The students should get a deep understanding of the notion of randomness and its usefulness. Using basic elements probability theory and number theory the students will discover randomness as a source of efficiency in algorithmic. The goal is to teach the paradigms of design of randomized algorithms.

In the course Professional Exercises the students achieve additional school-relevant experiences. The students carry out individually specified, practice related projects, in which they support, document or reflect on learning processes.

The unit "Subject Didactics of Computer Science I" addresses key contributions of computer science to general education. The course deals with the thoughtful choice of educational contents for computer science classes, which takes into account its comprehensibility for different age groups as well as didactic approaches suitable for a successful knowledge transfer.

This course deals primarily with didactic aspects of computer science and its key contributions to general education nurturing the youths' development of a unique and indispensable way of thinking while at the same time leading to their understanding of our world and to higher education entrance qualifications.

Students undergo a practical teaching course for several weeks at a secondary school or at a university of applied sciences. The training consists of two parts: the observation of lessons and conducting lessons. Students will be supervised by an experienced teacher.

Students undergo a practical teaching course for several weeks at a secondary school or at a university of applied sciences. The training consists of two parts: the observation of lessons and conducting lessons. Students will be supervised by an experienced teacher.

Students apply the insights, abilities and skills they have acquired within the context of an educational institution. They observe 10 lessons and teach 20 lessons independently. Two of them are as assessed as Examination Lessons.

Students apply the insights, abilities and skills they have acquired within the context of an educational institution. They observe 10 lessons and teach 20 lessons independently. Two of them are as assessed as Examination Lessons.

The teaching practice takes in 50 lessons: 30 are taught by the students, and the students sit in on 20 lessons. The teaching practice lasts 4-6 weeks. It gives students the opportunity to implement the contents of their specialist-subject, educational science and subject-didactics training in the classroom. Students also conduct work assignments in parallel to their teaching practice.

In the final phase of their training, students have to apply and test the insights, abilities and skills they have acquired. They spend 3-5 weeks in an educational institution, during which time they observe 10 lessons and teach 30 lessons independently. The Teaching Internship is complemented by 10 further observed lessons, which are integrated into the Mentored Work in Subject Didactics.

This is a supplement to the Teaching Internship required to obtain a Teaching Diploma in the corresponding subject. It is aimed at enlarging the already acquired teaching experience. Students observe 10 lessons and teach 15 lessons independently.

Concepts to cope with: a) what can be accomplished in a fully automated fashion (algorithmically solvable) b) How to measure the inherent difficulty of tasks (problems) c) What is randomness and how can it be useful? d) What is nondeterminism and what role does it play in CS? e) How to represent infinite objects by finite automata and grammars?