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Study information

Digital and Technology Solutions (Integrated Degree Apprenticeship) (2024)

1. Programme Title:

Digital and Technology Solutions (Integrated Degree Apprenticeship)

NQF Level:

7

2. Description of the Programme (as in the Business Approval Form)

The MSc Digital and Technology Solutions (Integrated Degree Apprenticeship) is an innovative taught programme designed and delivered with industry and targeted at professionals. The programme is aligned to the Level 7 Apprenticeship Standard - Digital & Technology Solutions Specialist (Data Analytics Specialism). It will cover the core areas of digital leadership and technology management as well as underpinning technical knowledge and skills in Data Analytics that will enable you to explore applications of Digital Technology and Data Analytics in the workplace.

Taught modules will be delivered by University of Exeter in an accessible format to accommodate and complement your organisational context. You will undertake modular teaching at first followed by a substantial work based project in your organisation, which will be closely supported by academics with relevant expertise. Throughout the modular components, industry experts will be consulted on course content, ensuring a balance of academic rigour and relevance to business needs.

Digital and Data are transforming the modern workplace and skills in data analytics provide you with the foundation and vehicle for these domains to be developed, embedded and communicated in practice. You will benefit from the University’s significant investments in world leading academics and gain a respected qualification alongside practical mentoring to effectively embed your learning in the workplace. Your employers participating in the course will gain valuable skillsets within their organisation to drive digital and data leadership and innovation.

 

3. Educational Aims of the Programme

The main programme’s intention is to provide you the academic content for a Level 7 apprenticeship, the approved standard for Level 7 Digital & Technology Solutions Specialist (Integrated Degree) as stated in Institute for Apprenticeships and Technical Education (IfATE): https://www.instituteforapprenticeships.org/apprenticeship-standards/digital-and-technology-solutions-specialist-integrated-degree/. Programme’s content is designed for investigation, identifying and implementing technological strategic solutions and will cover:

  • the management and leadership in technology;
  • related business and change management;
  • data engineering for ensuring the underlying acquired big data is organised and accessible for analysis and decision-making;
  • data in business and society for analysing the information governance requirements;
  • data analysis and visualisation with extensive coverage of machine learning for making informed decisions and derive valuable insights for addressing real-world business and industrial challenges.

This is a blended programme and you will be taught at Streatham campus and virtually. The content will be delivered through a combination of intensive face to face teaching (e.g. in person/virtual masterclasses and webinars) and subsequent weekly online teaching, incorporating lectures, practicals, seminars and group work, individual self-study, and online interaction with modules’ tutors. Assessment will primarily be coursework assignments designed to be flexible and fit around your other commitments, presentations and in class tests.

Industry partners will also contribute to programme design and offer guest lectures and specialist training. This programme format is currently unique in the UK and represents a distinctive industry-focused approach to postgraduate training in Digital and Technology Solutions.

Mapping to the Level 7 Digital and Technology Solutions (Data Analytics Specialism) standard

When used to deliver the academic content needed for this apprenticeship, the knowledge, skills and behaviours (KSBs) associated with the apprenticeship have been mapped to programme modules.

 

4. Programme Structure

University of Exeter Award: MSc Digital and Technology Solutions

The MSc Digital and Technology Solutions is an eighteen-month full-time programme of study at Regulated Qualifications Framework (RQF) level 7 (as confirmed against the FHEQ). Programmes are divided into units of study called ‘modules’ which are assigned a number of ‘credits’. The MSc is made up of 180 credits, of which there are 100 credits of taught modules, 20 credit Portfolio and a 60 credit Project module. All modules on this programme are compulsory.

Interim awards:

There are no interim awards.

Standard Exit  Awards

  • Postgraduate Diploma: At least 120 credits of which 90 or more must be at level M.
  • Postgraduate Certificate: At least 60 credits of which 45 or more must be at level M.

 

5. Programme Modules

Stage 1

Code Title Credits Compulsory NonCondonable
BEMM794DABusiness and Change Management20YesYes
BEMM795DAManagement and Leadership in Technology 20YesYes
BEMM796DAPortfolio20YesYes
COMM033DAData Engineering15YesYes
COMM034DAData in Business and Society15YesYes
COMM035DAExploratory Data Analysis15YesYes
COMM036DAMachine Learning15YesYes
COMM037DAProject60YesYes

6. Programme Outcomes Linked to Teaching, Learning & Assessment Methods

On successfully completing the programme you will be able to: Intended Learning Outcomes (ILOs) will be accommodated & facilitated by the following learning & teaching and evidenced by the following assessment methods:

A Specialised Subject Skills & Knowledge

A Specialised Subject Skills and Knowledge

  1. Evaluate the strategic importance of technology enabled business processes, and how they are designed and managed to determine a firm’s ability to compete effectively.
  2. Analyse the principles of business transformation and how organisations integrate different management functions in the context of technological change.
  3. Demonstrate the role of leadership in contemporary technology-based organisations and the personal leadership qualities that are required to establish and maintain an organisations technical reputation.
  4. Demonstrate key aspects of information governance requirements, legislative data protection and security, and ethical concerns involved in data management and analysis.
  5. Explain the big data technologies for data management of large scale real-time complex datasets with help of modern databases/data storage platforms, and to identify and select business data from available data (including from clouds) for analytics in the context of enterprise systems.
  6. Utilise appropriate analytical techniques including visual analytics for performing analytical investigations of data to understand the nature, utility, quality of data and draw statistically sound conclusions and decisions.
  7. Conduct high-quality complex investigations using machine learning techniques to make data driven decisions to solve live commercial problems.

 

Learning & Teaching Activities

In-person and virtual masterclasses in form of lectures, workshops, seminars, practical sessions, discussions, online materials, webinars, progress reviews and individual support.

Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.

Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.

B Academic Discipline Core Skills & Knowledge

B Academic Discipline Core skills and Knowledge

  1. Design and develop technology roadmaps, implementation strategies and transformation plans focused on digital technologies to achieve improved productivity, functionality and end user experience in an area of technology specialism.
  2. Evaluate the significance of human factors to leadership in the effective implementation and management of technology enabled business processes.
  3. Demonstrate effective technology leadership and change management skills for managing technology driven change and continuous improvement.
  4. Describe the data architecture and structures using appropriate data modelling tools.
  5. Analyse the properties of data storage solutions, their design and implementation in the available platforms for processing and analytics in large-scale and diverse data scenarios.
  6. Demonstrate concepts, tools and techniques for data visualisation and presentation of data and how this provides a qualitative understanding of the information on which decisions can be based on.
  7. Evaluate analytical software, key algorithms, appropriate data selection, and model fitting to develop effective machine learning and analytical solutions for complex data problems.

 

Learning & Teaching Activities

In-person and virtual masterclasses in form of lectures, workshops, seminars, practical sessions, discussions, online materials, webinars, progress reviews and individual support. 

Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.

Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.

C Personal / Transferable / Employment Skills & Knowledge

C Personal/ Transferable/Employment Skills and Knowledge

  1. Negotiate and agree digital and technology specialism delivery budgets with those with decision-making responsibility.
  2. Develop own leadership style and professional values that contributes to building high performing teams.
  3. Demonstrate effective communication methods to present data and results that support human understanding of complex data sets.
  4. Demonstrate awareness of tools and technologies relevant to data science.
  5. Conduct any data analysis project from initiation to final report.

 

Learning & Teaching Activities

In-person and virtual masterclasses in form of lectures, workshops, seminars, practical sessions, discussions, online materials, webinars, progress reviews and individual support.  

Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.

Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming and data analysis, project work, and individual and group presentations.

7. Programme Regulations

Award

You must attempt the End-Point Assessment (EPA) before the University of Exeter award can be conferred.

There are no condonable modules (i.e., no condonement process) available in this programme and the pass mark for award of credit in PG modules (NQF level 7) is 50%.

Full details of assessment regulations for all taught programmes can be found in the TQA Manual, specifically in the Credit and Qualifications Framework, and the Assessment, Progression and Awarding: Taught Programmes Handbook.

Additional information, including Generic Marking Criteria, can be found in the Learning and Teaching Support Handbook.

 

8. College Support for Students and Students' Learning

Academic Mentors

In accordance with University policy a system of Academic mentors is in place for all students on this programme. A University-wide statement on such provision is included in the University’s TQA Manual. As a student enrolled on this programme you will receive the personal and academic support of the Programme Coordinator and will have regular scheduled tripartite meetings with your academic mentor and workplace mentor; you may request additional meetings as and when required. The role of Academic mentor is to provide you with advice and support during the programme study. Your academic mentor will work with you to address questions, explain processes,

monitor progress and sign off your end point assessment materials. They will help sign-post to module academic leads and welfare and other University services if you need. They will also conduct face-to-face tripartite meetings at your workplace sites and virtual meetings using webinars and other technology.

Academic Staff and IT Support.

You can also make an appointment to see individual teaching staff. Information Technology (IT) Services provide a wide range of services throughout the Exeter campuses including open access computer rooms, some of which are available 24 hours, 7 days a week. Help may be obtained through the Helpdesk, and most study bedrooms in halls and flats are linked to the University’s campus network.

Additionally, the Faculty has its own dedicated IT support staff, helpdesk and computer facilities which are linked to the wider network, but which also provide access to some specialised software packages. Email is an important channel of communication between staff and students in the Faculty and an extensive range of web based information (see https://intranet.exeter.ac.uk/emps/) is maintained for the use of students, including a comprehensive and annually revised student handbook.

The Harrison Learning Resource Centre is generally open during building open hours. The Centre is available for quiet study, with four separate rooms that can be booked for meetings and group work. Amongst its facilities, the Learning Resource Centre has a number of desks, four meeting rooms with large LCD screens, and free use of a photocopier. Also available are core set texts from your module reading lists, and undergraduate and MSc projects from the past two years (if applicable).

Online Module study resources provide materials for modules that you are registered for, in addition to some useful subject and IT resources. Generic study support resources, library and research skills, past exam papers, and theAcademic Honesty and Plagiarism’ module are also available through the student portal (http://vle.exeter.ac.uk).

Student/Staff Liaison Committee (SSLC) enables students and staff to jointly participate in the management and review of the teaching and learning provision.

 

10. Admission Criteria

All applications are considered individually on merit. The University is committed to an equal opportunities policy with respect to gender, age, race, sexual orientation and/or disability when dealing with applications. It is also committed to widening access to higher education to students from a diverse range of backgrounds and experience.

Standard University Admissions requirements:

Entry requirements for this programme can be found on the Postgraduate Study Page.

Candidates must satisfy the general admissions requirements and English Language requirements of the University of Exeter.

Undergraduate applicants must satisfy the Undergraduate Admissions Policy of the University of Exeter.

Postgraduate applicants must satisfy the Postgraduate Admissions Policy of the University of Exeter.

Specific requirements required to enrol on this programme are available at the respective Undergraduate or Postgraduate Study Site webpages.

Programme specific requirements:

Applications will be made to the employer, with the University having oversight with respect to academic qualifications.

  • A second-class honours degree in a relevant subject
  • Level 2 Maths and English will need to be evidenced prior to end-point assessment (EPA).
  • Alternatively, a minimum of five years’ experience in a data analytics role would be considered if no prior degree is held.

Applicants will be in a role that supports the gathering of evidence required for the Level 7 Digital & Technology Solutions apprenticeship ‘standard’

 

11. Regulation of Assessment and Academic Standards

Each academic programme in the University is subject to an agreed Faculty assessment and marking strategy, underpinned by institution-wide assessment procedures.

The security of assessment and academic standards is further supported through the appointment of External Examiners for each programme. External Examiners have access to draft papers, course work and examination scripts. They are required to attend the Board of Examiners and to provide an annual report. Annual External Examiner reports are monitored at both Faculty and University level. Their responsibilities are described in the University's code of practice. See the University's TQA Manual for details.

12. Indicators of Quality and Standards

Faculty entry – Provide summary of the outcomes of recent accreditation by PSRBs or others.

Certain programmes are subject to accreditation and/or review by professional and statutory regulatory bodies (PSRBs).

There is no PSRB for this programme.

 

14 Awarding Institution University of Exeter
15 Lead College / Teaching Institution Faculty of Environment, Science and Economy
16 Partner College / Institution
17 Programme accredited/validated by
18 Final Award(s) MSc
19 UCAS Code (UG programmes) DigTechSol
20 NQF Level of Final Awards(s): 7
21 Credit (CATS and ECTS) 180/90
22 QAA Subject Benchmarking Group (UG and PGT programmes)
23 Origin Date March 27th 2024 Last Date of Revision: March 27th 2024