Skip to navigation | Skip to main content | Skip to footer
Menu
Menu

COMP11012 Foundation in Computer Science-Computational Thinking syllabus 2021-2022

COMP11012 Foundation in Computer Science-Computational Thinking

Level 1
Credits: 10
Enrolled students: 62

Course leader: Sean Bechhofer


Additional staff: view all staff

Assessment methods

  • 10% Other
  • 50% Written exam
  • 40% Practical skills assessment
Timetable
SemesterEventLocationDayTimeGroup
Sem 2 w20-27,31,33-34 Lecture Sackville Street F47 Mon 14:00 - 15:00 -
Sem 2 w20,22,24,26,31,33 Workshop IT407 Fri 10:00 - 12:00 -

Overview

Computational Thinking is a term used to describe the processes that can be used to develop solutions for complex problems. It uses a number of approaches to decompose and analyse problems, presenting them in ways that can then be effectively carried out by machines or humans. Key concepts introduced will include decomposition, abstraction, generalisation and algorithms.
 
The unit will also introduce the notion of computational complexity and some discussion of the limitations of computation.
 
These are key themes in Computer Science, but this should not be seen as a unit on coding or programming. Computational Thinking can be applied in scenarios which are not just about code development. The unit is thus primarily targeted at those on the Computer Science pathway, but should also be of interest to other Foundation Year students. 
 

Aims

The unit aims to introduce students to Computational Thinking: the thought processes involved in formulating a problem and expressing its solution(s) in such a way that a computer — human or machine — can effectively carry out.

Teaching methods

Weekly one hour lectures introducing key concepts and topics. These will be accompanied by online materials (video, podcasts) for self-study. 
 
Six workshops will target problems and exercises to be completed in groups with GTA support. Workshops will be supported by online materials, discussion boards and fora. 
 
Practical assignments will be largely group work. A proportion of the assessment credit will be based on individual contributions to the group and engagement in online discussion. 
 
The final exam will be online. 
 

Study hours

  • Lectures (10 hours)
  • Practical classes & workshops (12 hours)

Learning outcomes

On successful completion of this unit, a student will be able to:

On the successful completion of the course, students will be able to:                Developed Assessed

ILO 1 Decompose a problem into a series of ordered steps Yes Yes
ILO 2 Apply techniques such as decomposition, abstraction and generalisation to problems  Yes Yes
ILO 3 Describe computational complexity in an informal way Yes Yes
ILO 4 Explain how self-referential problems relate to the limits of computation.  Yes Yes
 

Reading list

TitleAuthorISBNPublisherYear
The power of computational thinking : games, magic and puzzles to help you become a computational thinker Curzon, Paul,9781786341853; 1786341859World Scientific Publishing Europe Ltd; ProQuest Ebook Central[2017]
Gòˆdel, Escher, Bach : an eternal golden braid Hofstadter, Douglas R.,0855277572; 9780855277574Harvester Press1979.
Algorithmics : the spirit of computing Harel, David,9783642441356Springer2012
Computational thinking : a beginner's guide to problem-solving and programming Beecher, Karl ,9781780173658 EB; 9781523116874 (Unspecified); 9781780173665 (Electronic Book); 9781780173672 (Electronic Book)Chartered Institute for IT2017.