Teaching and learning

The primary method of communicating information and stimulating interest is through lectures, which provide you with a formal knowledge base from which your understanding can be developed. Understanding of lecture material is reinforced by problem classes, computer workshops and group tutorials, as well as by self-study. Peer-assisted learning, discussion with other students and individual discussion with staff also support the learning process.

Whereas lectures provide the primary vehicle for accumulating a knowledge base, your intellectual, academic and research skills will mainly be developed outside of the lecture theatre, for example, by tackling and discussing problems set on a regular (usually weekly) basis. Some coursework requires you to develop your thinking beyond rote learning, and to link ideas between different modules. You will be encouraged to reason openly through discussion of set problems in tutorials. For some modules, workshops allow you to work on problems individually or in groups, with teaching staff / assistants present to give help. Teaching staff also hold regular "office hours" during which you are welcome to come and ask questions about the material and obtain individual (one-to-one) assistance and feedback.

Practical and transferable skills are developed by the provision of opportunities for hands-on experience through regular workshops and projects. Data analysis demonstrations and exercises are an essential component of the core modules and much of the tuition for statistical computing takes place in computer workshops, which will allow you to learn through active participation. Additional workshops running during the teaching terms provide preparation for the summer research project and cover the communication of statistics, for example, the presentation of statistical graphs and tables. Project supervisors will provide guidance on how to manage an extended task effectively and you are encouraged to monitor your own working practice using a self-assessment questionnaire, as well as to monitor your own progress by self-marking of non-assessed coursework.

All summative assessment is organised at modular level during the academic year in which the module is taken. Most Statistical Science and Computer Science modules employ a combination of end-of-year written examination and coursework to assess your subject-specific knowledge and academic skills, although some modules are entirely coursework based. Data analysis project work further assesses your intellectual, academic and research skills by means of word-processed written reports and, in the case of the summer research project, an oral presentation.

Coursework is designed to encourage you to develop your knowledge and skills as each module proceeds. Although not all coursework contributes towards formal assessment, it will provide you with the opportunity to demonstrate your intellectual and practical skills in written responses to problem sheets and in oral responses during tutorials, with feedback mainly presented through tutorials / problem classes / workshops, and on an individual basis on request.

On average it is expected that a student spends 150 hours studying for each 15-credit module. This includes teaching time, private study and coursework. Modules are usually taught in weekly two-hour sessions over 10 weeks each term.

For full-time students, typical contact hours are around 12 hours per week. Outside of lectures, seminars, workshops and tutorials, full-time students typically study the equivalent of a full-time job, using their remaining time for self-directed study and completing coursework assignments.

In terms one and two full-time students can typically expect between 10 and 12 contact hours per teaching week through a mixture of lectures, seminars, workshops, crits and tutorials. In term three and the summer period students will be completing their own research project, keeping regular contact with their supervisors.