From Visual Awareness to Free Will (PGT) PSYCH5094
- Academic Session: 2021-22
- School: School of Psychology
- Credits: 20
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 1
- Available to Visiting Students: No
- Available to Erasmus Students: No
In this course we will discuss psychological and neuroscientific studies on visual awareness and voluntary actions. We will select and critically assess influential publications in this field and discuss their wider implications.
10 hours of lectures for 5 weeks
Requirements of Entry
At least 2:1 honours degree in a science subject.
There are two pieces of coursework worth 50% each of the overall mark, one presentation and one critical review on a topic relevant to the course (3000 words).
The aims of this interdisciplinary course is to explain and discuss psychological and neuroscientific studies that investigate visual awareness and voluntary decisions. Working in groups and individually we will cover the main philosophical, psychological, and neuroscientific aspects of research on visual awareness, voluntary and spontaneous actions and decisions, and their implications on the concept of free will. In particular we will analyze and evaluate classic as well as recent studies on the prediction of behaviour. We will highlight new techniques and exemplify potential limitations of this research. At the end of the course students should be able to independently evaluate new research developments in this field and to identify positive and negative implications of emerging applications.
Intended Learning Outcomes of Course
By the end of the course students should be able to:
■ critically evaluate basic philosophical constructs surrounding the idea of awareness and free will
■ describe and evaluate the concept of visual awareness and to recognize associated research paradigms
■ reflect critically on the difference between visual awareness and attention
■ detect methodological challenges and limitations when predicting psychological states and behaviour from neuroscientific measurements
■ critically evaluate and illustrate basic principles of predicting behaviour (machine learning) and to apply these principles to different domains (legal, security, market research, learning and teaching)
■ critically and independently evaluate pros and cons of new research and applications in this field
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.