Talent promotion in the AI laboratory at TU Braunschweig School pupils successfully participate in TU master's course

Artificial intelligence has long been shaping our everyday lives, whether through voice assistants or personalised music recommendations. But how do algorithms actually learn to recognise patterns and make decisions? Practical experience in this area is provided by the Pattern Recognition Computer Lab at the Institute of Communications Engineering (IfN) at Technische Universität Braunschweig, which has been offered as a master’s course since 2023 and has already been nominated for the TU Teaching Award several times. In the summer semester of 2025, the IfN ventured an experiment: For the first time, particularly high-achieving students from the tenth grade onwards were also allowed to participate – with surprising success and creditable microcredit points for later studies.

In the summer semester of 2025, the AI lab opened its virtual doors for the first time to a whole new target group: motivated students from the tenth grade onwards. The search for suitable candidates was carried out in cooperation with the NiedersachsenMetall Foundation. The requirements were high: excellent grades in mathematics and computer science as well as good English skills were required. Thirteen students from various schools and grades were ultimately selected from the applications.

The lab is divided into seven teaching units. To officially pass the module, six units must be successfully completed. But even those who do not complete the entire laboratory course will not come away empty-handed: for each unit passed, they will receive microcredits (small teaching units worth between 0.25 and 1.0 ECTS points). These can later be credited towards a degree at TU Braunschweig – a tangible incentive that builds bridges to the world of higher education even before students begin their studies.

One ECTS point usually corresponds to around 25 to 30 hours of work. A full academic year of full-time study normally corresponds to 60 ECTS points. The ECTS system allows academic achievements to be compared and credited between different universities and countries.

Impressive achievements

Of the eleven students who participated in the AI lab, ten were awarded microcredits. A total of seven participants, including one female student, can look forward to receiving formal certification of five official ECTS credits in the Master’s programme in Information Systems Engineering at TU Braunschweig – without even having to complete their A-levels! These credit points can generally be applied to relevant degree programmes nationwide in the Master’s elective area.

Professor Tim Fingscheidt, scientific director of the Computer Labs Pattern Recognition, says: “It was a high risk to invite students to a regular Master’s course. The risk of frustration was very high. Now we are glad we took the risk and are fascinated to see what pupils are capable of even without a high school diploma, bachelor’s degree or accompanying Master’s lecture.”

Outlook: Expansion of AI courses

The institute plans to continue offering the Computer Lab Pattern Recognition to pupils in the future in order to promote young talent at an early stage. Applications have already been received for the winter semester. In addition, the range of modules in the field of artificial intelligence is being expanded: starting in the 2025/2026 winter semester, the new lecture ‘AI Engineering’ will teach practical aspects of the use of large language models (LLMs). The accompanying exercises for this lecture will be designed along the lines of the Pattern Recognition Computer Lab in order to apply the successful teaching method here as well.

Background

The Pattern Recognition Computer Lab was developed at TU Braunschweig and offered for the first time in the summer semester of 2023 – since then, it has been held every semester. It was created as part of the AI4ALL joint project, which is funded by the Federal Ministry of Education and Research (BMBF) from 2021 to 2025.

The course is conducted entirely online: participants work on interactive programming tasks in so-called ‘notebooks’, which use Jupyter software to provide not only the tasks but also accompanying content. In addition, a group chat is available where questions can be asked and experiences exchanged.

Students at TU Braunschweig use the programme to deepen their understanding of the pattern recognition lecture in their master’s programme with practical exercises. A solid basic knowledge of mathematics and programming is required – requirements that are actually only expected in a master’s programme.

Text: Patrick Blumenberg