COMP11012
Foundation in Computer Science-Computational Thinking
10
Semester 2
Undergraduate
Level 1
Sean Bechhofer
Unit coordinator
Uli Sattler
Unit coordinator
Andrea Schalk
Unit coordinator
Department of Computer Science
1
FHEQ level (Framework for Higher Education Qualifications) ' Foundation '
European Credit Transfer & Accumulation System Rating : 5.0
<p>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.</p>
<div> 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.</div><div> </div><div> The unit will also introduce the notion of computational complexity and some discussion of the limitations of computation.</div><div> </div><div> 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. </div><div> </div>
<p>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.</p>
<div> <p> </p><p>On the successful completion of the course, students will be able to: <span style="white-space:pre"> </span>Developed<span style="white-space:pre"> </span>Assessed</p> <table border="1" cellpadding="1" cellspacing="1" style="width: 500px"> <tbody> <tr> <td> ILO 1</td> <td> Decompose a problem into a series of ordered steps</td> <td> Yes</td> <td> Yes</td> </tr> <tr> <td> ILO 2</td> <td> Apply techniques such as decomposition, abstraction and generalisation to problems </td> <td> Yes</td> <td> Yes</td> </tr> <tr> <td> ILO 3</td> <td> Describe computational complexity in an informal way</td> <td> Yes</td> <td> Yes</td> </tr> <tr> <td> ILO 4</td> <td> Explain how self-referential problems relate to the limits of computation. </td> <td> Yes</td> <td> Yes</td> </tr> </tbody> </table></div><div> </div>
<div> Weekly one hour lectures introducing key concepts and topics. These will be accompanied by online materials (video, podcasts) for self-study. </div><div> </div><div> 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. </div><div> </div><div> 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. </div><div> </div><div> The final exam will be online. </div><div> </div>
0
Other
10%
1
Written exam
50%
8
Practical skills assessment
40%
N
<p>Algorithmics: The spirit of computing. David Harel and Yishai Feldman (Springer), 1987.</p><p> </p><p>Godel, Escher, Bach: An Eternal Golden Braid. Douglas R. Hofstadter. (Basic Books) 1999.</p><p><span style="font-size:11pt"><span style="font-size:14px">The power of computational thinking : games, magic and puzzles to help you become a computational thinker. Paul Curzon and Peter McOwan. World Scientific Publishing, 2017</span>. </span></p><p> </p><p>For Information and advice on Link2Lists reading list software, see: </p><p>http://www.library.manchester.ac.uk/academicsupport/informationandadviceonlink2listsreadinglistsoftware/</p><p> </p><p> </p><p> </p><p> </p>
Assessment written exam
2
Lectures
10
Practical classes & workshops
12
0
76