DM881: Theory of Science for Informatics

Study Board of Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N340089112, N340089102
Censorship: Second examiner: None
Grading: Pass/Fail
Offered in: Odense
Offered in: Spring
Level: Master

STADS ID (UVA): N340089101
ECTS value: 5

Date of Approval: 08-10-2020


Duration: 1 semester

Version: Approved - active

Comment

New course spring 2021.
Will be taught in parallel to BB855: Philosophy of science for biologists (5 ECTS) with joint sessions, students can only sign up for either BB855 or DM881.

Entry requirements

None.

Academic preconditions

Students taking the course are recommended to have a fundamental understanding of different areas of computer science, e.g., by having obtained a bachelor's degree in computer science or having passed the major part of the courses of a BSc curriculum in computer science.

Course introduction

The aim of the course is to enable the student to reflect on the knowledge of the field of Computer Science, which is important in regard to identify scientific issues.
The course builds on the knowledge acquired in the courses of the BSc curriculum in computer science, and gives an academic basis for doing a Master's dissertation in computer science that draws on topics of theory of science.

In relation to the competence profile of the degree it is the explicit focus of the course to:
  • Give the competence to reflect on the knowledge of the field of Computer Science and to identify scientific issues.
  • Give skills to elucidate hypotheses on a qualified theoretical background and critically refer to own and others' research results and scientific models.
  • Give knowledge and understanding of how scientific knowledge is obtained and modeled through an interplay between theory and experiment

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:

  • Communicate a selected topic of theory of science in writing.
  • Be able to select and present a topic of theory of science within the course syllabus.
  • Be able to use the terminology from the course correctly.
  • Be able to reproduce, and relate to, the course's texts of theory of science.


Content

The following main topics are contained in the course:
  • theory of science in general (e.g., relationship between theory and observation, experiments, inductivism, falsificationism, theories as structures, methodical changes in method, Bayesian approach, experimentalism, laws, realism and anti-realism)
  • philosophy of computer science (e.g., information, models, abstraction, implementation, epistemological status of computer science, ethical questions, metaphysical questions)

Literature

See Blackboard for syllabus lists and additional literature references.

Examination regulations

Prerequisites for participating in the exam a)

Timing

Spring

Tests

Presentation of one or more topics in class, as assigned by the instructor

EKA

N340089112

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

Prepared presentation material (handouts, slides) allowed, a closer description of the exam rules will be posted under 'Course Information' on Blackboard.

ECTS value

0

Additional information

The prerequisite examination is a prerequisite for participation in exam element a).

Exam element a)

Timing

Spring

Prerequisites

Type Prerequisite name Prerequisite course
Examination part Prerequisites for participating in the exam a) N340089101, DM881: Theory of Science for Informatics

Tests

Project Report

EKA

N340089102

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Student Identification Card

Language

Normally, the same as teaching language

Examination aids

Allowed, a closer description of the exam rules will be posted under 'Course Information' on Blackboard.

ECTS value

5

Additional information

The examination form for re-examination may be different from the exam form at the regular exam.

Indicative number of lessons

24 hours per semester

Teaching Method

The teaching method is based on three phase model.
  • Intro phase: 6 hours
  • Training phase: 18 hours, hereof tutorials: 18 hours
Activities during the study phase:
  • Self study of various parts of the course material.
  • Reflection upon the intro and training sections.
  • Preparation of presentations for tutorials

Teacher responsible

Name E-mail Department
Arthur Zimek zimek@imada.sdu.dk Institut for Matematik og Datalogi, Datalogi, Datavidenskab & Statistik

Timetable

Administrative Unit

Institut for Matematik og Datalogi (datalogi, fiktiv)

Team at Registration & Legality

NAT

Recommended course of study

Profile Programme Semester Period