Postgraduate Course: Seminar in Cognitive Modelling (UG) (INFR11237)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course follows the delivery and assessment of Seminar in Cognitive Modelling (INFR11210) exactly. For the academic year 2026/2027 undergraduate students are able to register on INFR11210. |
| Course description |
This course follows the delivery and assessment of Seminar in Cognitive Modelling (INFR11210) exactly. For the academic year 2026/2027 undergraduate students are able to register on INFR11210.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | This course follows the delivery and assessment of Seminar in Cognitive Modelling (INFR11210) exactly. For the academic year 2026/2027 undergraduate students are able to register on INFR11210.
This course is only open to students in Informatics and PPLS whose DPT lists this course. PPLS students and PTs should take note of the "other requirements" if they cannot take the recommended co-requisite.
The course assumes knowledge of cognitive science and, by the second semester, knowledge of linear algebra (vectors / matrix multiplication, orthogonality, eigenvectors), probability theory (discrete and continuous univariate random variables, expectations, Bayes rule), statistics (linear / logistic regression) and model evaluation.
Data visualization and programming experience will be useful but there is no required programming. |
Information for Visiting Students
| Pre-requisites | The course assumes knowledge of cognitive science and, by the second semester, knowledge of linear algebra (vectors / matrix multiplication, orthogonality, eigenvectors), probability theory (discrete and continuous univariate random variables, expectations, Bayes rule), statistics (linear / logistic regression) and model evaluation.
Data visualization and programming experience will be useful but there is no required programming. |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- demonstrate understanding of a range of classic and current articles in cognitive science / modelling by summarizing and critiquing their central ideas and / or results
- demonstrate understanding of the relationship between computational models and cognitive theories, by being able to critically assess the theoretical adequacy of a given model
- compare and contrast the strengths and weaknesses of different models of the same behaviour
- search the literature and synthesize information from several papers on the same topic and create a coherent oral presentation on that topic
- communicate (written and oral) key findings in cognitive science/modelling to inter-disciplinary audiences
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Additional Information
| Course URL |
https://opencourse.inf.ed.ac.uk/scm |
| Graduate Attributes and Skills |
Critical / analytical thinking, knowledge integration and application, independent learning, creativity, interpersonal skills, verbal, written and cross-disciplinary communication |
| Keywords | SCM,cognitive science,cognitive modelling,science communication |
Contacts
| Course organiser | Dr Bonan Zhao
Tel:
Email: bzhao2@exseed.ed.ac.uk |
Course secretary | Ms Lindsay Seal
Tel: (0131 6)50 5194
Email: lindsay.seal@ed.ac.uk |
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