Algorithms, Probability and Computing

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This project was about creating software tools that allow instructors to create TeX documents for teaching purposes that contain interactive components. These interactive components allow students to give answers to clarifying questions and exercises, which are then immediately graded and dynamic feedback depending on the student's answer is given.

We have added interactive components to an old LaTeX document that has seen constant use for over a decade in the course Algorithms, Probability, and Computing. The document serves as a refresher for students about some basic concepts from probability theory that they are expected to know before taking this course. We believe that the interactive nature of the new document (with many clarifying questions and the possibility to receive immediate feedback) improves the learning experience greatly, of course also after the pandemic.

A set of seven reading assignments with interactive exercises was prepared for students in the CAS Applied Information Technology (which only exists since autumn 2020), with the goal of bringing their math background up to scratch. Feedback from students was extremely positive, and we plan to keep using them even after the pandemic.

We believe that the developed tools and the resulting interactive documents are not limited in their use to distance learning during a pandemic. There are many more use cases to be found in a variety of courses and situations.

Course Description

Name:
Algorithms, Probability, and Computing
Description:
Advanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction).
Objective:
Studying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory.
VVZ:
252-0209-00L
Department:
D-INFK
Level:
Bachelor Students
Size:
150

Course Description

Name:
Data Science
Description:
In this module, basic paradigms and techniques in working with data will be discussed, especially towards data security, managing data decentrally, and learning from data.
Objective:
Participants learn about some important computer science concepts necessary for data science. They understand some of these concepts in detail and see the mathematics behind them.
VVZ:
265-0101-00L
Department:
D-INFK
Level:
CAS in Applied Information Technology
Size:
50

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