Undergraduate Course: Causal cognition (PSYL10160)
Course Outline
School | School of Philosophy, Psychology and Language Sciences |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 20 |
ECTS Credits | 10 |
Summary | This course focuses on the psychological processes that underlie human learning, reasoning and decision-making. A major theme is the central role played by causal models in cognition: how people learn models from uncertain data, and use these models to draw inferences and make decisions.
The course will explore the role of causal theories and reasoning in both adults¿ and children¿s cognition, as well as in underpinning the methodologies we use as cognitive psychologists to understand the human mind. |
Course description |
The search for a causal understanding of the world is at the heart of human cognition. It shapes learning throughout development and guides intelligent behaviour by allowing cognisers to predict outcomes, selectively gather information, attribute blame and credit, and imagine hypothetical and counterfactual situations. Causal reasoning is also central to the scientific method, underpinning how we, as scientists, design experiments, build and evaluate theories including the ones we use to describe and understand our own minds.
This course will make sense of the cognitive processes involved in learning and representing a causal model of the world. This will involve introducing formal frameworks from computational cognitive science including Bayesian probability theory and causal graphical models. Alongside this, the course will involve critiquing a number of behavioural experiments that have probed how adults and children learn through interacting with causal systems and how they use their causal knowledge to solve problems and gather rewards.
This course takes a broader, more philosophical, perspective on cognition than many other psychology electives, so offers an opportunity to reflect on psychology as a whole and to connect its topics under a unified scientific perspective. Indeed, the course touches on all six of the British Psychological Society¿s core topic areas. Its primary basis is in cognitive and developmental psychology and statistics. However, it also has clear links to social psychology (through issues of responsibility attribution), differential psychology (though the statistical challenges of inferring the causes and consequences of personality) and biological psychology (through questions of how the structure of our representations reflect the structure of the brain and the environment). The course will provide lots of opportunity to build up critical thinking and academic writing skills.
The course will cover a range of topics related to causality in thought, including (but not limited to):
(a) A history of philosophical ideas about causality.
(b) How causal models support learning, thinking and reasoning.
(c) How learning in humans goes beyond model-free behaviourist and conditioning accounts.
(d) The key difference between learning from observation (correlational data) vs. learning from intervention (experimental data).
(e) The ¿child as scientist¿ theory, and how causal learning shapes learning development across childhood.
(f) The role of time in causal learning and reasoning.
(g) How our causal beliefs and theories colour how we interpret new evidence.
(h) How causal models and counterfactuals shape judgments of responsibility and blame.
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Information for Visiting Students
Pre-requisites | Visiting students should be studying Psychology as their degree major, and have completed at least 3 Psychology courses at grade B or above. We will only consider University/College level courses. Applicants should note that, as with other popular courses, meeting the minimum does NOT guarantee admission. Applicants should note that, as with other popular courses, meeting the minimum does NOT guarantee admission. **Please note that upper level Psychology courses are high-demand, meaning that they have a very high number of students wishing to enrol in a very limited number of spaces.** These enrolments are managed strictly by the Visiting Student Office, in line with the quotas allocated by the department, and all enquiries to enrol in these courses must be made through the CAHSS Visiting Student Office. It is not appropriate for students to contact the department directly to request additional spaces. |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2020/21, Available to all students (SV1)
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Quota: 0 |
Course Start |
Semester 1 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
176 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Mid assessment: A short essay (1000 words), on a question selected from 3 alternatives (or a question of the students own choice agreed with the course organiser).
Final assessment: 10-15 short answer questions. Questions will test understanding and evaluation of theories across all the core topics covered. Student will have 1 week and will have to answer all questions. |
Feedback |
Feedback from the mid-term assessment will help students prepare for final assessment by improving writing skills and understanding of course material. |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Evaluate behavioural evidence for causal model based cognition.
- Demonstrate an understanding of the major recent advances, debates, and challenges in the causal cognition literature.
- Appreciate roles of probability theory and information theory as tools for studying learning and the structure of beliefs.
- Understand and reason about the evidential value of interventions for revealing causal structure.
- Construct and use simple causal models to analyse data.
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Reading List
Gopnik, A. & Schulz, L. (2007) Causal learning: Psychology, philosophy, and computation. Oxford University Press.
Pearl, J. (2018). The Book of Why: The new science of cause and effect. Basic Books.
Sloman, S. A. (2005). Causal Models: How people think about the world and its alternatives, Oxford University Press.
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Additional Information
Graduate Attributes and Skills |
Critical analysis of theories, experiments and results. Engagement with philosophical issues surrounding causality and representation. Understanding of contemporary active debates. Introduction to the roles of probability and information theory in studying cognition's primary functions and processes. Introduction to rational analysis approach to cognitive science. |
Keywords | Psychology,cognition |
Contacts
Course organiser | Dr Neil Bramley
Tel: (0131 6)50 4643
Email: Neil.Bramley@ed.ac.uk |
Course secretary | Ms Alex MacAndrew
Tel: (0131 6)51 3733
Email: alexandra.macandrew@ed.ac.uk |
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