ADVANCED MATHEMATICS AND COMPUTING B - 2022/3

Module Overview

The module is designed to further develop and extend the critical thinking skills and problem solving skills of the students beyond that which would normally be acquired in an A-level (or comparable level) course. From a theoretical perspective, students will study pure mathematics, together with vectors and matrices and their applications to data analysis. The practical computing aspect of the module introduces programming with Python and brings together a variety techniques in data processing, analysis, modelling and probability and statistics. Students may further advance their problem solving skills and apply some of the theory within a variety of interesting and challenging contexts.

Module provider

Sustainability, Civil & Env Engineering

Module Leader

HARRISON Richard (CS & EE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 3

Module cap (Maximum number of students): 50

Module Availability

Semester 2

Prerequisites / Co-requisites

N/A

Module content

Topics in pure mathematics, applied mathematics and computational methods, including the application of probability, statistics and matrices. Data processing techniques and visualisation, computational (numerical) modelling and problem solving.

Assessment pattern

Alternative Assessment

Not applicable

Assessment Strategy

  

The module has two equally weighted (50%) assessment components reflecting the balance of the mathematics and computing elements.

Mathematics

The assessment strategy for the mathematics components is designed to provide students with the opportunity to demonstrate

(i) their knowledge of relatively advanced mathematical concepts and rules

(ii) the development of critical thinking skills in interpreting and solving a variety of problems, in different contexts

(iii) an appropriate and accurate application of the mathematical techniques to a given problem.

Continuous in-semester assessment: students will attempt 5 x sets of online questions at regular intervals or at such a time that a particular topic has been covered. The questions will be MCQ/short answer. 

End of module examination: students will attempt written questions covering academic content/scenarios not previously assessed in the continuous assessment. The end of module exam will examine all learning objectives for the mathematics component.

Computing

The assessment strategy for the computing components is designed to provide students with an opportunity to demonstrate

(i) they have grasped basic programming and processing techniques in Python

(ii) they have developed critical thinking skills in interpreting and solving a variety of problems, in different contexts

(iii) they can apply simple processing strategies/algorithms

(iv) they can select and apply appropriate mathematical methods to a particular computational problem.

Continuous in-semester assessment: students will attempt 5 x sets of online questions at regular intervals or at such a time that a particular topic has been covered. The questions will be MCQ/short answer. 

Coursework task: students will carry out a coursework task covering multiple learning objectives based on and extending the work in the lab worksheets. There will be a practical submission comprising Python code files together with a short report. Time guidance for coursework is 10 hours. The single coursework component will assess all learning objectives not already assessed in the continuous assessment.

Formative ‘assessment’ is ongoing throughout the semester through work on tutorial questions in mathematics and laboratory worksheets.

Feedback from formative assessment is provided orally on a one-to-one basis and to the whole group in tutorial/problems classes. Fully worked solutions to mathematics tutorial problems will be provided via SurreyLearn.

Feedback will be provided on the continuous online assessment via Surreylearn. 

 

Module aims

• Reinforce and extend existing mathematical knowledge.
• Develop competency in applying some relatively advanced mathematical concepts.
• Develop critical thinking and problem solving skills in mathematical and computational processes.

Learning outcomes

Methods of Teaching / Learning

Mathematics component: The teaching and learning strategy is designed to familiarise students with mathematical concepts and techniques, supported by extensive use of examples and applications; students are engaged in the solution of problems and application of techniques in tutorials/problems classes.

The learning and teaching methods include:

• Lectures (in-situ delivery)to introduce new concepts and techniques and provide illustrative examples and applications.

• Guided self-study to cover certain topics, in order to develop students’ independent learning skills.

• Problem sheets of examples for technique selection and skills development.

• Tutorial classes (in-situ delivery) for the development of skills in problem solving, using problems sheets. Assistance is given both at individual level, and for the group on common areas of difficulty.

• Independent learning

Computing component:

The teaching and learning strategy is designed to facilitate students practical and critical thinking skills development in a challenging problem solving context involving a variety of concepts from mathematics, statistics, data analysis, modelling and computing. The processes, concepts and techniques, are reinforced in a “hands on” manner using dedicated laboratory worksheets designed to be used at the computer. Students are engaged in practical and theoretical tasks as well as critical thinking/problem solving as they work through each laboratory worksheet.

• Computer laboratory practical (in-situ delivery) 


• Computer laboratory tutorial/practical (in-situ delivery) 


• Support sessions (in-situ delivery) 


• Independent learning and completing lab worksheets

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.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENG0020

Other information

The module may be delivered fully online, in-situ or as a hybrid such as online mathematics and lab based computing components.

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 2022/3 academic year.