Return to Practice Nursing

2021/22 Part-time Undergraduate course

School:

School of Nursing

Campus:

Magee campus

Start dates:

September 2021

January 2022

Overview

Ulster University is the sole provider for Return to Practice Nursing in Northern Ireland.

Summary

Thank you for your interest in the Return to Practice Programme at Ulster.

Our Return to Practice Programme is being re-designed. The new programme is scheduled to commence in September 2021 pending approval from the Nursing and Midwifery Council.

For up to date information about the Return to Practice Programme, please email the Course Director, Dr Pauline Black, at p.black@ulster.ac.uk

How to Apply

If you are interested in applying for the Return to Practice Programme, please click on the link below to access our Online Applications process.

Once you have set up your username, please choose Undergraduate Part Time as your application type to ensure your application is processed correctly.

When prompted for your programme choice, please scroll down to Nursing, Return to Practice - Part Time, Magee.

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About this course

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Start dates

  • September 2021
  • January 2022

Teaching, Learning and Assessment

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Content

The content for each course is summarised on the relevant course page, along with an overview of the modules that make up the course.

Each course is approved by the University and meets the expectations of:

Attendance and Independent Study

As part of your course induction, you will be provided with details of the organisation and management of the course, including attendance and assessment requirements - usually in the form of a timetable. For full-time courses, the precise timetable for each semester is not confirmed until close to the start date and may be subject to some change in the early weeks as all courses settle into their planned patterns. For part-time courses which require attendance on particular days and times, an expectation of the days and periods of attendance will be included in the letter of offer. A course handbook is also made available.

Courses comprise modules for which the notional effort involved is indicated by its credit rating. Each credit point represents 10 hours of student effort. Undergraduate courses typically contain 10- or 20-credit modules (more usually 20) and postgraduate course typically 15- or 30-credit modules.

The normal study load expectation for an undergraduate full-time course of study in the standard academic year is 120 credit points. This amounts to around 36-42 hours of expected teaching and learning per week, inclusive of attendance requirements for lectures, seminars, tutorials, practical work, fieldwork or other scheduled classes, private study, and assessment. Part-time study load is the same as full-time pro-rata, with each credit point representing 10 hours of student effort.

Postgraduate Master’s courses typically comprise 180 credits, taken in three semesters when studied full-time. A Postgraduate Certificate (PGCert) comprises 60 credits and can usually be completed on a part-time basis in one year. A 120-credit Postgraduate Diploma (PGDip) can usually be completed on a part-time basis in two years.

Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures you can expect at least 3 contact hours per week (lectures/seminars/tutorials). Laboratory classes often require a greater intensity of attendance in blocks. Some modules may combine lecture and laboratory. The precise model will depend on the course you apply for and may be subject to change from year to year for quality or enhancement reasons. Prospective students will be consulted about any significant changes.

Assessment

Assessment methods vary and are defined explicitly in each module. Assessment can be a combination of examination and coursework but may also be only one of these methods. Assessment is designed to assess your achievement of the module’s stated learning outcomes. You can expect to receive timely feedback on all coursework assessment. The precise assessment will depend on the module and may be subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.

Coursework can take many forms, for example: essay, report, seminar paper, test, presentation, dissertation, design, artefacts, portfolio, journal, group work. The precise form and combination of assessment will depend on the course you apply for and the module. Details will be made available in advance through induction, the course handbook, the module specification and the assessment timetable. The details are subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.

Normally, a module will have 4 learning outcomes, and no more than 2 items of assessment. An item of assessment can comprise more than one task. The notional workload and the equivalence across types of assessment is standardised.

Calculation of the Final Award

The class of Honours awarded in Bachelor’s degrees is usually determined by calculation of an aggregate mark based on performance across the modules at Levels 5 and 6, (which correspond to the second and third year of full-time attendance).

Level 6 modules contribute 70% of the aggregate mark and Level 5 contributes 30% to the calculation of the class of the award. Classification of integrated Master’s degrees with Honours include a Level 7 component. The calculation in this case is: 50% Level 7, 30% Level 6, 20% Level 5. At least half the Level 5 modules must be studied at the University for Level 5 to be included in the calculation of the class.

All other qualifications have an overall grade determined by results in modules from the final level of study. In Master’s degrees of more than 200 credit points the final 120 points usually determine the overall grading.

Academic profile

The University employs over 1,000 suitably qualified and experienced academic staff - 59% have PhDs in their subject field and many have professional body recognition.

Courses are taught by staff who are Professors (25%), Readers, Senior Lecturers (18%) or Lecturers (57%).

We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic staff (81%) are accredited fellows of the Higher Education Academy (HEA) - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.

The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise. The precise staffing for a course will depend on the department(s) involved and the availability and management of staff. This is subject to change annually and is confirmed in the timetable issued at the start of the course.

Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.

Figures correct for academic year 2019-2020.

Magee campus

Our vision is aligned to the strategic growth plan for the city and region.


Accommodation

Enjoy student life in one of Europe's most vibrant cities.

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Sports Facilities

Our facilities in Magee cater for many sports ranging from archery to volleyball, and are open to students and members of the public all year round.

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Student support

At Student Support we provide many services to help students through their time at Ulster University.

Find out more - information about student support  

Address

Ulster University
Northland Road
Derry~Londonderry
County Londonderry
BT48 7JL

T: 028 7012 3456

Modules

Here is a guide to the subjects studied on this course.

Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.

In this section

Year one

Statistical Modelling & Data Mining

Year: 1

This module first provides a systematic understanding of probability and statistics. It then provides an in-depth analysis of the statistical modelling process and how to answer hypothesised questions. Next, the module provides a synthesis of the concepts of data mining and methods of exploring data. The content will be delivered and experienced through lectures, seminars and practical exercises using tools, such as Python, R and Weka. Online tools, such as Blackboard will be used to facilitate blended learning approach. On completing this module, students will be able to compute conditional probabilities and use null hypothesis significance testing to test the significance of results and understand and compute statistical measures such as the p-value for these tests. Students will apply, evaluate and critically appraise this knowledge in a range of complex real-world contexts.

Pervasive Computing

Year: 1

This module is optional

The focus of this module is to provide an opportunity for students to gain an in-depth understanding of pervasive computing and to apply this understanding to a range of application domains through working with wireless sensor networks. The module surveys emerging hardware and software components associated with Pervasive Computing Systems, examining the technical and societal issues concerned with a pervasive infrastructure, wireless networks, protocols and emergent algorithms. In doing so a number of examples of innovative systems and applications are reviewed. The module includes a strong practical element where students will be asked to develop services providing support for wearable and smart home context-aware solutions.

Autonomic Computing & Robotics

Year: 1

This module is optional

This module focuses on the development of self-managing systems, inspired by the human body's autonomic nervous system. The ANS is that part of the nervous system that manages body functions such as blood circulation, intestinal activity, and hormonal secretion and production, all without conscious effort. The desire of Autonomic Computing and Robotics is to bring a similar self-managing level of capability to systems, including robots, and thus free up the human user for higher-level concerns.

Deep Learning and Its Application

Year: 1

This module is optional

The module introduces the fundamental concepts of deep learning, neural networks as well as the theory associated with the development of successful deep learning algorithms. Students will learn state of the art convolutional neural networks, recurrent neural networks, loss functions and optimization process along with development tools, and apply them to the development of solutions for deep learning application domains (i.e. Computer Vision, Natural Language Processing, etc.)

Year two

Scalable Advanced Software Solutions

Year: 2

This module aims to explore a range of modern development and deployment concepts in the context of scalable and high performance computing services.

Within this module concepts such as containerisation, Continuous Integration, Continuous Delivery, cloud architectures, scalable solutions and infrastructure will be explored. Additionally, advanced programming/development concepts facilitating high performance solution development will be examined.

IoT Networks & Security

Year: 2

This module is optional

IOT has emerged as a significant technology that can be used for automation and empowerment. The module covers the life cycle of IoT security mechanisms, including the design, development, management and, most importantly, how they are sustained. The module provides an understanding of the IoT architecture, protocols and security considerations

Big Data & Infrastructure

Year: 2

This module is optional

Within this module a variety of database and data storage paradigms will be explored, ranging from more traditional relational systems to NoSql and object stores, time series databases, semantic store and graph stores.

Consideration will be given to big data and the problem with storing and querying high volumes of highly variable data which is stored and processed at a high speed. The cloud computing paradigm will also be introduced and how to avail of its power and resources.

The core concepts of distributed computing will be examined in the context of Hadoop. Students will be taught, practically and theoretically, about the components of Hadoop, workflows, functional programming concepts, use of MapReduce, Spark, Pig, Hive and Sqoop.

Masters Project

Year: 2

This module is optional

The aim of the project is to allow the student to demonstrate their ability in undertaking an independent research project for developing theoretical perspectives, addressing research questions using data, or analysing and developing real-world solutions. They will be expected to utilise appropriate methodologies and demonstrate the skills gained earlier in the course when implementing the project.

As part of the project development activity, they will be required to extract and demonstrate knowledge from the literature in an analytic manner and develop ideas and appropriate hardware and software implementations. This may involve the development of a hardware sensor component or may access existing hardware to develop new/ novel software processing or data analytics. This will typically be followed by a structured analysis of needs for a realistic application or actual organisation and identification and application of tools/techniques required to deliver a well-formed solution. Through the project, the student will develop capabilities to analyse cases studies related to IoT / Artificial Intelligence / Advanced Computer Science and its application in a range of domains including transport, environment, health and commerce. The project may further create improvement plans and recommendations for future implementation based on the tools/technologies experienced during the programme of study.

In summary, the Masters Project represents a piece of work performed by the student under suitable staff supervision which draws both from the practical and creative nature of a problem-solving project and the traditional, scholarly exposition of an area of study. The content of the work must be original and contain a critical appraisal of the subject area.

Knowledge Engineering & Computational Creativity

Year: 2

This module is optional

This module will cover modern topics in a classical field of artificial intelligence, including knowledge representation and reasoning (deductive and inductive), and their effective utilisation in e.g. decision making, semantic web and computational creativity. Students will gain deep understanding of key concepts and principles, and gain practical skills in critically evaluating and effectively building knowledge-based applications.

Machine Learning

Year: 2

This module is optional

This module will provide students with the mathematical and statistical knowledge to understand the foundations of common supervised and unsupervised machine learning algorithms, and with the practical programming skills to apply them to real world data-sets. State-of-the art methods including probabilistic programming and explainable AI will also be introduced.

Masters Applied Research Project

Year: 2

This module is optional

In this final module, you will undertake an independent research project, addressing real research challenges or analysing and developing real world solutions. The project will draw upon knowledge and skills developed throughout your MSc. Your research will involve a detailed literature review to understand and define the problem. Following this, you will design, implement and evaluate a novel solution. You will then communicate the outcome of your research through a research paper and presentation.

As part of the project development activity you will be required to extract and demonstrate knowledge from the literature in an analytic manner and develop ideas including, appropriate hardware and software implementations. This may involve the development of a hardware sensor component or may access existing hardware to develop new / novel software processing or data analytics. This will typically be preceded by a structured analysis of needs for a realistic application or actual organisation and identification and application of tools / techniques required to deliver a well-formed solution. Through the project you will develop capabilities to analyse cases studies related to IoT / Artificial Intelligence / Advanced Computer Science and its application in a range of domains including transport, environment, health and commerce. The project may further create improvement plans and recommendations for future implementation based upon the tools / technologies experienced during the programme of study.

In summary the masters project represents a piece of work performed by the student under suitable staff supervision which draws both from the practical and creative nature of a problem-solving project and the traditional, scholarly research. The content of the work must be original and contain a critical appraisal of the subject area.

Standard entry conditions

We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.

Entry Requirements

You need

(a)

(i) a second class honours degree or better, in the subject areas of computing, engineering, mathematics or related discipline, from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard; or

(ii) an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification; and the qualification must be in the subject areas of computing, engineering, mathematics or related discipline;

and

(b) provide evidence of competence in written and spoken English (GCSE grade C or equivalent). For applicants whose first language is not English the minimum English language requirement is an Academic IELTS 6.0 with no band score less than 5.5, Trinity ISE: Pass at level III or equivalent English language tests comparable to IELTS equivalent score.

In exceptional circumstances, as an alternative to (a) (i) or (a) (ii) and/or (b), where an individual has substantial and significant experiential learning, a portfolio of written evidence demonstrating the meeting of graduate qualities (including subject-specific outcomes, as determined by the Course Committee) may be considered as an alternative entrance route. Evidence used to demonstrate graduate qualities may not be used for exemption against modules within the programme.

English Language Requirements

English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.

Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.

United States of America flagAdditional information for students from United States of America

Undergraduate

Each programme will have slightly different requirements, both in terms of overall points and certain subjects, so please check the relevant subject in the undergraduate on-line prospectus.

Normally Ulster University welcomes applications from students with:

Generally, for undergraduate courses for international applicants we require equivalent to A-Level CCC, for these courses the entry requirements will be one of the following:

Qualification

  • Qualification High School diploma with overall GPA 3.0 and 1000 out of 1600 in SAT (Post March 2016)
  • High School Diploma with overall GPA 3.0 and grades 3,3,3 in 3 AP subjects
  • High School Diploma with overall GPA 3.0 and 580 in 3 subject specific SAT tests
  • High School Diploma with overall GPA 3.0 and 26 in ACT
  • Associate Degree with GPA 3.0

Please note that some courses will have subject specific entry requirements, please check the relevant course entry requirements in the undergraduate on-line prospectus. If there is a subject specific requirement you will be required to get 580 in the Subject Specific SAT or Grade 3 in the Subject Specific AP test.

Some courses may also have additional entry criteria, such as a Skype interview, submission of a satisfactory portfolio, criminal record check or health check, please check the relevant course entry requirements in the undergraduate on-line prospectus.

For courses that require GCSE Mathematics Grade C, you will be required to successfully complete Grade 12 in High School Diploma Mathematics.

Some courses have higher entry requirements, please see list below;


BSc Hons Optometry

(A-level ABB to include 2 science subjects from Biology, Chemistry, Mathematics and Physics or equivalent)

Qualification

To include one of the following:

  • High School Diploma with overall GPA 3.0 and grades 5,4,4 in 3 AP subjects to include 2 science subjects
  • High School Diploma with overall GPA 3.0 and 1200 out of 1600 in SAT and 650 in 2 subject specific SAT, to include 2 science subjects
  • High School Diploma with overall GPA 3.0 and 28 in ACT and 2 AP subjects grades 4,4, to include 2 science subjects
  • Associate Degree with GPA 3.2 in an appropriate science subject

    In addition to both of the following:
  • Successful completion of Grade 12 High school Diploma English and Mathematics
  • A satisfactory criminal record check and health screening

MPharm Pharmacy

(A-Level BBB to include Chemistry and 1 science from Mathematics, Physics or Biology or equivalent)

Qualification

To include one of the following:

  • Qualification High School Diploma with overall GPA 3.0 and grades 4,4,4 in 3 AP subjects to include Chemistry and one other science
  • High School Diploma with overall GPA 3.0 and 1200 out of 1600 in SAT and 630 in 2 subject specific SAT to include Chemistry and one other science
  • High School Diploma with overall GPA 3.0 and 28 in ACT and 2 AP subjects Grades 4,4 to include Chemistry and 1 other science
  • Associate Degree with GPA 3.2 in an appropriate science subject

    In addition to both of the following:
  • Successful completion of Grade 12 High school Diploma English and Mathematics
  • A satisfactory criminal record check and health screening

BSc Hons Nursing (Adult) and BSc Hons Nursing (Mental Health)

(A-Level BBC or equivalent)

Qualification

To include one of the following:

  • High School Diploma with overall GPA 3.0 and grades 4,4,3 in 3 AP subjects
  • High School Diploma with overall GPA 3.0 and 1150 out of 1600 in SAT (Post March 2016)
  • High School Diploma with overall GPA 3.0 and 600 in 3 Subject Specific SAT tests
  • High School Diploma with overall GPA 3.0 and 28 in ACT
  • Associate Degree with GPA 3.1

    In addition to all of the following:
  • Successful completion of Grade 12 High school Diploma English and Mathematics
  • A satisfactory Skype interview
  • A satisfactory criminal record check and health screening

Financial Information

In addition to the scholarships and bursaries open to all international students, US students may apply for Federal and Private US loans

English Language

Qualification
Level 12 English Lang in HSD

View more information for students from United States of America  

Careers & opportunities

Professional recognition

Apply

Start dates

  • September 2021
  • January 2022

Contact

If you would like to contact us

E: study@ulster.ac.uk

International Admissions Office

E: internationaladmissions@ulster.ac.uk

For more information visit

Disclaimer

  1. The University endeavours to deliver courses and programmes of study in accordance with the description set out in this prospectus. The University’s prospectus is produced at the earliest possible date in order to provide maximum assistance to individuals considering applying for a course of study offered by the University. The University makes every effort to ensure that the information contained in the prospectus is accurate but it is possible that some changes will occur between the date of printing and the start of the academic year to which it relates. Please note that the University’s website is the most up-to-date source of information regarding courses and facilities and we strongly recommend that you always visit the website before making any commitments.
  2. Although reasonable steps are taken to provide the programmes and services described, the University cannot guarantee the provision of any course or facility and the University may make variations to the contents or methods of delivery of courses, discontinue, merge or combine courses and introduce new courses if such action is reasonably considered to be necessary by the University. Such circumstances include (but are not limited to) industrial action, lack of demand, departure of key staff, changes in legislation or government policy including changes, if any, resulting from the UK departing the European Union, withdrawal or reduction of funding or other circumstances beyond the University’s reasonable control.
  3. If the University discontinues any courses, it will use its best endeavours to provide a suitable alternative course. In addition, courses may change during the course of study and in such circumstances the University will normally undertake a consultation process prior to any such changes being introduced and seek to ensure that no student is unreasonably prejudiced as a consequence of any such change.
  4. The University does not accept responsibility (other than through the negligence of the University, its staff or agents), for the consequences of any modification or cancellation of any course, or part of a course, offered by the University but will take into consideration the effects on individual students and seek to minimise the impact of such effects where reasonably practicable.
  5. The University cannot accept any liability for disruption to its provision of educational or other services caused by circumstances beyond its control, but the University will take all reasonable steps to minimise the resultant disruption to such services.

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