Computer Science: Computer Science and Education

Master

The specialisation Computer Science and Education is a joint programme offered in collaboration with the Leiden University Graduate School of Teaching (ICLON)). It prepares students for a career as a computer science teacher and results in the teacher qualification (eerstegraads-lesbevoegdheid) required for teaching in Dutch secondary schools. For teaching in bilingual and international schools the World Teachers Programme (WTP) is offered.

In addition to the Computer Science entry requirements proof of Dutch language proficiency is required. Applicants who do not hold a Dutch secondary school diploma (VWO-diploma) will have to take a Dutch language test.

Curriculum

The two-year Computer Science and Education programme consists of:

Year 1

at least 30 EC of level-500 Specialisation courses and seminars in Computer Science to be selected in correspondence with the chosen topic of the Master's Thesis Research Project in Computer Science (30 EC) and including the mandatory course Psychology of Programming.
a Master's Thesis Research Project in Computer Science (30 EC) in one of the LIACS research groups.

Year 2

the Education component (60 EC).

More information

For specific questions about programme content, curriculum choices and/or study planning, please contact the Computer Science study advisor/education coordinator and/or ICLON study advisor Toke Egberts MSc.

Specialisation courses and seminars Computer Science

Important announcements:

Due to Covid-19 the following courses are cancelled:
- Better Science for Computer Scientists (3 EC)
- Competitive Programming (6 EC)
- Information Retrieval and Text Analytics (6 EC)
- Information Theoretic Data Mining (6 EC)
Students can choose an alternative course from the Computer Science and Education list of specialisation courses and seminars (see below).

Vak	EC	Semester 1	Semester 2
Fall semester
Advanced Data Management for Data Analysis	6
Advances in Data Mining	6
Automated Machine Learning	6
Better Science for Computer Scientists - CANCELLED	3
Computational Creativity	6
Complex Networks (BM)	6
Computational Models and Semantics	6
Computational Molecular Biology	6
Distributed Data Processing Systems	6
Evolutionary Algorithms	6
Foundations of Software Testing	6
High Performance Computing I	6
Information Theoretic Data Mining - CANCELLED	6
Introduction to Deep Learning	6
Introduction to Machine Learning	6
Multimedia Systems	6
Seminar Advanced Deep Reinforcement Learning	6
Seminar Swarm-based Computation with Applications in Bioinformatics	6
Social Network Analysis for Computer Scientists	6
Software Development and Product Management	6
Quantum Algorithms	6
Text Mining	6
Urban Computing	6
Spring semester
Advances in Deep Learning	6
Applied Quantum Algorithms	6
Audio Processing and Indexing	6
Bio-Modeling	6
Competitive Programming - CANCELLED	6
Concurrency and Causality	6
Cloud Computing	6
Embedded Systems and Software	6
High Performance Computing II	6
Image Analysis with Applications in Microscopy	6
Information Retrieval and Text Analytics - CANCELLED	6
Modern Game AI Algorithms	6
Multicriteria Optimization and Decision Analysis	6
Multimedia Information Retrieval	6
Psychology of Programming	6
Quantum Computing	3
Reinforcement Learning	6
Robotics	6
Seminar Combinatorial Algorithms	6
Software Verification	6
Sports Data Science	6

Research components Computer Science

Vak	EC	Semester 1	Semester 2
Master Class	0
Master's Thesis Research Project (CS & SCS/EDU)	30

Education component

Outline of the Education programme:

Educational theory (5 EC)
learning and instruction 1 (5 EC)
learning and instruction 2 (3 EC)
teaching Methodology 1(5 EC)
Teaching Methodology 2 ( 5 EC)
Design Research (7 EC)
Teaching Practice 1 (15 EC)
Teaching Practice 2 (15 EC)

For students who passed the Minor Education (30 EC) during their Bachelor's, the programme consists of the following:

Learning and instruction 2 (3 EC)
Teachinge Methodology 2 (5 EC)
Design Research (7 EC)
Teaching practice 2 (15 EC)

Course levels

Level 100
Introductory course, builds upon the level of the final pre-university education examination.
Characteristics: teaching based on material in textbook or syllabus, pedagogically structured, with
practice material and mock examinations; supervised workgroups; emphasis on study material and
examples in lectures.
Level 200
Course of an introductory nature, no specific prior knowledge but experience of independent
study expected.
Characteristics: textbooks or other study material of a more or less introductory nature; lectures, e.g. in
the form of capita selecta; independent study of the material is expected.
Level 300
Advanced course (entry requirement level 100 or 200).
Characteristics: textbooks that have not necessarily been written for educational purposes; independent
study of the examination material; in examinations independent application of the study material to
new problems.
Level 400
Specialised course (entry requirement level 200 or 300).
Characteristics: alongside a textbook, use of specialist literature (scientific articles); assessment in the
form of limited research, a lecture or a written paper. Courses at this level can, to a certain extent, also
be on the master’s curriculum.
Level 500 Course with an academic focus (entry requirement: the student has been admitted to a
master’s programme; preparatory course at level 300 or 400 has been followed).
Characteristics: study of advanced specialised scientific literature intended for researchers; focus of the
examination is solving a problem in a lecture and/or paper or own research, following independent
critical assessment of the material.
Level 600
Very specialised course (entry requirement level 400 or 500)
Characteristics: current scientific articles; latest scientific developments; independent contribution (dissertation research) dealing with an as yet unsolved problem, with verbal presentation.

The classification is based on the Framework Document Leiden Register of Study Programmes.