|
 Academic Year: |
2014/5 |
| Owning Department/School: |
Department of Mathematical Sciences |
| Credits: |
12 |
| Level: |
Masters UG & PG (FHEQ level 7) |
| Period: |
Academic Year |
| Assessment Summary: |
CW 60%, OR 40% |
| Assessment Detail: |
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| Supplementary Assessment: |
Coursework reassessment (where allowed by programme regulations) |
| Requisites: |
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| Description: |
Aims: This unit is designed to train students in the process of creative mathematical problem formulation and working in interdisciplinary research teams. In each semester there will be 10 weeks of a student-led symposium, followed by an Integrative Think Tank (ITT), an intensive five-day event. This year-long unit plays a key role in the Integrated PhD in Statistical Applied Mathematics, the degree course for students in the Statistical Applied Mathematics at Bath (SAMBa) doctoral training programme. The unit is taken for credit by SAMBa students in their MRes year. In each semester SAMBa students will, under supervision, organise a series of symposia on themes relating to the upcoming ITT, giving some of the symposia talks themselves, and inviting academic staff and external experts to speak and give short courses (there is a budget for this). Each MRes student will make at least one presentation in each symposium series and one such presentation will be assessed each semester. A student organising committee (SOC), made up of SAMBa students, will plan the programme of symposia, starting work before each semester in order to allow time to invite external speakers. This will be done under supervision and in liaison with the SAMBa Co-directors over the upcoming ITT topics. All SAMBa students will be members of the SOC in their MRes year, and so will help plan the Semester 2 symposia that year and Semester 1 symposia for the following year. The programme for Semester 1 of 2014 will be planned by an academic to initiate the process. The ITTs are designed exclusively for students on the MRes in Statistical Applied Mathematics. They are an exercise in "research distillation" in which students will learn how to formulate problems that are sufficiently advanced so as to contain some of the "hard" problems that industrial partners have to tackle, but sufficiently "clean" to allow them to be tackled in a Mathematics PhD within the theme of SAMBa. Participants in each ITT will comprise: * Students on the MRes in Statistical Applied Mathematics; * Partners from industry or other academic fields (presenting their problems); * Professional facilitators; * Academic staff; * SAMBa students at the PhD stage of SAMBa (after the first cohort of SAMBa students has reached this stage). An ITT will begin with (i) presentation of open problems (including data) by industrial representatives and/or outside academics ("application partners") and proceed in a systematic way with: (ii) breakout sessions with ITT staff and application partners as roaming consultants (iii) student writing sessions (iv) follow up presentations by application partners (v) daily short presentations by students and (vi) feedback from ITT staff and application partners. The students will also be mentored by more senior SAMBa students, once such students are in place. Teamwork will be strongly encouraged throughout the ITT. During the week, research groups of 2 to 4 students with dedicated mentors will be formed. Students will produce a report from the ITT in the form of a research proposal, which will be assessed. Learning Outcomes: Students should be able to learn independently and transfer knowledge into unfamiliar situations in a spirit of critical enquiry. Students should be able to work in research teams with different technical abilities and academic backgrounds. Students should be able to formulate concise mathematical problems from informally presented technical challenges, including the use of data. Students should understand the requirements for academic writing, including referencing and the appropriate use of graphs, diagrams and tables. Students should demonstrate academic writing skills within the production of a research proposal. Skills: Collaborative learning, self-organised learning, working in teams, seminar organisation, independent study. |
| Programme availability: |
MA50246 is Compulsory on the following programmes:Department of Mathematical Sciences
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