MA983-7-SU-CO:
Dissertation with Professional Placement

The details
2023/24
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Summer
Postgraduate: Level 7
Current
Monday 22 April 2024
Friday 28 June 2024
60
06 November 2023

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC G10112 Mathematics,
MSC G10124 Mathematics,
MSC GN1312 Mathematics and Finance,
MSC GN1324 Mathematics and Finance,
MSC G30412 Data Science,
MSC G30424 Data Science,
MSC G20312 Optimisation and Data Analytics,
MSC G30012 Statistics,
MSC N32312 Actuarial Science,
MSC N32324 Actuarial Science,
MSC G30512 Applied Data Science,
MSC G30524 Applied Data Science,
MSC G30612 Data Science and its Applications,
MSC G30624 Data Science and its Applications

Module description

This module enables students to undertake a placement with an external Placement Provider. The work placement will enable students to hone their professional and transferable skills as part of their continuing academic studies. Students will develop the skills sought by graduate employers and apply their academic knowledge in a practical working environment.


Students must secure their own placement and obtain approval from their Dissertation Supervisor, by the end of August before accepting a position.  The Placements Team and the Department should be informed if a placement is secured at which point information on enrolling on this module will be provided.

Module aims

The aims of this module are:



  • To provide the student with the opportunity to apply their academic learning outcomes in a work-related context

  • To enable students to develop employability skills in a work-related environment.

  • To write a dissertation based on an independently developed research project in collaboration with the employer providing the placement, under the supervision of an allocated academic supervisor.

Module learning outcomes

By the end of this module, students will be expected to be able to:



  1. Demonstrate a detailed understanding of work processes and a critical exploration of work ethics.

  2. Demonstrate the ability to engage in a self-reflective process of adapting their taught skills to a work environment.

  3. Demonstrate the capacity to effectively work in a team within a work environment.

  4. Develop effective work-based skills throughout the placement.

  5. Demonstrate mastery of the research process as appropriate for their area of study, working from initial discussion of the problem with the company through to analysis and critical discussion, highlighting their advanced knowledge of actuarial science, finance, data science, operational research, statistics, mathematics or mathematics education

Module information

The syllabus will be determined on an individual basis for each student. The Placement will be subject to approval by both the Placements Team and the Department. The Department and the Placement Provider will agree on the focus of the placement via the Learning Agreement to ensure the learning outcomes are met.

The Department and Placement Provider will agree on the focus of the placement via the Tripartite Work Placement Agreement or Erasmus plus Agreement (as appropriate), and this will ensure that the student is able to meet the module learning outcomes set out in the previous section of this form.


 Students are expected to write a dissertation with the following aspects:



  1. Clarity and coherence: students should understand the ideas involved in the subject at an appropriate level. In a project developing some piece of theory, the work should develop the theory in a logical order, with clear definitions and explanations of how these ideas could be useful in practice. In a project of applying existing mathematical theories/methods/models to a practical question/data, a clear explanation of why and how theories/methods/models are applied in the practical example(s) should be included.

  2. In suitable level of difficulty, depth and breadth of ideas expressed. Students are expected to have sufficient depth for an MSc dissertation – in particular, it should have little or no overlap with the material in students’ lecture courses. Original material or insights are not required, but are very welcome, and often students are expected to give different examples from original sources.

  3. In good quality English and word process. Mathematical formulas, figures and tables should be presented clearly and accurately in the dissertations. The resources, such as books, papers, and online resources should be properly cited and listed as references.


Include a section of the literature review in the area of the project

Learning and teaching methods

The learning and teaching methods will be dependent on the placement and will be recorded for an individual student on the training agreement signed by the Placement Provider, the student, and the University.

Each student will be assigned to an Academic Supervisor in their Department, and a Placement Supervisor named by the Placement Provider. Students will liaise with their Academic Supervisor and their Placement Supervisor on a regular basis throughout the period of their placement.

In particular, The Academic Supervisor and the Student are required to have a formal progress meeting during the Summer term to track progress and engagement in addition to agreeing on the appropriate Dissertation topic related to the placement. Also, liaison between the Students and their supervisors can carry out as necessary after the placement has ended in order to allow the student to complete the dissertation.

Students will additionally be provided with the contact details of administrative staff in the Department who will be contactable throughout the placement; and with the details of the relevant Faculty Placements Team who will be available to students throughout their placement to provide advice and support in relation to generic work-based learning issues.

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Vasileios Giagos, email: v.giagos@essex.ac.uk.
Dr Vasileios Giagos
v.giagos@essex.ac.uk

 

Availability
No
No
No

External examiner

No external examiner information available for this module.
Resources
Available via Moodle
No lecture recording information available for this module.

 

Further information

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