Search result: Catalogue data in Spring Semester 2020

Number	Title	Type	ECTS	Hours	Lecturers
Computer Science Teaching Diploma More informations at : Link
Educational Science Course offerings in the category Educational Science are listed under "Programme: Educational Science for Teaching Diploma and TC".
851-0240-01L	Designing Learning Environments for School (EW2 TD) Prerequisites: successful participation in 851-0240-00L "Human Learning (EW1)". Adresses to students enrolled either in Teaching Diploma* (TD) or Teaching Certificate (TC) in Computer Science, Mathematics or Physics. *Except for students of Sport Teaching Diploma, who complete the sport-specific course unit EW2.	O	3 credits	2V	E. Stern, P. Greutmann, J. Maue
Abstract	Teaching is a complex skill. The lecture comprises (a) presentations about the theoretical background of this skill, (b) discussions of practical aspects, and (c) practical exercises.
Learning objective	The participants have the conceptual und procedural knowledge, and skills necessary for long-term planning, preparing, and implementing good lessons. They can apply this knowledge on different topics of their scientific STEM-background.
Content	We discuss characteristics of successful lessons and how to design such lessons by using curricula and lesson plans, teaching goals and a variety of teaching methods.
Lecture notes	The lecture comprises interactive parts where the participants elaborate and extend their knowledge and skills. Thus, there is no comprehensive written documentation of the lecture. The participants can download presentation slides, learning materials, and templates from "Moodle".
Literature	The necessary literature can be downloaded from "Moodle".
Prerequisites / Notice	The lecture EW2 can only be attended by students who already successfully completed the lecture Human Learning (EW1). There will be two independent lectures for different groups of students. You will get further information in an email at the beginning of the semester. To get the Credits you have to - regularly attend to the lecture - have the grade 4 or higher in the final written exam.
851-0240-24L	Designing Learning Environments for Schools (EW2 LD) - Portfolio - Enrolment only possible with simultaneous enrolment in course 851-0240-01L Designing Learning Environments for School (EW2 LD)! - Prerequisites: successful participation in 851-0240-00L "Human Learning (EW1)". - Adresses to students enrolled either in Teaching Diploma* (TD) or Teaching Certificate (TC) in Computer Science, Mathematics or Physics. *Except for students of Sport Teaching Diploma, who complete the sport-specific course unit EW2.	O	1 credit	2U	P. Greutmann, J. Maue
Abstract	In this lecture, you design a portfolio, i.e. a complete and elaborated teaching enviroment for schools, based on your scientific STEM-background
Learning objective	This lecture is an implementation and transfer of the theoretical inputs provided by the lecture "Designing Learning Environments for School" (EW2).
851-0242-08L	Research Methods in Educational Science Number of participants limited to 30. This course unit can only be enroled after successful participation in, or imultaneous enrolment in the course 851-0240-00L "Human Learning (EW 1)" .	W	1 credit	1S	P. Edelsbrunner, T. Braas, C. M. Thurn
Abstract	Literature from learning sciences will be read and discussed. Research methods will be in focus. At the first meeting all participants will be allocated to working groups and two further meetings will be set up with the groups. In the small groups students will write critical short essays about the read literature. The essays will be presented and discussed in the plenum at the third meeting.
Learning objective	- Understand research methods used in the empirical educational sciences - Understand and critically examine information from scientific journals and media - Understand pedagogically relevant findings from the empirical educational sciences
851-0242-11L	Gender Issues In Education and STEM Number of participants limited to 20. Enrolment only possible with matriculation in Teaching Diploma or Teaching Certificate (excluding Teaching Diploma Sport). Prerequisite: students should be taking the course 851-0240-00L Human Learning (EW1) in parallel, or to have successfully completed it.	W	2 credits	2S	M. Berkowitz Biran, T. Braas, C. M. Thurn
Abstract	In this seminar, we introduce some of the major gender-related issues in the context of education and science learning, such as the under-representation of girls and women in science, technology, engineering and mathematics (STEM). Different perspectives, controversies and empirical evidence will be discussed.
Learning objective	- To familiarize students with gender issues in the educational and STEM contexts and with controversies regarding these issues. - To develop a critical view on existing perspectives. - To integrate this knowledge with teacher's work.
Content	Why do fewer women than men specialize in STEM (science, technology, engineering and mathematics)? Are girls better in language and boys better in math? These and other questions about gender differences relevant to education and STEM learning have been occupying researchers for decades. In this seminar, students will learn about major gender issues in the educational context and the different perspectives for understanding them. Students will read and critically discuss selected publications on these topics and their implications for the classroom context. There will be weekly (or bi-weekly) assignments as well as a final project in which students will integrate and elaborate on the topics learned in the seminar.
Prerequisites / Notice	Recommended: Completion of the course 851-0240-00L Human Learning (EW1). Active participation in the seminar.
» see Educational Science Teaching Diploma

Subject Didactics in Computer Science Important: You can only enrole in the courses of this category if you have not more than 12 CP left for possible additional requirements.
Number	Title	Type	ECTS	Hours	Lecturers
272-0102-00L	Subject Didactics of Computer Science II Prerequisite: Subject Didactics of Computer Science I	O	4 credits	3G	J. Hromkovic, G. Serafini
Abstract	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.
Learning objective	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. Subject Didactics in Computer Science II deals with the adequate choice of educational content for computer science, taking in account its comprehensibility for different age groups and the didactic methods suitable for a succesful knowledge transfer. Within the scope of a semester exercise the students develop and document an adaptive teaching unit for computer science. They improve their practical knowledge of the teaching methods and techniques introduced in Subject Didactics in Computer Science I. The aim of the course is to combine the mathematical and algorithmic way of thinking with the approaches adopted by engineering disciplines. The students understand the basic concepts of computer science in the context of a broad and deep knowledge. Through this understanding, they manage to prepare teaching materials for a successful knowledge transfer and to pass their passion for the subject on to their pupils. The students know various teaching methods including their advantages and disadvantages. They can handle unequal levels of the learners' prior knowledge. Besides of holding classes the students do care about the individual pupil support. They encourage the autonomy of the learners. They manage to work with diverse target groups and to establish a positive climate for learning. The students are able to express themselves using a comprehensible and refined professional language, both spoken and written, and they master the basic terms of computer science. Besides of the English terminology they are familiar with the german expressions. The students are able to produce detailed, matured, linguistically correct and design-wise appealing teaching materials.
Content	The main themes of Subject Didactics of Computer Science II are Cryptology and Computability. The unit focuses on the content of computer science that conveys general educational values. this aims at the understanding of basic concepts of the science, such as - Algorithm - Complexity - Determinism - Nondeterminism - Probability - Computation
Lecture notes	Unterlagen und Folien werden zur Verfügung gestellt.
Literature	J. Hromkovic: Sieben Wunder der Informatik: Eine Reise an die Grenze des Machbaren, mit Aufgaben und Lösungen. Vieweg+Teubner; Auflage: 2 (2008). K. Freiermuth, J. Hromkovic, L. Keller und B. Steffen: Einfuehrung in die Kryptologie: Lehrbuch für Unterricht und Selbststudium. Springer Vieweg; Auflage: 2 (2014). J. Hromkovic: Berechenbarkeit: Logik, Argumentation, Rechner und Assembler, Unendlichkeit, Grenzen der Automatisierbarkeit. Vieweg+Teubner; Auflage: 1 (2011). H.-J. Böckenhauer, J. Hromkovic: Formale Sprachen: Endliche Automaten, Grammatiken, lexikalische und syntaktische Analyse. Springer Vieweg; Auflage: 1 (Januar 2013).
Prerequisites / Notice	Bewilligung der Dozierenden für alle Studierenden notwendig
272-0103-00L	Mentored Work Subject Didactics Computer Science A Mentored Work Subject Didactics in Computer Science for TC andTeaching Diploma.	O	2 credits	4A	J. Hromkovic, G. Serafini
Abstract	In their mentored work on subject didactics, students put into practice the contents of the subject-didactics lectures and go into these in greater depth. Under supervision, they compile tuition materials that are conducive to learning and/or analyse and reflect on certain topics from a subject-based and pedagogical angle.
Learning objective	The objective is for the students: - to be able to familiarise themselves with a tuition topic by consulting different sources, acquiring materials and reflecting on the relevance of the topic and the access they have selected to this topic from a specialist, subject-didactics and pedagogical angle and potentially from a social angle too. - to show that they can independently compile a tuition sequence that is conducive to learning and develop this to the point where it is ready for use.
Content	Thematische Schwerpunkte Die Gegenstände der mentorierten Arbeit in Fachdidaktik stammen in der Regel aus dem gymnasialen Unterricht. Lernformen Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
Lecture notes	Eine kurze Anleitung zur mentorierten Arbeit in Fachdidaktik wird zur Verfügung gestellt.
Literature	Die Literatur ist themenspezifisch. Die Studierenden beschaffen sie sich in der Regel selber (siehe Lernziele). In besonderen Fällen wird sie vom Betreuer zur Verfügung gestellt.
Prerequisites / Notice	Die Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.
272-0104-00L	Mentored Work Subject Didactics Computer Science B Mentored Work Subject Didactics in Computer Science for Teaching Diploma and for students upgrading TC to Teaching Diploma.	O	2 credits	4A	J. Hromkovic, G. Serafini
Abstract	In their mentored work on subject didactics, students put into practice the contents of the subject-didactics lectures and go into these in greater depth. Under supervision, they compile tuition materials that are conducive to learning and/or analyse and reflect on certain topics from a subject-based and pedagogical angle.
Learning objective	The objective is for the students: - to be able to familiarise themselves with a tuition topic by consulting different sources, acquiring materials and reflecting on the relevance of the topic and the access they have selected to this topic from a specialist, subject-didactics and pedagogical angle and potentially from a social angle too. - to show that they can independently compile a tuition sequence that is conducive to learning and develop this to the point where it is ready for use.
Content	Thematische Schwerpunkte Die Gegenstände der mentorierten Arbeit in Fachdidaktik stammen in der Regel aus dem gymnasialen Unterricht. Lernformen Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
Lecture notes	Eine kurze Anleitung zur mentorierten Arbeit in Fachdidaktik wird zur Verfügung gestellt.
Literature	Die Literatur ist themenspezifisch. Die Studierenden beschaffen sie sich in der Regel selber (siehe Lernziele). In besonderen Fällen wird sie vom Betreuer zur Verfügung gestellt.
Prerequisites / Notice	Die Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.

Professional Training Important: You can only enrole in the courses of this category if you have not more than 12 CP left for possible additional requirements.
Number	Title	Type	ECTS	Hours	Lecturers
272-0202-00L	Professional Exercises	O	2 credits	4U	G. Serafini, J. Hromkovic
Abstract	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.
Learning objective	Achievement of additional school-relevant experiences. The students carry out individually specified, practice related projects, in which they support, document or reflect on learning processes.
Content	The course Professional Exercises offers the opportunity for additional school-relevant activities related to practice. The students are supported by the lecturers or by experienced teachers. They assist teachers at school, they create training systems and tests, correct the written homework of pupils and evaluate the progress of a class. The students create explanations and detailed solutions to exercises with respect to the actual knowledge of the pupils. A written assignment states the exact scope of the activity.
272-0203-00L	Teaching Internship in Computer Science	O	8 credits	17P	J. Hromkovic, G. Serafini
Abstract	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.
Learning objective	- Students use their specialist-subject, educational-science and subject-didactics training to draw up concepts for teaching. - They are able to assess the significance of tuition topics in their subject from different angles (including interdisciplinary angles) and impart these to their pupils. - They acquire the skills of the teaching trade. - They practise finding the balance between instruction and openness so that pupils can and, indeed, must make their own cognitive contribution. - They learn to assess pupils' work. - Together with the teacher in charge of their teacher training, the students constantly evaluate their own performance.
Content	Die Studierenden sammeln Erfahrungen in der Unterrichtsführung, der Auseinandersetzung mit Lernenden, der Klassenbetreuung und der Leistungsbeurteilung. Zu Beginn des Praktikums plant die Praktikumslehrperson gemeinsam mit dem/der Studierenden das Praktikum und die Arbeitsaufträge. Die schriftlich dokumentierten Ergebnisse der Arbeitsaufträge sind Bestandteil des Portfolios der Studierenden. Anlässlich der Hospitationen erläutert die Praktikumslehrperson ihre fachlichen, fachdidaktischen und pädagogischen Überlegungen, auf deren Basis sie den Unterricht geplant hat und tauscht sich mit dem/der Studierenden aus. Die von dem/der Studierenden gehaltenen Lektionen werden vor- und nachbesprochen. Die Praktikumslehrperson sorgt ausserdem dafür, dass der/die Studierende Einblick in den schulischen Alltag erhält und die vielfältigen Verpflichtungen einer Lehrperson kennen lernt.
Literature	Wird von der Praktikumslehrperson bestimmt.
Prerequisites / Notice	Findet in der Regel am Schluss der Ausbildung, vor Ablegung der Prüfungslektionen und vor der Lerneinheit „Lernwirksam unterrichten“ statt.
272-0204-00L	Teaching Internship in Computer Science II Teaching Internship for students upgrading TC to Teaching Diploma.	W	4 credits	9P	J. Hromkovic, G. Serafini
Abstract	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.
Learning objective	Die Studierenden können die Bedeutung von Unterrichtsthemen in ihrem Fach unter verschiedenen Blickwinkeln einschätzen. Sie kennen und beherrschen das unterrichtliche Handwerk. Sie können ein gegebenes Unterrichtsthema für eine Gruppe von Lernenden fachlich und didaktisch korrekt strukturieren und in eine adäquate Lernumgebung umsetzen. Es gelingt ihnen, die Balance zwischen Anleitung und Offenheit zu finden, sodass die Lernenden sowohl über den nötigen Freiraum wie über ausreichend Orientierung verfügen, um aktiv und effektiv flexibel nutzbares (Fach-)Wissen zu erwerben.
Content	Das Aufbaupraktikum richtet sich an Studierende, die bereits das Didaktik-Zertifikat in ihrem Fach erworben haben und nun eine Aufbauausbildung zum Lehrdiplom für Maturitätsschulen absolvieren. In diesem zusätzlichen Praktikum sollen die Studierenden vertiefte unterrichtliche Erfahrungen machen. Auf der Grundlage der zusätzlich erworbenen Kenntnisse und mit Hilfe der ihnen jetzt zu Verfügung stehenden Instrumente analysieren sie verschiedene Aspekte des hospitierten Unterrichts. In dem von ihnen selbst gestalteten Unterricht nutzen sie beim Entwurf, bei der Durchführung und der Beurteilung ihrer Arbeit insbesondere die zusätzlich gewonnen Erkenntnisse aus der allgemeinen und fachdidaktischen Lehr- und Lernforschung.
Literature	Wird von der Praktikumslehrperson bestimmt.
Prerequisites / Notice	Findet in der Regel am Schluss der Ausbildung, vor Ablegung der Prüfungslektionen und vor der Lerneinheit „Lernwirksam unterrichten“ statt.
272-0205-01L	Examination Lesson I in Computer Science Simultaneous enrolment in "Examination Lesson II in Computer Science" (272-0205-02L) is compulsory.	O	1 credit	2P	J. Hromkovic, G. Serafini
Abstract	In the context of an examination lesson conducted and graded at a high school, the candidates provide evidence of the subject-matter-based and didactic skills they have acquired in the course of their training.
Learning objective	On the basis of a specified topic, the candidate shows that they are in a position - to develop and conduct teaching that is conducive to learning at high school level, substantiating it in terms of the subject-matter and from the didactic angle - to analyze the tuition they have given with regard to its strengths and weaknesses, and outline improvements.
Content	Die Studierenden erfahren das Lektionsthema in der Regel eine Woche vor dem Prüfungstermin. Von der zuständigen Lehrperson erhalten sie Informationen über den Wissensstand der zu unterrichtenden Klasse und können sie vor dem Prüfungstermin besuchen. Sie erstellen eine Vorbereitung gemäss Anleitung und reichen sie bis am Vortrag um 12 Uhr den beiden Prüfungsexperten ein. Die gehaltene Lektion wird kriteriumsbasiert beurteilt. Die Beurteilung umfasst auch die schriftliche Vorbereitung und eine mündliche Reflexion des Kandidaten/der Kandidatin über die gehaltene Lektion im Rahmen eines kurzen Kolloquiums.
Lecture notes	Dokument: Schriftliche Vorbereitung für Prüfungslektionen.
Prerequisites / Notice	Nach Abschluss der übrigen Ausbildung, vor der Lerneinheit „Lernwirksam unterrichten“.
272-0205-02L	Examination Lesson II in Computer Science Simultaneous enrolment in "Examination Lesson I in Computer Science" (272-0205-01L) is compulsory.	O	1 credit	2P	J. Hromkovic, G. Serafini
Abstract	In the context of an examination lesson conducted and graded at a high school, the candidates provide evidence of the subject-matter-based and didactic skills they have acquired in the course of their training.
Learning objective	On the basis of a specified topic, the candidate shows that they are in a position - to develop and conduct teaching that is conducive to learning at high school level, substantiating it in terms of the subject-matter and from the didactic angle - to analyze the tuition they have given with regard to its strengths and weaknesses, and outline improvements.
Content	Die Studierenden erfahren das Lektionsthema in der Regel eine Woche vor dem Prüfungstermin. Von der zuständigen Lehrperson erhalten sie Informationen über den Wissensstand der zu unterrichtenden Klasse und können sie vor dem Prüfungstermin besuchen. Sie erstellen eine Vorbereitung gemäss Anleitung und reichen sie bis am Vortag um 12 Uhr den beiden Prüfungsexperten ein. Die gehaltene Lektion wird kriteriumsbasiert beurteilt. Die Beurteilung umfasst auch die schriftliche Vorbereitung und eine mündliche Reflexion des Kandidaten/ der Kandidatin über die gehaltene Lektion im Rahmen eines kurzen Kolloquiums.
Lecture notes	Dokument: Schriftliche Vorbereitung für Prüfungslektionen.
Prerequisites / Notice	Nach Abschluss der übrigen Ausbildung, vor der Lerneinheit „Lernwirksam unterrichten“.

Spec. Courses in Resp. Subj. w/ Educ. Focus & Further Subj. Didactics
Number	Title	Type	ECTS	Hours	Lecturers
252-0408-00L	Cryptographic Protocols	W	6 credits	2V + 2U + 1A	M. Hirt, U. Maurer
Abstract	The course presents a selection of hot research topics in cryptography. The choice of topics varies and may include provable security, interactive proofs, zero-knowledge protocols, secret sharing, secure multi-party computation, e-voting, etc.
Learning objective	Indroduction to a very active research area with many gems and paradoxical results. Spark interest in fundamental problems.
Content	The course presents a selection of hot research topics in cryptography. The choice of topics varies and may include provable security, interactive proofs, zero-knowledge protocols, secret sharing, secure multi-party computation, e-voting, etc.
Lecture notes	the lecture notes are in German, but they are not required as the entire course material is documented also in other course material (in english).
Prerequisites / Notice	A basic understanding of fundamental cryptographic concepts (as taught for example in the course Information Security or in the course Cryptography Foundations) is useful, but not required.
272-0300-00L	Algorithmics for Hard Problems Does not take place this semester. This course d o e s n o t include the Mentored Work Specialised Courses with an Educational Focus in Computer Science A.	W	5 credits	2V + 1U + 1A
Abstract	This course unit looks into algorithmic approaches to the solving of hard problems, particularly with moderately exponential-time algorithms and parameterized algorithms. The seminar is accompanied by a comprehensive reflection upon the significance of the approaches presented for computer science tuition at high schools.
Learning objective	To systematically acquire an overview of the methods for solving hard problems. To get deeper knowledge of exact and parameterized algorithms.
Content	First, the concept of hardness of computation is introduced (repeated for the computer science students). Then some methods for solving hard problems are treated in a systematic way. For each algorithm design method, it is discussed what guarantees it can give and how we pay for the improved efficiency. A special focus lies on moderately exponential-time algorithms and parameterized algorithms.
Lecture notes	Unterlagen und Folien werden zur Verfügung gestellt.
Literature	J. Hromkovic: Algorithmics for Hard Problems, Springer 2004. R. Niedermeier: Invitation to Fixed-Parameter Algorithms, 2006. M. Cygan et al.: Parameterized Algorithms, 2015. F. Fomin, D. Kratsch: Exact Exponential Algorithms, 2010.
272-0302-00L	Approximation and Online Algorithms	W	5 credits	2V + 1U + 1A	H.‑J. Böckenhauer, D. Komm
Abstract	This lecture deals with approximative algorithms for hard optimization problems and algorithmic approaches for solving online problems as well as the limits of these approaches.
Learning objective	Get a systematic overview of different methods for designing approximative algorithms for hard optimization problems and online problems. Get to know methods for showing the limitations of these approaches.
Content	Approximation algorithms are one of the most succesful techniques to attack hard optimization problems. Here, we study the so-called approximation ratio, i.e., the ratio of the cost of the computed approximating solution and an optimal one (which is not computable efficiently). For an online problem, the whole instance is not known in advance, but it arrives pieceweise and for every such piece a corresponding part of the definite output must be given. The quality of an algorithm for such an online problem is measured by the competitive ratio, i.e., the ratio of the cost of the computed solution and the cost of an optimal solution that could be given if the whole input was known in advance. The contents of this lecture are - the classification of optimization problems by the reachable approximation ratio, - systematic methods to design approximation algorithms (e.g., greedy strategies, dynamic programming, linear programming relaxation), - methods to show non-approximability, - classic online problem like paging or scheduling problems and corresponding algorithms, - randomized online algorithms, - the design and analysis principles for online algorithms, and - limits of the competitive ratio and the advice complexity as a way to do a deeper analysis of the complexity of online problems.
Literature	The lecture is based on the following books: J. Hromkovic: Algorithmics for Hard Problems, Springer, 2004 D. Komm: An Introduction to Online Computation: Determinism, Randomization, Advice, Springer, 2016 Additional literature: A. Borodin, R. El-Yaniv: Online Computation and Competitive Analysis, Cambridge University Press, 1998
272-0400-00L	Mentored Work Specialised Courses in the Respective Subject with Educational Focus Computer Sc A	O	2 credits	4A	J. Hromkovic, G. Serafini
Abstract	In the mentored work on their subject specialisation, students link high-school and university aspects of the subject, thus strengthening their teaching competence with regard to curriculum decisions and the future development of the tuition. They compile texts under supervision that are directly comprehensible to the targeted readers - generally specialist-subject teachers at high-school level.
Learning objective	The aim is for the students - to familiarise themselves with a new topic by obtaining material and studying the sources, so that they can selectively extend their specialist competence in this way. - to independently develop a text on the topic, with special focus on its mathematical comprehensibility in respect of the level of knowledge of the targeted readership. - To try out different options for specialist further training in their profession.
Content	Thematische Schwerpunkte: Die mentorierte Arbeit in FV besteht in der Regel in einer Literaturarbeit über ein Thema, das einen Bezug zum gymnasialem Unterricht oder seiner Weiterentwicklung hat. Die Studierenden setzen darin Erkenntnisse aus den Vorlesungen in FV praktisch um. Lernformen: Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
Lecture notes	Eine Anleitung zur mentorierten Arbeit in FV wird zur Verfügung gestellt.
Literature	Die Literatur ist themenspezifisch. Sie muss je nach Situation selber beschafft werden oder wird zur Verfügung gestellt.
Prerequisites / Notice	Die Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.
272-0401-00L	Mentored Work Specialised Courses in the Respective Subject with Educational Focus Computer Sc B	O	2 credits	4A	J. Hromkovic, G. Serafini
Abstract	In the mentored work on their subject specialisation, students link high-school and university aspects of the subject, thus strengthening their teaching competence with regard to curriculum decisions and the future development of the tuition. They compile texts under supervision that are directly comprehensible to the targeted readers - generally specialist-subject teachers at high-school level.
Learning objective	The aim is for the students - to familiarise themselves with a new topic by obtaining material and studying the sources, so that they can selectively extend their specialist competence in this way. - to independently develop a text on the topic, with special focus on its mathematical comprehensibility in respect of the level of knowledge of the targeted readership. - To try out different options for specialist further training in their profession.
Content	Thematische Schwerpunkte: Die mentorierte Arbeit in FV besteht in der Regel in einer Literaturarbeit über ein Thema, das einen Bezug zum gymnasialem Unterricht oder seiner Weiterentwicklung hat. Die Studierenden setzen darin Erkenntnisse aus den Vorlesungen in FV praktisch um. Lernformen: Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
Lecture notes	Eine Anleitung zur mentorierten Arbeit in FV wird zur Verfügung gestellt.
Literature	Die Literatur ist themenspezifisch. Sie muss je nach Situation selber beschafft werden oder wird zur Verfügung gestellt.
Prerequisites / Notice	Die Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.
263-0007-00L	Advanced Systems Lab Only for master students, otherwise a special permission by the study administration of D-INFK is required.	W	8 credits	3V + 2U + 2A	M. Püschel, C. Zhang
Abstract	This course introduces the student to the foundations and state-of-the-art techniques in developing high performance software for mathematical functionality occurring in various fields in computer science. The focus is on optimizing for a single core and includes optimizing for the memory hierarchy, for special instruction sets, and the possible use of automatic performance tuning.
Learning objective	Software performance (i.e., runtime) arises through the complex interaction of algorithm, its implementation, the compiler used, and the microarchitecture the program is run on. The first goal of the course is to provide the student with an understanding of this "vertical" interaction, and hence software performance, for mathematical functionality. The second goal is to teach a systematic strategy how to use this knowledge to write fast software for numerical problems. This strategy will be trained in several homeworks and a semester-long group project.
Content	The fast evolution and increasing complexity of computing platforms pose a major challenge for developers of high performance software for engineering, science, and consumer applications: it becomes increasingly harder to harness the available computing power. Straightforward implementations may lose as much as one or two orders of magnitude in performance. On the other hand, creating optimal implementations requires the developer to have an understanding of algorithms, capabilities and limitations of compilers, and the target platform's architecture and microarchitecture. This interdisciplinary course introduces the student to the foundations and state-of-the-art techniques in high performance mathematical software development using important functionality such as matrix operations, transforms, filters, and others as examples. The course will explain how to optimize for the memory hierarchy, take advantage of special instruction sets, and other details of current processors that require optimization. The concept of automatic performance tuning is introduced. The focus is on optimization for a single core; thus, the course complements others on parallel and distributed computing. Finally a general strategy for performance analysis and optimization is introduced that the students will apply in group projects that accompany the course.
Prerequisites / Notice	Solid knowledge of the C programming language and matrix algebra.

Compulsory Elective Courses Further course offerings from the category Educational Science are listed under "Programme: Educational Science for Teaching Diploma and TC".
» see Compulsory Elective Courses Teaching Diploma

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