInfood includes a fictional story about Lotte talking to a chatbot and presumably providing information about her to companies. Further, some points related to chatbots are explained, along with some tips for young people to better protect their (personal) data. In this way, we aim to make young people more aware of how chatbots work and encourage them to reflect on the data collected about them.
BrAInfood Personalized Newsfeeds Download In this BrAInfood from the Knowledge Center Data & Society, tips are given on how to keep control over your newsfeed.
Manual 'Chatbot' - Also available in print Download Teachers acquire sufficient background information through this manual to work with (a part of) the 'Chatbot' project in the classroom. The book covers various aspects of language technology, such as the history of artificial intelligence, its ethical aspects, sentiment analysis, and cyberbullying detection, chatbots, speaking digital assistants, and author recognition. It also addresses the STEM objectives and the objectives related to digital competence and media literacy.
Improbotics - Lesson Plan - Teacher's Version Download In the theater performance Improbotics, a social robot improvises in the scenes. The lesson plan provides information about the technologies used.
Improbotics - Lesson Plan - Students Download In the theater performance Improbotics, a social robot improvises in the scenes. The lesson plan provides information about the technologies used.
The teaching material is made available under the terms of a Creative Commons BY-SA license.