MA199-7-SP-CO:
Research Skills and Employability

The details
2023/24
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 15 January 2024
Friday 22 March 2024
0
03 January 2024

 

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

 

(none)

Key module for

MSC G305JS Applied Data Science,
MSC G306JS Data Science and its Applications

Module description

The module will provide an opportunity to all PG Maths students to develop the skills and knowledge required to succeed both during and after their time at University.


It will help prepare them fully to engage in the wider society (both academic and industry) and to make significant contributions in whatever area of life and work they choose to do so. For example, the module provides an introduction to the principal research tools for the students on postgraduate courses in Mathematical Sciences, including practice in the mathematical word-processing language LaTeX; and the module will also provides an introduction of programming language R.

Module aims

The aims of this module are:



  • To provide an opportunity to all PGT Maths students to further develop the skills and knowledge required to succeed both during and after their time at University. Students will work towards enhancing:

    • Self-awareness.

    • Opportunity awareness.

    • Decision learning.

    • Transition learning.

    • Basic academic writing skills in Latex.

    • Basic programming skills using R.

    • Awareness of independent research skills.



  • These skills will help them progress with employability from the outset of their studies.

  • To help prepare the students fully to engage in the wider society and to make significant contributions in whatever area of life and work they choose to do so.

Module learning outcomes

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



  1. Review key personal factors that inform career choice (interests, skills, values, motivations, relationships).

  2. Reflect on current and future academic, and employability development.

  3. Become more professionally aware of careers directly and indirectly related to the degree.

  4. Deepen their knowledge of the national and international graduate labour market.

  5. Identify skills, attitudes, and competencies sought by employers, including academic writing skills, and independent research abilities.

  6. Develop a list of suitable careers and narrowing down to a short list.

  7. Identify new and build on already developed skills to help transition to a profession (transition learning).

  8. Fully understand the recruitment and selection of masters graduates, and how this differs by size and sector.

  9. Learn how to maximise chances of success, and how to research and find vacancies, including the hidden jobs market.

Module information

PG Maths students will be expected to carefully consider their future objectives and how they need to plan and manage their development to achieve these objectives. The module will have an emphasis on transition learning to ensure that they will make progress with employability from the outset of their studies, understand graduate recruitment and selection processes, how to best prepare their CVs and cover letters, how to work out application forms and, will learn about interview processes and assessment centres. The module will also ensure students learn basic independent research skills, including identifying interesting research topic for their dissertation.


Syllabus



  • Self-awareness of interests, strengths, motivations, priorities and values that inform career choice 

  • Opportunity awareness in terms of knowing what work opportunities exist and what the requirements are.

  • Decision learning regarding optimal opportunities for a future career. 

  • Identification of new skills and development of existing skills to help transition to a profession. 

  • Basic academic writing skills in Latex.

  • Basic programming skills using R.

  • Awareness of independent research skills.

Learning and teaching methods

This module will be delivered via:

  • One 1-hour lecture per week.
  • Two 1-hour guest lectures throughout spring/summer term.

Bibliography

This module does not appear to have any essential texts. To see non - essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Latex short report: research project outline and personal career development plan     

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

Module is either passed or marked as not completed.

Reassessment

Module is either passed or marked as not completed.

Module supervisor and teaching staff
Dr Chris Antonopoulos, email: canton@essex.ac.uk.
Wenxing Guo
maths@essex.ac.uk

 

Availability
No
No
No

External examiner

No external examiner information available for this module.
Resources
Available via Moodle
Of 13 hours, 13 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information

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