195.080 Philosophy of Science
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, VU, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Online

Learning outcomes

After successful completion of the course, students are able to...

  • discuss the basic positions in the philosophy of science
  • understand the history of the debates about the content and form of computer science
  • connect the debates about what computer science is with the basic positions in the philosophy of science
  • explain their own research topic in terms of the philosophy of science
  • relate their own research with the paradigms of (computer) science;
  • describe the intellectual foundations of their research; and
  • explain some aspects of the applicability, limitations, and boundaries of their research results.

Subject of course

The lecturer of this course will be Prof. Matti Tedre / University of Eastern Finland.


Course Description:

This course looks at the philosophy of science from the viewpoint of computing.  In this course we pose concrete, commonsensical, specific, and well-defined questions about the nature of science, how science should be done and how it is done, and how can one best explain and understand the nature of science.  Our approach is a modern "naturalistic" approach to the philosophy of science in the sense that we are not going to speak much about how science should ideally be done, but we are going to focus on how it is actually done. As this course is aimed at people in computing disciplines, the examples will mostly be from the field of computing.  We will analyze science in terms of philosophy of science and sociology of scientific knowledge. We are also going to talk about the subject matter of science in the context of computing’s disciplinary debates - that is, what kinds of things do computer scientists study, how certain can we be about our results in computer science, and are our findings like "discoveries", "laws", or "products".

More specifically, the questions in this course include epistemological questions such as "What is scientific knowledge and (how) is it different from beliefs and assumptions?", "How can one differentiate between knowledge and beliefs in science?", "Can (computer) scientists know some things with certainty?", "Are there things in science that cannot be proven (with certainty)?", "What is progress in (computer) science?", "Are new algorithms or programs progress?", "How does new knowledge about computing become a part of commonly held knowledge about computing?", and "Are there laws in computer science?". We also discuss methodological questions specific to computing, such as "How do computer scientists work and how should computer scientists work?" and "Do (should) computers scientists prove formulas like mathematicians do, build things like engineers do, or test hypotheses like natural scientists do?". And we also talk about ontological questions such as "What kinds of things (if any) in computer science are universal, or objective, or timeless?".

Note that this course does not discuss the ethics of science, the philosophy of mind, artificial intelligence, or specialized topics in the philosophy of science.

For postgraduate (PhD) students this course offers perspectives into one's own research topic/field, helps to locate one's work within the larger enterprise of science as well as computer science, lays a philosophical foundation of one's work, and sheds light on one's own research paradigm (why do we work as we do, how do our results relate to the broader intellectual landscape, what do our results mean, what is the product of our work and research?).  This course also offers an overview of the variety of things computer scientists work with, helps to understand different kinds of research in computer science, and offers insight into the debates about what computer science is and what computer scientists do.

Teaching methods

The course is organized around individual on-line work, distance lectures, online workshop presentation of students' work, and final essay.  The online workshop is mandatory, as it includes presentation of one’s work to the audience as well as critical opposition of other participants’ reports.

Mode of examination


Additional information

This is a Fundamental PhD Course of the Faculty of Informatics for doctoral and master students. This course is related to methodologies.

Doctoral students in Computer Science have admission priority to this course.

The course will be held online.The access is

Join Zoom Meeting

Meeting ID: 661 4472 2583
Passcode: 941525

Further information will be announced in TUWEL as soon as possible.



Course dates

Fri10:00 - 12:0003.11.2023 Online - further information will be announced in TUWEL (LIVE)Lecture 1
Wed10:00 - 12:0008.11.2023 Online - further information will be announced in TUWEL (LIVE)Lecture 2
Tue08:00 - 10:0014.11.2023 Online - further information will be announced in TUWEL (LIVE)Lecture 3
Wed10:00 - 12:0022.11.2023 Online - further information will be announced in TUWEL (LIVE)Lecture 4
Wed10:00 - 12:0029.11.2023 Online - further information will be announced in TUWEL (LIVE)Lecture 5
Wed09:00 - 13:0013.12.2023 Online - further information will be announced in TUWEL (LIVE)Student presentations 1
Thu09:00 - 13:0014.12.2023 Online - further information will be announced in TUWEL (LIVE)Student presentations 2

Examination modalities

The grading will be based on the performance in the individual on-line work, online workshop presentation of the students' work and the quality of the final essay.

Course registration

Begin End Deregistration end
04.10.2023 15:00 03.11.2023 18:00

Registration modalities

Please register in TISS.


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784 175 Business Informatics Mandatory elective
784 939 Business Engineering and Computer Science Mandatory elective
786 175 Business Informatics Mandatory elective
786 881 Computer Sciences Mandatory elective
791 881 Computer Sciences Mandatory elective
791 884 Subject: Informatics und Informatics Management Mandatory elective
PhD TU Wien Informatics Doctoral School Not specified


Textbook: Tedre, Matti (2014) The Science of Computing: Shaping a Discipline.  Taylor & Francis / CRC Press.

Supplementary reading: Denning, Peter J. & Tedre, M. (2019) Computational Thinking.  The MIT Press.

Other literature (journal articles) is presented over the course.


  • Attendance Required!