Undergraduate Course: Informatics 1 - Cognitive Science (INFR08020)
|School||School of Informatics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 8 (Year 1 Undergraduate)
||Availability||Available to all students
|Summary||This course is designed as a first introduction to Cognitive
Science. It will provide a selective but representative overview of
the subject, suitable for
all interested students, including students on the Cognitive Science
degrees and external students.
The aim of the lecturing team is to present a unified view of the
field, based on a computational approach to analysing cognition. The
material is organized by cognitive function (e.g., language, vision),
rather than by subdiscipline (e.g., psychology, neuroscience).
The course covers language, vision and attention, memory, motor
control and action, and reasoning and generalization. All topics will
be presented from a computational point of view, and this perspective
will be reinforced by lab sessions in which students use
implementations of cognitive models. The course will also provide a
basic grounding in the methods of Cognitive Science, focusing on
computational modelling and experimental design.
The syllabus covers the following topics.
They are listed separately here, but in some cases they will be
presented in an interleaved fashion:
- the language faculty
- models of linguistic data, words and rules theory
- Connectionist models of language
- language acquisition: speech segmentation, word learning, learning
- categorization and models of word meaning
- understanding sentences
- the anatomy of vision, neural correlates of visual perception
- Marr's model
- fine vs. coarse coding
- face recognition
3. Memory and Attention
- types of memory, memory impairments, models of memory
- attention, neglect
4. Cognition and neuroscience
- an introduction to cognitive neuroscience
- some philosophical perspectives on the brain
5. Reasoning and generalization
- inductive reasoning
- fallacies and (ir)rationality
- models of abstraction and generalisation
- theory formation and the origins of knowledge
Note that this course is intended to give a high-level introduction to
the topics listed; subsequent courses (e.g., Cognitive Modeling) will
then provide a more detailed coverage.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| None
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2015/16, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 30,
Seminar/Tutorial Hours 10,
Supervised Practical/Workshop/Studio Hours 10,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Additional Information (Assessment)
There will be three assessed assignments in this course, these will
- practical exercises in which students are provided with
implemented cognitive models they have to explore and modify;
- essay questions in which students analyze empirical or conceptual
problems in cognitive science.
The practical exercises will be supported by lab sessions in which
students learn how to use implemented cognitive models. Where
possible, the assignments will employ pre-existing modeling tools
(e.g., neural network simulators, probabilistic modeling tools).
The essay questions will be supported by tutorials in which students
are able to clarify and discuss the materials covered in the lectures.
||Hours & Minutes
|Main Exam Diet S2 (April/May)||2:00|
|Resit Exam Diet (August)||2:00|
On completion of this course, the student will be able to:
- Demonstrate knowledge of key areas of cognitive science, and be able to take an integrated, rather than disciplinary perspective on the field.
- Evaluate the most important conceptual problems in cognitive science and discuss the solutions that have been proposed.
- Analyze and modify simple computational models in a variety of modeling paradigms.
- Demonstrate understanding of experimental design and statistics and apply it to simple problems in cognitive science.
- Understand how cognition and cognitive science is societally situated and the ethical issues raised in researching cognition
|Graduate Attributes and Skills
|Additional Class Delivery Information
||Total Hours: 200 ( Lecture Hours 30, Seminar/Tutorial Hours 10,
Supervised Practical/Workshop/Studio Hours 10, Summative Assessment
Hours 2, Programme Level Learning and Teaching Hours 4, Directed
Learning and Independent Learning Hours 144 )
|Course organiser||Prof Maria Lapata
Tel: (0131 6)50 4416
|Course secretary||Mr Gregor Hall
Tel: (0131 6)50 5194
© Copyright 2015 The University of Edinburgh - 18 January 2016 4:12 am