Key facts
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Level 1 - 12 credits - autumn term
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Course description
Course outline
What is it to be an intelligent embodied person? We will look at a number of different `materialist’ theories, concentrating on variants of the computer model, and on neurophysiologically based accounts of mind. In doing so, we will examine some of the basic issues underlying cognitive science as an interdisciplinary study of the mind, taking in topics from psychology, neurosicence, linguistics, computing, artificial intelligence, robotics, evolutionary theory, biology and philosophy along the way.
Learning outcomes
By the end of the course, a successful student should be able to:
1 be familiar with the basics of philosophical and methodological problems in cognitive science.
2 have a preliminary grasp of the way different disciplines (eg psychology, neuroscience, linguistics, computer science and AI, robotics, biology, etc.) collaborate and compete together over their treatment of common themes in cognitive science.
3 be familiar with standard definitions of, and arguments for and against the possible realisation of, Artificial Intelligence (AI) and be able to comment critically on these
4 appreciate the importance of thinking and reasoning clearly, of expressing their ideas with clarity, and critically reflecting upon their own views and prejudices.
5 carry their awareness of interdisciplinarity and the contributions of different disciplines to cognitive science forward to inform the rest of their undergraduate studies in this area.
Assessments
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Essay | Autumn Week 6 | 30.00% |
| Presentation | Autumn Week 10 | 30.00% |
| Essay | Spring Week 2 | 40.00% |
Resit mode of assessment
| Type | Timing | Weighting |
|---|---|---|
| Unseen Examination | Summer Vacation (1 hour 30 minutes) | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
Teaching methods
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Term | LECTURE | 1 hour | 1111111111 |
| Autumn Term | SEMINAR | 1 hour | 1111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.