This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.
Undergraduate Handbook 2010-2011 (archived)
Module COMP1051: Computational Thinking
Department: Computer Science
COMP1051: Computational Thinking
| Type | Level | Credits | Availability | Module Cap | Location |
|---|---|---|---|---|---|
| Open | 1 | 20 | Available in 2010/2011 | None. | Durham |
Pre-requisites
- None.
Corequisites
- None.
Excluded Combinations
- None.
Aims
- To introduce students to the skills of computational thinking.
- To illustrate the use of computational thinking by drawing on concepts and methods fundamental to computing and computation.
- To show how computational thinking pervades science and impacts upon cutting-edge inter-disciplinary research.
Content
- History of computation and computing.
- Notions of computers and computation.
- What can we measure?
- Solving problems.
- Techniques for problem solving: recursion; reduction; embedding; transformation; simulation.
- The nature of 'wicked problems' (ill-structured problems) and programming.
- Abstraction and decomposition.
- System design and simplicity.
- Prevention, detection, and recovery from worst-case scenarios through redundancy, damage containment and error correction.
- Modularization.
- Deadlock and races.
Learning Outcomes
Subject-specific Knowledge
- Students will gain an awareness of some fundamental concepts and methods that are specific to and pervasive within computing.
- Students will understand how computational thinking impacts upon current inter-disciplinary research.
Subject-specific Skills
- Students will be able to apply the concepts and methods of computational thinking to specific scenarios within computing.
Key Skills
- Students will gain a variety of problem-solving skills.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
- Practicals provide the practice and support in applying the methods learned to specific scenarios, as well as active engagement and feedback to the learning process.
- Summative coursework provides an incentive for students to consolidate their learning as the module progresses. It serves as an aid to the correct development of knowledge and skills, as well as to the development of students' awareness of standards required.
- The end of year examination assesses the knowledge acquired by students as well as their ability to apply this knowledge.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 40 | 2 per week | 1 hour | 40 | |
| Practicals | 20 | 1 per week | 2 hours | 40 | Yes |
| Preparation and Reading | 120 | ||||
| Total | 200 |
Summative Assessment
| Component | Component Weighting | Element | Length/Duration | Element Weighting | Resit Opportunity |
|---|---|---|---|---|---|
| Examination | 66% | Examination | 2 hours | 100% | Yes |
| Coursework | 34% | Practical work | 100% | Yes |
Formative Assessment
Example exercises are given throughout the course. In addition, a collection paper is sat during the year.
Students who do not attend monitored activities shown under Teaching Methods
and Learning Hours, or who fail to complete the summative or formative
assessment(s) specified above, may be subject to the Academic Progress
procedures defined in the University's General Regulation V, and may be
required to leave the University.