Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice (e.g. cancellation of on-site teaching and conversion to online exams). Register for courses/exams via u:space, find out about the current status on u:find and on the moodle learning platform.

Further information about on-site teaching and access tests can be found at https://studieren.univie.ac.at/en/info.

Warning! The directory is not yet complete and will be amended until the beginning of the term.

180148 VO+UE Tools in Cognitive Science I: Computation, Computer-aided Methodologies and Problem Solving (2021W)

5.00 ECTS (3.00 SWS), SPL 18 - Philosophie
Continuous assessment of course work
Fr 08.10. 16:45-20:00 Hörsaal 2i NIG 2.Stock


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 25 participants
Language: English


Classes (iCal) - next class is marked with N

Friday 15.10. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 22.10. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 05.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 12.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 19.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 26.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 03.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 10.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 17.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 07.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 14.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 21.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Friday 28.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock


Aims, contents and method of the course

Different branches of digital sciences and computer science such as artificial intelligence, robotics, computational cognitive modelling, human-computer interaction, digital ethics, human-centric computing, etc., can be considered important (and even core) research fields of cognitive science. Analytical thinking and programming play fundamental roles in all these fields. Moreover, beyond their application in digital sciences and computer science, analytical thinking and programming are also widely used in other branches of cognitive science, such as the development of computer-based empirical experiments, data collection, data representation, data analysis, data visualisation, etc. Therefore, acquiring basic and working knowledge of analytical thinking and programming is essential for all cognitive science students.

This course introduces students to:
• basic concepts and challenges of digital sciences
• basic concepts of computation
• analytical, systemic and algorithmic thinking
• applied problem-solving skills
• working knowledge of programming (using Python), skills related to programming and application of programming in cognitive science
• practical skills related to design, implementation, and evaluation of computer-based empirical experiments, data collection, representation, analysis, visualisation, etc.
• basic understanding of the role of computer science in cognitive science
• basic understanding of human-centric approaches in computer science as well as cognitive science
• basic understanding of ethics and accountability in computer science as well as cognitive science

____ COVID 19 Updates ____

Considering the current developments related to COVID-19, the course will be held partially (or entirely) online (depending on the situation).

The decisions/updates and detailed instructions will be announced via Moodle platform or email.

Most of (or maybe all of) the communications, lectures, assignments, presentations, group-works, projects, evaluations, and exams will be done online.

– Course mode:
–– Mixed/hybrid (online + in-person) or fully online

– Teaching/learning methods:
– – Virtual/in-person synchronous course units,
– – Self-study with literature and online resources,
– – Virtual/in-person group-works,
– – Online/in-person exams,
– – Online/in-person presentations,
– – Virtual/in-person coaching/supervision sessions (if needed)
– – ...

– Students are expected to participate in announced online/in-person sessions, online/in-person presentations, online/in-person exams, etc.
– Students are expected to construct private virtual communication means for their virtual group works.
– Students are expected to regularly check their emails as well as the course Moodle environment.
– Students are expected to follow all detailed instructions related to remote/in-person teaching.
– The assessments will be based on the regular assessment plans.

Assessment and permitted materials

The course will be graded on a basis of 100 points in total:• 100-87 points: Excellent (1)• 86-75 points: Good (2)• 74-63 points: Satisfactory (3)• 62-50 points: Sufficient (4)• 49-0 points: Unsatisfactory (5) (fail)

Minimum requirements and assessment criteria

Assessment criteria:• 10% Active participation• 25% Homework assignments (via Moodle)• 20% Presentation (debriefing) of homework assignments• 15% In-class quizzes• 15% Final Exam• 15% Final Project• A positive score (>50%) in each of the above criteria is required for passing the course.• Regular participation in at least 90% of sessions is obligatory.

Examination topics

Exam questions will be based on what we discuss in class, the readings and the homework assignments.

Reading list

https://www.python.org/doc/• Further readings will be announced in the course

Association in the course directory

Last modified: We 01.09.2021 11:08