FOUNDATIONS OF COMPUTING II - 2020/1
Module code: COM1033
In light of the Covid-19 pandemic the University revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. Further information on changes made to modules during the 2020/21 academic year can be found here: https://www.surrey.ac.uk/coronavirus/course-changes-old
Due to the volume of changes made during the 2020/21 academic year this means that some information within the programme and module catalogue had been amended. Please ensure that you are viewing your modules alongside the module changes page. If you have any queries you are invited to contact the relevant Programme Leader or Academic Hive with any questions relating to the information available.
The course builds upon COM1026, Foundations of Computing, and introduces the key concepts of differentiation/integration of a function and their applications. It also provides a short introduction to solving linear equations using matrix manipulation and a primer on statistics.
LI Yunpeng (Computer Sci)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 4
JACs code: I100
Module cap (Maximum number of students): N/A
Overall student workload
Lecture Hours: 33
Laboratory Hours: 11
Prerequisites / Co-requisites
Indicative content includes:
- Limits and continuity
- What is a derivative
- Derivatives of functions
- Optimisation problems
- Definite integrals of simple functions
- Fundamental theorem of calculus
- Numerical methods of integration and their application.
- Linear equations and matrices:
- Solve linear equations systematically
- Matrices and matrix manipulation
- A primer on statistics:
- Describing and summarising data
- Samples and populations
- Significance testing
|Assessment type||Unit of assessment||Weighting|
|Coursework||COURSEWORK I INDIVIDUAL||40|
|Examination||2HR UNSEEN EXAM||60|
The assessment strategy is designed to provide students with the opportunity to demonstrate that they have achieved the module learning outcomes.
Thus, the summative assessment for this module consists of:
· An individual coursework on differentiation/ integration of functions and matrix manipulation. This addresses LO1, LO2, LO3, LO4, LO6.
· A 2h unseen examination on the whole course content. This addresses all learning outcomes.
The individual coursework will be due around week 8.. The exam takes place at the end of the semester during the exam period.
Formative assessment and feedback
EVS handsets may be used extensively in the lectures, with each lecture consisting of a number of slides explaining the theory followed by a number of slides gauging the students’ understanding. The answers are discussed when necessary, eg if a high proportion (more than 25%) of the students get the answer wrong. Individual formative feedback will also be given during the lab sessions and as part of the summative assessment.
- This module aims to deepen the students' understanding of mathematical functions and their applications, and demonstrate how these are relevant to the discipline. Octave will be used practically to illustrate how functions can be differentiated and integrated. The module also aims to show how sets of linear equations can be solved by simple matrix manipulations. Finally, students will gain insights into how statistics can be used to summarise and interpret data.
|1||Differentiate and integrate some elementary functions, including polynomials, exponential and trigonometric functions;||KCT|
|2||Apply differentiation, e.g. to solve optimisation problems||KCT|
|3||Apply integration, e.g. to find the mean value of function and the area between curves||KCT|
|4||Solve linear equations using matrix manipulations||KCT|
|5||Understand and apply simple statistical methods;||KCT|
|6||Translate real-world problems into mathematical expressions to be solved||CPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
- Help students be confident in manipulating mathematical functions
- Provide opportunities to explore mathematical concepts, like differentiation, using Octave
- Practise solving real-world problems by translating them into mathematical expressions
- Enable students to interpret data using simple statistical techniques
The learning and teaching methods include:
- Lectures (11 weeks at 2h) using EVS handsets to gauge the students’ understanding
- Laboratory session (10 weeks at 2h)
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: COM1033
Programmes this module appears in
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.