Computational Thinking

2018-2019

Course Objective

After attending this course you will be able:
- to analyze problems,
- to choose a right solution strategy or a combination of solution
strategies to solve problems,
- to create algorithms,
- to translate algorithms to a flowchart,
- to give an oral presentation of a project to peers,
- to reflect critically on your and others' work,
- to write a project report.

Course Content

There are various strategies to solve everyday problems. Often a problem
can be solved in different ways and there is not always a "best way".
However, sometimes one way is more efficient than the other, or you find
one approach easier or more pleasant than the other.
During the lectures of this course, you will be acquainted with
different
solution strategies (such as modeling, formulation, guess and check) and
algorithms (such as search algorithms, sorting algorithms and graph
algorithms) to solve problems. You will learn to solve problems by
reasoning and by using knowledge from other disciplines. In the
practical sessions, you will resolve various problems using the
different
solution strategies and algorithms that have been discussed in the
lectures. Since there are many ways to solve a problem, you will also
start thinking about developing algorithms yourself. In this course, we
encourage your problem solving and algorithmic thinking, as well as your
creative and innovative skills. At the end of the course, you will work
together with some other students in a group on a project. You will
conclude
the project with a short presentation.

Teaching Methods

Lectures, practical sessions, project, presentations, self study

Method of Assessment

The final grade is based on the practicum assignments, project
assignment, and the exam.

The first exam is a digital exam consisting of multiple choice
questions. The resit is a paper exam consisting of open questions. The
final grade is based on the practicum assignments, project assignment,
and the exam. For all these three parts separately, the average grade
should be at least a 5.5 to pass the course.

Entry Requirements

No specific knowledge is required to participate in this course.

Literature

Syllabus

Target Audience

1CS, 1IMM, 1LI

Additional Information

You should register in Canvas for a practicum group if you want to
participate in the practical sessions

Custom Course Registration

For this course, please enroll for the module, lecture, (interim)exam via VUnet. The faculty will enroll you for the other teaching methods. Students should (also) register in Canvas for a practicum group if they want to participate in the practical sessions.

Recommended background knowledge

Although no specific knowledge is required to participate in this course
a little mathematical understanding may be to your advantage.

General Information

Course Code X_400475
Credits 3 EC
Period P1
Course Level 100
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. A. Bhulai
Examiner dr. A. Bhulai
Teaching Staff dr. A. Bhulai

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Practical*

*You cannot select a group yourself for this teaching method, you will be placed in a group.

Target audiences

This course is also available as: