PROGRAMME SPECIFICATION FOR AWARDS MADE BY THE UNIVERSITY OF EAST ANGLIA

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1 Learning, Teaching and Quality Committee PROGRAMME SPECIFICATION FOR AWARDS MADE BY THE UNIVERSITY OF EAST ANGLIA SECTION A: SESSION: 2012 to 2013 A1 Course Name Computing Science A2 Final Award MSc (e.g. BA/BSc(Hons)/ MA/MSc etc) A3 UEA Course Code(s) T1G (full-time) T2G (part-time) A4 UCAS Course Code(s) T1G400101/T2G A5 Professional Award None (if any) A6 School of Studies School of Computing Sciences SECTION B: SUMMARY OF COURSE STRUCTURE AND FEATURES B1 Summary e.g. General statement about course structure, including special features such as placement opportunities, whether these are compulsory or optional; fieldwork; year abroad. Include any cross references to other relevant information such as Student Handbook and/or School/Faculty website. The topics covered in this course all fall within and where appropriate extend the body of knowledge outlined in the Benchmarking Standards for Taught Masters Degrees in Computing set in 2008 by the Council of Professors and Heads of Computing (CPHC) and the British Computer Society (BCS), and the core skills in the IEEE Computer Society and ACM Joint Task Force on Year 2001 Model Curricula for Computing: CS-2001 and its latest interim Revision CS The credit framework follows the joint Credit Guidelines for HE Qualifications in England, Wales and Northern Ireland set in November Rationale The increasing breadth of computing can exploit and benefit from skills learned in other disciplines, which may not be a part of a conventional computing science education. The expansion of the discipline of computing requires a wider range of intellectual perspectives, techniques and competencies. There is a substantial demand from industry and society for computer scientists and software engineers, particularly with skills in other disciplines. Philosophy The programme philosophy is to broaden students intellectual outlook by building on their knowledge, experience and maturity to give them a comprehensive overview of core computing disciplines combined with an in-depth treatment of salient modern computing technologies and practices. Specialisations complement, broaden and deepen that knowledge, and integrate computing skills with their previous education and experience. This makes considerable intellectual demands on students, most obviously in the manner and pace of teaching that relies heavily on the additional intellectual and emotional maturity

2 expected of a graduate. Structure of the course The course is broadly divided into three parts: 1. Students take 80 M-level credits of compulsory (and Option Range A) modules which are primarily designed to provide a coherent technical foundation in computing systems, internet technologies and contemporary software applications development, and an intensive training for developing their transferable skills in research, technical writing and presentation, and increasing their awareness in computing professional ethical and legal issues. 2. Students normally take 40 credits of optional modules allowing them to develop academically coherent areas of expertise, building on the foundation modules. 3. The dissertation project (60 M-level credits) draws on material from many taught modules and beyond; students are required to integrate a wide range of knowledge and skills to carry out their project work and then write up an MSc dissertation. Part-time students follow a similar structure, except that the modules are spread over two years. Students should discuss with their adviser to devise a specific study plan for two years. The assessment modes of each module are published in the University Course Catalogue and on the CMP Teaching Web pages and students are normally notified of a more precise schedule of coursework prior to the module (and at the latest at an initial lecture). As much of this information as can be made available in the School s Taught MSc Handbook, and supplemental information specific to the Master of Science, is issued to each student in September, when they arrive. SECTION C: EDUCATIONAL AIMS AND OUTCOMES C1 Educational Aims of the Programme (Include any distinctive/innovative features/route pathways) The MSc Computing Science is normally a 12 month full-time course, but may be followed part-time over 2 years. It is designed for graduates of disciplines other than Computing Science. Its aims are to: Provide a high quality masters level programme which combines intellectual challenge and relevance to current issues in Computing Sciences; Provide a programme that builds on the body of knowledge identified in the Benchmarking Standards for Taught Masters Degrees in Computing set in 2008 by CPHC/BCS, and is consistent with the benchmarking standards for Computing produced by the Quality Assurance Agency for Higher Education, and the advanced curriculum specified in the joint ACM/IEEE Computer Society document Computing Curricula 2001 and its updates in Review key computing topics, focussing in depth on issues relevant to current computing theory and practice. Maintain the central role of research to inform teaching and to engage students in the critical review of new developments in the field. Further develop students intellectual skills in reasoning, problem-solving, self-expression, independent research and team work, and thereby enable them to deal systematically and creatively with complex issues in their future profession. Build students up a good understanding of social, ethical and legal issues in computing fields, further encourage their commitment to computing profession, and prepare students for employment in careers that require them to exercise initiative and professional judgement in unfamiliar situations. 2

3 C2 Course Outcomes C2(i) Knowledge and understanding a Systematic understanding of computing and computer systems organisation. b Conceptual knowledge of net-centric computing as a model of contemporary systems development. c Methods for problem analysis, software design, implementation, and evaluation especially the integration of a range of techniques to solve practical problems. d Critical assessment and understanding of relevant academic, commercial and marketing literature. e Recognition and evaluation of the interplay between social and technological developments and professional, ethical and legal responsibilities of scientists and engineers. f A number of symbolic formalisms, particularly computer programming languages and diagrammatic formalisms for problem and software specification and design. g Of science and engineering underpinning computer based models used to explain and articulate areas of human activity relevant to a number of specialist areas of computing science. Teaching/learning methods and strategies Core knowledge is presented in the taught modules, where research issues and recent developments are incorporated as appropriate. Laboratory sessions are used to introduce practical techniques and associated software tools. Formative exercises are used to ensure the students understanding of core techniques and tools. Several assessed coursework exercises and the dissertation are used as unifying educational experiences. Students are encouraged to develop self-learning using Web resources, the university library and course hand-outs. Assessment A variety of assessment methods are used in different modules, from 100% coursework to 80% examination. Coursework assessments include programming assignments, essays, class tests, problem sheets, laboratory reports, seminar participations and oral presentations. Group work is an integral part of some modules in this programme. The core modules taught in the first semester are assessed by a variety of coursework assessments. Most optional modules have an examination, typically 60% of the assessment. 3

4 C2(ii) Cognitive Skills a Formulate ill-defined problems into well-defined projects. b Apply numerical and reasoning skills and critically review different approaches to problems. c Solve complex problems and make decisions in new situations. d Frame hypothesis, test theory with observations and evaluate diverse data relating to real world problems. e Ability to undertake research and experimental design, showing independence of thought and judgement. Teaching/learning methods and strategies Intellectual skills are developed by direct contact with lecturers. Throughout the programme, modules involve applied work in collecting, analysing or reviewing data and observation, with particular emphasis on the critical assessment of existing knowledge. Reasoning skills, problem posing and solving skills are promoted through seminars and groups discussions. Some exercises are well defined and focused on a particular technique or skill; others are less well defined and the student has to refine the project and determine (and justify) the best approach. In all cases results have to be presented clearly and analysed. Research, design and analysis are brought together in the dissertation, which normally has a substantial practical component and requires the integration of skills and knowledge from several parts of the programme. Assessment Intellectual skills are assessed variously through the design and implementation of computer programs, essays, reports, presentations and problem sheets. Intellectual skills are formally indentified in assessment guidelines, made available to students. Problem solving and reasoning skills are fundamental to many assessed exercises. The requirement to produce a dissertation (of about 15,000 words) allows assessment at the highest level of intellectual skills acquired and integrates much of the material taught in other parts of the student s course. 4

5 C2(iii) Subject Specific Practical Skills a Competence and self direction in problem identification specification and analysis, design and implementation of software using a range of appropriate strategies and specific techniques. b Expertise in the use of available tools and software to aid in the construction of software and computerbased information systems for a variety of application areas. c Competence in evaluating and analysing information from a variety of sources in selected areas of specialism. d Competence in handling a variety of symbolic notations, including programming languages and diagrammatic formalisms. Teaching/Learning methods and strategies Lectures are the general vehicle for introducing the basics of a topic, which are supplemented by directed reading, seminars, and laboratories where appropriate. Practically oriented modules will often use supervised laboratories for supporting development of computer programs. Modules which address more theoretical and abstract concerns often use seminars to exemplify and amplify the ideas and notations used in lectures, and stimulate discussion of topics. Assessment Problem analysis, program design and implementation are typically assessed by coursework exercises and through demonstration of their operation. Competence with specific notations, the underlying methodologies of research, design and implementation of programs, and comparative attributes of existing systems are usually assessed by a combination of seminar performance, coursework exercises and examination. C2(iv) Key Skills and Attributes a Think and work independently, integrate knowledge and problem-solving strategies, exercise own judgement, deal with unfamiliar situations and manage own time. b Retrieve and synthesise information from independent sources and present coherent intellectual arguments in oral, written, and graphical form, suitably referenced and formatted for both specialist and non-specialist audiences. c Work effectively as part of a team. d Make full use of information technology: , word processing, the web, software development tools etc. e Recognition of the importance of continuous professional development and appropriate standards of behaviour. Teaching/Learning methods and strategies Transferable skills training is a compulsory part of the first semester programme; it is the focus of much of the compulsory Research Techniques module. Coursework in many modules entails presentation skills. Seminars rely on discussion and interaction, often focussed around reading particular papers. Independent work is required in the majority of coursework, in the dissertation and in examinations. Assessment Assessment of skill is a fundamental aspect of most work on the programme. Other transferable skills are less amenable to direct assessment but submission of word-processed assignments on time and to a satisfactory standard confirms that skills have been acquired. 5

6 SECTION D1: COURSE PROFILE AND AWARD REQUIREMENTS Please insert (i.e. cut and paste) the course profile here or complete the following boxes, as appropriate. If you insert the course profile, please ensure that the NOTICE below about changes to modules is retained. Each box relates to a year of study. If the programme is part-time or offers a part-time option, please extend the number of years as appropriate (maximum = 9). NOTICE: Whilst the University will make every effort to offer the modules listed, changes may sometimes have to be made for reasons outside the University s control (e.g. illness of a member of staff) or because of low enrolment numbers or sabbatical leave. Where this is the case, the University will endeavour to inform students. Core, Compulsory and Optional modules See attached course profile Progression requirements or Award Year 1 60 credits [PG Cert.] 120 credits [PG Dip.] 180 credits MSc Computing Science 6

7 SECTION D2: REGULATORY FRAMEWORK FOR AWARDS D2a Regulatory Framework: (please tick against the relevant framework) Common Course Structure for Undergraduate Programmes (CCS) NAM Common Course Structure (NAM-CCS) Common Regulatory Framework for Postgraduate Programmes (CPG) It is expected that all new degree courses will conform to the common University regulations (either to CCS, NAM-CCS or CPG, and the associated Instructions to Examiners). D2b Degree Classifications For First degree programmes i) Weighting (in percentage terms) which each year of the course contributes to the calculation of the degree classification. (Part-time Programmes) Year 1 Year 5 Year 2 Year 6 Year 3 Year 7 Year 4 Year 8 Year 9 ii) Please indicate whether an aggregate mark and/or the University marks profile is taken into consideration for the purpose of determining degree class. D2c Postgraduate Awards i) Are (any) modules assessed on a pass/fail (instead of numerical) basis? YES NO If so how many credits are assessed on a pass/fail basis ii) Can the award be conferred with distinction? YES NO iii) On what criteria is the distinction awarded? (See also the Regulations for the Common Postgraduate Regulatory Framework.) An aggregate over 180 credits of at least 70% 7

8 APPENDIX A COURSE PROFILE FULL TIME Course Profile for 2012/3 Course: School: Director: Computing Science (Msc) (T1G400101) Computing Sciences Dr Wenjia Wang Year 1U Compulsory Modules ( 80 credits) CMPSMP2Y RESEARCH TECHNIQUES CW 20 YEAR D5*D6,D8*B9/E1*E2 CMPSMP6X DISSERTATION DS 60 SEM2 U Options Range A Students will select 60 credits from the following modules: CMPSMA23 APPLICATIONS PROGRAMMING CW 20 SEM1 B1*B2,B3*E4 CMPSMB11 DATABASE MANIPULATION WW 20 SEM1 A5*A6,A7/B6,B7*B8 CMPSMB13 INTERNET & MULTIMEDIA TECHNIQUES CW 20 SEM1 A1*A2,D3*C4 Options Range B Students who have studied the material covered in Option Range A modules may ask for exemption on the basis of prior learning, or may ask for a concession to study suitable alternative modules. Students will select 40 credits from the following modules: CMPSMA24 CMPSMB20 CMPSMB22 ARTIFICIAL INTELLIGENCE AND ALGORITHMICS SYSTEMS ENGINEERING ISSUES E-BUSINESS SYSTEMS DEVELOPMENT WW 20 SEM2 C7*C8,C3*D4 WW 20 SEM2 E4*E3*A4,D3/C4 CP 20 SEM2 C7*C8,B5,A1*A2 CMPSMC24 DATA MINING CW 20 SEM2 B2*D7*D8,C1*C2 CMPSMC28 APPLIED STATISTICS CW 20 SEM2 D1*E3*A4,A3/B4 CMPSMC34 DISTRIBUTED COMPUTING WW 20 SEM2 C5*C6,D1,A3*B4 CMPSMD22 COMPUTER NETWORKS WW 20 SEM2 A5*A7*A8,D1,B1*B2/B3*E4/C5*C6 CMPSMI16 COMPUTER VISION (FOR DIGITAL PHOTOGRAPHY) WW 20 SEM2 D2*D9,A2*D3*C4 PART-TIME Course Profile for 2012/3 Course: School: Director: Computing Science (Msc) (T2G400201) Computing Sciences Dr Wenjia Wang This is the first year of your taught Masters programme. INDIVIDUALS NEED TO DISCUSS WITH THEIR ADVISER 8

9 WHEN CHOOSING THEIR MODULES AND DETERMINING THEIR PROGRAMMES FOR THE FIRST AND SECOND YEARS Compulsory Modules ( 20 credits) CMPSMP2Y RESEARCH TECHNIQUES CW 20 YEAR D5*D6,D8*B9/E1*E2 Options Range A Students will select 40 credits from the following modules: CMPSMA23 APPLICATIONS PROGRAMMING CW 20 SEM1 B1*B2,B3*E4 CMPSMB11 DATABASE MANIPULATION WW 20 SEM1 A5*A6,A7/B6,B7*B8 CMPSMB13 INTERNET & MULTIMEDIA TECHNIQUES CW 20 SEM1 A1*A2,D3*C4 Options Range B Students will select credits from the following modules: Students will select credits from the following modules: CMPSMA24 CMPSMB20 CMPSMB22 ARTIFICIAL INTELLIGENCE AND ALGORITHMICS SYSTEMS ENGINEERING ISSUES E-BUSINESS SYSTEMS DEVELOPMENT WW 20 SEM2 C7*C8,C3*D4 WW 20 SEM2 E4*E3*A4,D3/C4 CP 20 SEM2 C7*C8,B5,A1*A2 CMPSMC24 DATA MINING CW 20 SEM2 B2*D7*D8,C1*C2 CMPSMC28 APPLIED STATISTICS CW 20 SEM2 D1*E3*A4,A3/B4 CMPSMC34 DISTRIBUTED COMPUTING WW 20 SEM2 C5*C6,D1,A3*B4 CMPSMD22 COMPUTER NETWORKS WW 20 SEM2 A5*A7*A8,D1,B1*B2/B3*E4/C5*C6 CMPSMI16 COMPUTER VISION (FOR DIGITAL PHOTOGRAPHY) WW 20 SEM2 D2*D9,A2*D3*C4 9

10 This is the second year of your taught Masters programme. But students may start their dissertation in their first year if they wish and are approved by the Course Director. Compulsory Modules ( 60 credits) CMPSMP6X DISSERTATION DS 60 SEM2 U Options Range A Students will select 20 credits from the following modules: CMPSMA23 APPLICATIONS PROGRAMMING CW 20 SEM1 B1*B2,B3*E4 CMPSMB11 DATABASE MANIPULATION WW 20 SEM1 A5*A6,A7/B6,B7*B8 CMPSMB13 INTERNET & MULTIMEDIA TECHNIQUES CW 20 SEM1 A1*A2,D3*C4 Options Range B Students may select no or 20 credits from the following modules, depending on the number of the modules of their first year. Students will select credits from the following modules: CMPSMA24 CMPSMB20 CMPSMB22 ARTIFICIAL INTELLIGENCE AND ALGORITHMICS SYSTEMS ENGINEERING ISSUES E-BUSINESS SYSTEMS DEVELOPMENT WW 20 SEM2 C7*C8,C3*D4 WW 20 SEM2 E4*E3*A4,D3/C4 CP 20 SEM2 C7*C8,B5,A1*A2 CMPSMC24 DATA MINING CW 20 SEM2 B2*D7*D8,C1*C2 CMPSMC28 APPLIED STATISTICS CW 20 SEM2 D1*E3*A4,A3/B4 CMPSMC34 DISTRIBUTED COMPUTING WW 20 SEM2 C5*C6,D1,A3*B4 CMPSMD22 COMPUTER NETWORKS WW 20 SEM2 A5*A7*A8,D1,B1*B2/B3*E4/C5*C6 CMPSMI16 COMPUTER VISION (FOR DIGITAL PHOTOGRAPHY) WW 20 SEM2 D2*D9,A2*D3*C4 10