University of the West of Scotland

Programme Specification

Session: 2019/20

Last modified: 23/08/2019 10:57:31

Named Award Title:MSc AdvancedComputing/BigData/IoT/Digital Health

Award Title for Each Award: MSc  AdvancedComputing/BigData/IoT/Digital Health
PG Cert  Advanced Computing
PG Dip  Advanced Computing

Awarding Institution/Body: University of the West of Scotland
Language of Instruction & Examination: English
Award Accredited By:British Computer Society (Advanced Computing and Big data)
Mode of Study:Full Time
Part Time
Campus:Paisley

School:School of Computing, Engineering and Physical Sciences

Admission Criteria

Candidates must be able to satisfy the general admission requirements of the University of the West of Scotland as specified in Section 6 of the University Regulatory Framework together with the following programme requirements:

Appropriate Undergraduate Qualification
Candidates must be able to satisfy the general admission requirements of the University of the West of Scotland as specified in Section 6.3 of the University Regulatory Framework together with the following programme requirements: Appropriate undergraduate qualification: Honours Degree (2.2 or above) in Computing/ Engineering (or relevant disciplines)
Other Required Qualifications/Experience

None


Further desirable skills pre-application

Applicants may also be considered with other academic, vocational or professional qualifications deemed to be equivalent.

Final decision of admission will be at the discretion of the Programme Leaders.


General Overview

The availability of high speed internet and advancement in data processing, persisting and provisioning technologies along with miniaturization of sensing devices have opened new opportunities to utilise data to obtain a better understand of many application areas. This comprehensive understanding leads to intelligent and well informed decision making supported by field data. As we are moving toward connected environments, our reliance on data is increasing and also becoming important from a business and personal perspective. Advanced computing technologies provide a roadmap of technological innovation across science and engineering domains. The MSc Advanced Computing is a postgraduate programme focused on teaching advance topics of internet-of-things, big data, and digital health. It is designed to develop practical skills through comprehensive understanding of fundamental knowledge coupled with hands-on experience of advance computing technologies. 

The MSc in Advanced Computing is motivated by following factors. Firstly, the growing market of the IoT and its mass adoption at personal and community level i.e., smart and wearable devices, and smart cities. Within UK and across the world, governments are supporting real-deployment of smart sensing solutions for future cities. Secondly, conventional methodologies of data processing cannot handle Volume, Veracity, Variety, and Veracity of data generated through modern data sources i.e., smartphone, IoT, social media etc. Big data offers solutions to 4 V’s with big data processing platforms and real-time analytics. This makes big data very attractive to service driven business and industry striving to unleash hidden wealth within modern data sources. Thirdly, with 2020-2021 NHS funding gap forecasted to £30billion, the need of cost effective and timely health services is becoming inevitable.  Digital health with its market size expected to reach £253 billion by 2022, has emerged as a promising field offering new range of services, better care and new job prospects. Finally, the advancement in data sensing and communication technologies has significantly increased the reliance of businesses on data sources. 

 

This MSc programme focuses on practical skill development. Modules are carefully selected as core and specialised modules. Core modules like Mobile Networks and Smartphone Application, Data Mining and Visualization, and Object Oriented Analysis and Design support necessary skill development for more specialised modules in Big Data, Internet-of-Things, and Digital Health tracks. Modules like Emerging Topics in Advanced Computing and Networking is included in the programme structure to ensure students can learn state-of-the-art tools, technologies, and methodologies that are practiced in industry. The team is committed to provide research informed teaching, ensuring students can gain research experience and obtain critical awareness and judgement of methodologies, tools and technologies in specialised domains. 

Research active and experienced staff members in the area of advanced computing are involved in teaching and learning activities of this programme. They have been leading various nationally and internationally funded R&D projects and standardisation activities, in collaboration with other research institutions and industry partners. They have a track record of scholarly publications in top tier journals and conferences.

23           Programme Overview (2)  (Employers)

The MSc Advanced Computing has been designed to adhere to UK QAA Benchmark Statement for Masters Degrees in Computing. The programme is supported by the Scottish Funding Council’s Innovation Centres: Digital Health & Care Institute, Data Lab and Innovation Centre for Sensor and Imaging Systems. For its relevance to the job market trends and employers expectations from graduating students this programme is acknowledged by the UWS Industrial Advisory Board.

This programme is mainly motivated by the growing importance of internet-of-things and big data and their obvious benefits to the application areas of digital health. International Data Corporation (IDC: a market research firm) predicated that IoT market will grow to £4.93 trillion in revenue by 2020 [1]. Gartner estimated, IoT install base will hit 26 billion units by 2020 [2]. Similarly, IDC forecasted that that Big Data technology market will grow at a 26.4% CAGR (compound annual growth rate) to £28.79 billion by 2018 – approximately six times the growth rate of the overall information technology market [3]. The market of both smart sensing solutions (IoT) and data driven services (digital health) is very promising. The overall interest in advanced computing across the world has risen, driven by the inception of sensing devices, and tools and technologies that make used of data generated from those devices for a particular application area. With the growing market of internet-of-things, big data and importance of advanced computing skills in healthcare , UWS graduates will be appropriately skilled with theoretical understanding and practical knowledge.

Teaching and learning activities within each module are specifically designed to focus on practical skills development – rather than concentrating on theoretical aspects of topics. The development of knowledge and expertise of advanced computing is support by core modules in specialised tracks of Internet-of-things, Big Data, and digital health. All core modules are designed to respect the overarching theme of advanced computing, delivering research informed teaching in lectures, tutorials, and laboratory sessions; while other modules will focus on academic, research and ethical practices within professional environment.

Through the master projects students are encouraged to select topics having a focus or potential for industrial innovation or addressing specific research challenges where appropriate. Students are introduced to research groups and institutes to work on research projects relevant to overall theme of advanced computing. 

 

24           Programme Overview (3)  (students)

This specialist programme is designed to build upon your computing expertise and focuses on the understanding and development of state-of-the-art advanced computing systems that meet the increasing business requirements of modern day businesses. In the MSc Advanced Computing you will learn theoretical concepts and build practical skills. The teaching and learning activities are explicitly designed to support comprehensive understanding of a topic and its practical working and hands-on experience. This programme will also suit students who will pursue research degrees (MPhil/PhD) in related technology areas upon their graduation from this programme. You will closely work with research active staff to seek research guidance for emerging research challenges and areas.

 

25           Pointers to Further Study-Progression Routes

This MSc programme is predominantly delivered by research active staff. Students will get a chance to work on challenging research problems. The masters project will significantly help to understand requirements of research and get motivated to solve research challenges that have a social and economic impact. Completion of this MSc will greatly enhance the potential of any student to progress to a doctorate degree in relevant areas of advanced computing as well as offering enhanced career opportunities in industry.

 

26        Teaching, Learning and Assessment Strategy

The teaching and learning strategies adopted for the PgD/MSc advanced computing, Big Data, IoT, and digital health are planned to deliver students with the necessary subject knowledge, understanding, abilities and skills for the Advanced Computing and/or related stream profession.

An assortment of teaching methods will be used to guarantee that students become and remain engaged, motivated and challenged to learn. Much of this is left to the professionalism of the staff delivering the material with some traditional lectures and tutorials featuring for face-to-face delivery in most modules. After first year, distance and flexible delivery however a range of innovative approaches to learning will be used and these will be made available for face-to-face students as supporting material or to enable reinforcement of learning.

The intention is to deliver the programme on a face-to-face basis initially, to allow bedding in with the development of material to support distance and other forms of delivery brought on stream to support demand.

Moodle is the University’s Virtual Learning Environment (VLE). Every module will have a Moodle site, with background information to the module, teaching, laboratory and tutorial schedules and staff contact details. Some modules will make use of discussion forums and chat groups to support engagement with the module topic and materials outside of scheduled class times. Formative and summative (project and coursework type) assessment material are also on the Moodle sites.

All modules will be taught by experienced staff, many of whom make use of materials and topics raised through their professional research or consultancy activities. Many case studies and examples of applications are based on real industrial situations.

A variety of assessment methods are used throughout the programme. These include critical investigations of problems within industry, and proposal of possible solutions, laboratory reports, individual and group presentations and formal examinations.

Both group project work and individual project work are incorporated into the curriculum, enabling students to develop and demonstrate essential employment skills.

27           External and Internal Reference Points Used to Inform Programme Outcomes

The QAA Subject Benchmark statements for Computing have been used to inform the levels of competence that would be expected of a graduate from this Master programme.

Scottish Credit and Qualifications Framework (SCQF) were used to help frame the general learning outcomes for the programme and for modules. The BCS’s requirements for specialist Masters courses accredited for CITP Further Learning and for partial fulfilment of the educational requirements for CEng have also been used. The Engineering Council’s document “UK Standard for Professional Engineering Competence” has also been used to help frame the learning outcomes at MSc level.

The use of the above external reference points was aimed at ensuring broad comparability with other related programmes in the HE sector.

The UWS Regulatory Framework Section 5 Regulations for Programmes of Study leading to the University’s Academic Awards are outlined in Section 5.2.13.

 

[1] http://www.cxotoday.com/story/iot-market-to-hit-71-trillion-by-2020-idc/

[2] http://www.gartner.com/newsroom/id/2636073

[3] https://www.idc.com/prodserv/4Pillars/bigdata


Employability Skills & Personal Development Planning

This programme has been specifically designed considering the UWS Graduate Attributes of Universal, Work ready, and Successful. Details to these attributes is available at UWS Graduate Attributes webpage.

Students will be supported in accordance with the Personal Development Planning and Policy Framework of the University. Personal Development Planning is embedded within the programme with links to each module. PDP will be introduced at the beginning of the programme and will be supported with regular workshops for the class. A range of coursework exercises will be identified and used to give students the opportunity to reflect upon their performance and plan for the next cycle of PDP. The demonstration of the ability to carry out PDP will be a requirement for progression from the PgD to the MSc part of the programme.

Employability skills will be built into the programme at a variety of points in many different ways. Industrial and research methods employed in smart network development will be a frequent theme of examples in class and in the laboratory exercises. Generic skills that are transferable to many field of employment are embedded throughout the programme and are listed in some detail in the module descriptors. All the core modules will ensure that research-informed materials are delivered with research skills demonstrated wherever appropriate. There will also be specialist teaching input from industry wherever possible ensuring up-to-date content for certain topics.

The University Student Link service is available to help all students with advice, resources and assistance in many areas affecting employability. Personal planning, personal finance, time management, career advice, interview preparation and assistance with preparing CVs are some of the areas they can assist with. Services include advice and support on career planning, graduate recruitment, placement, part time work, summer jobs and volunteering. For full time students in particular, the Careers adviser works with staff to deliver a series of workshops aimed at helping graduates seek employment.

Work Based Learning/Placement Details

Opportunities for industry focused learning activities have been built into some of the modules of the programme enabling students to engage with employers. These include ‘live’ case studies, problem-solving scenarios, and individual work-related projects. Some industry and research based placement will be offered in the programme.


Programme structures and requirements, SCQF level, trimester, module name and code, credits and awards (Link to Regulation 5.2.9)

A. PG Cert
Learning Outcomes (Maximum of 5 per heading)

Knowledge and Understanding

A1Demonstrate good knowledge of advanced computing
A2Carry out work that evidences a critical understanding of the practical aspects of advanced computing provision
A3Demonstrate a critical awareness of the capabilities of relevant technologies

Practice - Applied Knowledge and Understanding

B1Apply a range of principal methodologies covered in the modules to identify requirements in planning advanced computing
B2Investigate, compare and evaluate advanced computing
B3Apply a range of techniques/tools to support the development and/or management of advanced computing and document relevant information

Communication, ICT and Numeracy Skills

C1Interpret and analyse advanced computingg sets and information using ICT methods
C2Communicate information effectively with different audiences using a range of appropriate methods

Generic Cognitive Skills - Problem Solving, Analysis, Evaluation

D1Evaluate the performance of advanced computingthrough laboratory work
D2Demonstrate an advanced working knowledge of recent advances in advanced computing and present findings in report format

Autonomy, Accountability and Working With Others

E1Demonstrate leadership and/or partnership in the planning and delivery individual work and group work
E2Demonstrate a high level of understanding of the needs of the business and how to work with colleagues to design and explain advanced computing strategies

Core Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
               

* Indicates that module descriptor is not published.

Footnotes

Optional Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
11COMP11068Advanced Data Science20check mark  
11COMP11058Advanced Wireless Networking Technologies20check mark  
11COMP11069Data Mining and Visualisation20 check mark 
11COMP11070eHealth and Healthcare Systems20 check mark 
11COMP11060Emerging Topics in Computing10 check mark 
11COMP11001Ethics for the IT Professional10check mark  
11COMP11071Intelligent Systems20 check mark 
11COMP11061Internet of Things (IoT) and Applications20 check mark 
11NURS11129Introduction to eHealth20check mark  
11COMP11062Mobile Networks and Smartphone Applications20check mark  
11COMP11032Object Oriented Analysis & Design10check mark  
11COMP11017Research Design and Methods10 check mark 

* Indicates that module descriptor is not published.

Footnotes
Justification on Knowledge and Understanding learning outcomes of PgC and how learning outcomes of the core modules deliver them:
From SCQF Level 11
Demonstrate and/or work with:
• Knowledge that covers and integrates most, if not all, of the main areas of a subject discipline – including their features, boundaries, terminology and conventions.
• A critical understanding of the principal theories, principles and concepts.
• A critical understanding of a range of specialised theories, principles and concepts.
• Extensive, detailed and critical knowledge and understanding in one or more specialisms, much of which are at or informed by developments at the forefront.
• A critical awareness of current issues in a subject/discipline and one or more specialisms.
From the QAA Masters Benchmark in Computing
5.1 The study of computing at master's degree level is typically characterised by:
• An ability to evaluate the technical, societal and management dimensions of computer systems
• A knowledge and understanding of advanced aspects of computer systems and their use
• A combination of theory and practice, with practice being guided by theoretical considerations
• A strong emphasis on the underlying discipline and/or applications
• The mastery of the practical methodology of the relevant area of computing, whether for general application in software development or in specialised applications relating to the storing, processing and communication of information
• An understanding of, and attention to, the many and varied aspects of quality
• An understanding of professional, legal, social, cultural and ethical issues related to computing and an awareness of societal and environmental impact.
Based on the above, we believe that our following suggestions are a reasonable expectation of outcomes from our modules:
A1. Demonstrate knowledge of advanced computing;
A2. Carry out work that shows a critical understanding of the practical aspects of advanced computing technological provision;
A3. Show a critical awareness of the capabilities of relevant advanced computing technologies.

Criteria for Progression and Award

The criteria for the Award of Postgraduate Certificate are defined in the University Regulatory Framework.

There is no specific progression decision needed after the first trimester, as all students are registered for the MSc. The Postgraduate Certificate is available as an exit award:
Postgraduate Certificate (PgC) advanced computing.

For a PgC advanced computing, at least 60 credits and minimum of 3 modules are required, of which a minimum of 40 are at least level 11 and none below level 10.

The students will be informed and encouraged to progress towards PgD or Masters.


B. PG Dip
Learning Outcomes (Maximum of 5 per heading)

Knowledge and Understanding

A1Demonstrate a critical and deep understanding and practical ability in examining the current and emerging techniques, standards, methodologies and tools that support the development of advanced computing
A2Analyse business requirements, choose from and justify the choice of different smart networking approaches by analysing the benefits and risks for a given advanced computing strategy, and recommend appropriate standard-based solutions
A3Develop and deploy advanced computing solutions using suitable methodologies, technologies, software tools etc.

Practice - Applied Knowledge and Understanding

B1Apply skills to configure advanced computing devices or technologies, and deploy/develop applications that meet standards
B2Analyse a given business scenario in order to offer recommendations on how best to develop the advanced computing solutions

Communication, ICT and Numeracy Skills

C1Analyse and interpret complex information relating to the development, management and evaluation of advanced computing solutions using ICT methods
C2Produce and present numerical results regarding advanced computing, e.g., in performance evaluation
C3Communicate information and justifying the chosen advanced computing strategy to stakeholders effectively with different audiences using a range of appropriate methods

Generic Cognitive Skills - Problem Solving, Analysis, Evaluation

D1Carry out critical analysis, evaluation and synthesis of strategies meeting a given set of requirements
D2Prepare reports that demonstrate a working knowledge of recent advances in advanced computing
D3Demonstrate ability to develop and implement solutions to practical problems
D4Analyse and critically review research in a specific area of advanced computing

Autonomy, Accountability and Working With Others

E1Demonstrate leadership in the planning and delivery individual work and group work
E2Work in ways that demonstrates critical reflection upon roles and responsibilities
E3Demonstrate a high level of understanding of the needs of the business and how to work with non-technical senior colleagues to design and explain advanced computingstrategies
E4Demonstrate the ability to work in a professional manner and be able to make informed judgements relating to professional issues including ethical considerations

Core Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
11COMP11069Data Mining and Visualisation20 check mark 
11COMP11060Emerging Topics in Computing10 check mark 
11COMP11001Ethics for the IT Professional10check mark  
11COMP11062Mobile Networks and Smartphone Applications20check mark  
11COMP11032Object Oriented Analysis & Design10check mark  
11COMP11017Research Design and Methods10 check mark 

* Indicates that module descriptor is not published.

Footnotes

Optional Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
11COMP11068Advanced Data Science20check mark  
11COMP11058Advanced Wireless Networking Technologies20check mark  
11COMP11001Ethics for the IT Professional10check mark  
11COMP11071Intelligent Systems20 check mark 
11COMP11061Internet of Things (IoT) and Applications20 check mark 
11NURS11129Introduction to eHealth20check mark  

* Indicates that module descriptor is not published.

Footnotes

Criteria for Progression and Award

The criteria for the Award of Postgraduate Diploma are defined in the University Regulatory Framework.

For a PgD advanced computing, at least 120 credits are required of which a minimum of 100 are at least at level 11 and none below level 10.

The normal length of study will be the equivalent of one year of full-time study.


C. MSc/MA/MBA
Learning Outcomes (Maximum of 5 per heading)

Knowledge and Understanding

A1Produce an MSc project specification, and write a detailed, well-argued and coherent thesis of a sustained independent work of high quality that fulfils an agreed specification
A2Demonstrate a systematic and critical understanding of the approaches available to address problems and create knowledge and useful artefacts within the advanced computing/Big Data/IoT/eHealth subject areas, and of the underlying theoretical assumptions and concepts of such approaches
A3Demonstrate an ability to select and apply in a critical and reflective fashion, appropriate research and/or development techniques in producing a solution or solutions to a practical problem in the advanced computing/Big Data/IoT/eHealth subject area
A4Critically and reflectively plan and execute an advanced computing/Big Data/IoT/eHealth related project to develop an artefact that is fit for purpose in addressing a stated problem
A5Understand the design/research aspects of smart networking algorithm/protocol development

Practice - Applied Knowledge and Understanding

B1Apply appropriate theoretical and practical methods to the analysis and solution of advanced computing/Big Data/IoT/eHealth
B2Identify potential projects and opportunities for enhancing advanced computing/Big Data/IoT/eHealth
B3Conduct appropriate research and undertake design and development of advanced computing/Big Data/IoT/eHealth solutions
B4Implement solutions in accordance with designs and evaluate their effectiveness

Communication, ICT and Numeracy Skills

C1Communicate in English with others at all levels
C2Present and discuss proposals on strategic matters, leading and sustaining debate and feed results back to improve proposals
C3Demonstrate personal and social skills and awareness of the concerns of others

Generic Cognitive Skills - Problem Solving, Analysis, Evaluation

D1Plan and evaluate programs of laboratory work relating to advanced computing/Big Data/IoT/eHealth
D2Demonstrate ability to develop and implement creative solutions to practical problems
D3Analyse and critically review data from various analyses in the context of advanced computing/Big Data/IoT/eHealth

Autonomy, Accountability and Working With Others

E1Provide technical and commercial leadership
E2Demonstrate potential to plan, budget organise, direct and control tasks, people and resources
E3Demonstrate a personal commitment to professional standards, codes of conduct, safe systems of work, contributing to sustainable development, and continuing professional development

Core Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
11COMP11069Data Mining and Visualisation20 check mark 
11COMP11060Emerging Topics in Computing10 check mark 
11COMP11001Ethics for the IT Professional10check mark  
11COMP11024Masters Project60check markcheck markcheck mark
11COMP11062Mobile Networks and Smartphone Applications20check mark  
11COMP11032Object Oriented Analysis & Design10check mark  
11COMP11017Research Design and Methods10 check mark 

* Indicates that module descriptor is not published.

Footnotes
Details of Dissertation/Project Requirements

The choice of topic for the MSc Project is made by the student in consultation with the MSc Project coordinator, academic staff and Programme Leader that the student may have consulted with. The topic is normally related to the subjects and content covered during the PgC/PgD stage of the programme. At the start of the MSc Project the student will be allocated a specific supervisor and moderator with experience and expertise in the student’s chosen topic for the duration of the MSc project module.

A student is expected to reach three specific milestones during the MSc project:

1. To produce an MSc Project Specification that meets the approval of a panel of academic reviewers in the School.

2. To produce an interim report approximately at the half-way point of the project, containing an early draft of the literature review as well as comprehensive description of the project methodology to be used, and forward plan for the completion of the project.

3. To submit a dissertation of approximately 18,000 words in which the following areas are typically expected to be addressed: subject literature is critically reviewed, full project methodology is described, collected data and results are published, or prototype systems are developed and evaluated, and a critique incorporating recommendations suggested by the research results, a self-assessment and recommendations for further work on the topic are included.

Optional Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
11COMP11068Advanced Data Science20check mark  
11COMP11058Advanced Wireless Networking Technologies20check mark  
11COMP11070eHealth and Healthcare Systems20 check mark 
11COMP11071Intelligent Systems20 check mark 
11COMP11061Internet of Things (IoT) and Applications20 check mark 
11NURS11129Introduction to eHealth20check mark  

* Indicates that module descriptor is not published.

Footnotes
All the students will enroll in Advanced Computing framework with named exit awards for Big Data, Internet of Things,and digital health. However the students will only be eligible to these exit awards on the successful completion of 2 specialised modules and a project in the same area.

For MSc Big data, the following specialised modules need successful completion of "Advanced Data Science" and "Intelligent Systems".
For MSc Internet of Things, the following specialised modules need successful completion of "IoT and Applications" and "Advanced Wireless Networking Technologies".
For MSc Digital Health, the following specialised modules need successful completion of "Introduction to eHealth" and "eHealth and Healthcare Systems".
For MSc Advanced Computing, any 2 specialised modules need successful completion.

Criteria for Progression and Award

The criteria for the Award of Masters are defined in the University Regulatory Framework.

Credit points at least 180 credits of which a minimum of 150 are at least at level 11 and none below level 10.

All the students will enroll in Advanced Computing framework with named exit awards for Big Data, Internet of Things,and Digital Health. However the students will only be eligible to these exit awards on the successful completion of 100 specialist credits which constitute of 2 specialised modules and a project in the same area. For students who take varied combination will exit with Advanced Computing exit award.


D. DBA/DProf
Learning Outcomes (Maximum of 5 per heading)

Knowledge and Understanding

A1

Practice - Applied Knowledge and Understanding

B1

Communication, ICT and Numeracy Skills

C1

Generic Cognitive Skills - Problem Solving, Analysis, Evaluation

D1

Autonomy, Accountability and Working With Others

E1

Core Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
               

* Indicates that module descriptor is not published.

Footnotes

Optional Modules
SCQF Level Module CodeModule NameCreditTrimesterFootnotes
123
               

* Indicates that module descriptor is not published.

Footnotes

Criteria for Award


Regulations of Assessment

Candidates will be bound by the general assessment regulations of the University as specified in section 7 of the University Regulatory Framework .

An overview of the assessment details is provided in the Student Handbook and full details of the assessment criteria for each module is provided in the module descriptor which forms part of the module pack issued to students. For further details on assessment please refer to Section 7 of the Regulatory Framework.

To qualify for an award of the University, students must complete all the programme requirements and must meet the credit minima detailed in Section 3 of the Regulatory Framework.

(Regulation 7)

(Assessment Policy)