Postgraduate Course: Topics in Cognitive Modelling (Level 11) (INFR11086)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 11 (Year 4 Undergraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course description||The aim of this course is to expose students to a variety of cognitive models and to discuss competing models for similar problems, i.e. to explore a small number of cognitive domains in depth rather than to aim for broad coverage, as in CCS. The course will focus especially on how to evaluate and compare models against each other and experimental data. Students will be expected to present and critique classic and recent research articles from the cognitive modelling literature, chosen from a list provided by the instructor.
Entry Requirements (not applicable to Visiting Students)
|Prohibited Combinations|| Students MUST NOT also be taking
Topics in Cognitive Modelling (Level 10) (INFR10050)
||Other requirements|| This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.
This course requires familiarity with cognitive and linguistic issues, as evidenced by having taken, e.g., [Computational Cognitive Science or Computational Cognitive Neuroscience or Cognitive Psychology] and [Advanced NLP or Foundations of NLP].
Some mathematics background is required:
- comfort with mathematical notation (e.g. summations, vector notation)
- basic probability theory is strongly recommended (e.g. familiarity with Bayes' Rule and probability distributions)
|Additional Costs|| None
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||Yes
Course Delivery Information
|Delivery period: 2013/14 Semester 2, Available to all students (SV1)
||Learn enabled: No
|Course Start Date
|Breakdown of Learning and Teaching activities (Further Info)
Lecture Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Breakdown of Assessment Methods (Further Info)
|No Exam Information
Summary of Intended Learning Outcomes
|- Demonstrate understanding of classic and current articles on cognitive modelling by summarizing their central ideas and/or results.
- Demonstrate understanding of the relationship between computational models and psychological theories, by being able to critically assess the psychological adequacy of a given model.
- Compare and contrast the strengths and weaknesses of different models of the same behaviour.
- Synthesize information from several papers on the same topic and create a coherent presentation on that topic.
|Written Examination 0|
Assessed Assignments 80
Oral Presentations 20
The assessment will be based on several components:
- Oral presentation (20%): students will (in pairs or small groups, depending on course enrolment) choose 2-3 papers on a given topic to present (topics and papers will be selected from a list provided by the instructor; students may choose a different topic if approved by the instructor).
- Brief paper responses (25%): For each class other than the one with their own presentation, students will submit a brief (1 paragraph) summary of the main content of one paper presented that day, as well as any comments or questions arising from their reading. Responses will be due on the day of each paper's oral presentation, so that those students who have written responses can serve as additional discussants of paper.
- Essay (55%): students will choose an area of cognitive modelling and write an essay based on one or more articles approved by the instructor.
||The syllabus consists of two parts. In the first part, the instructor will provide introductory and background material, as well as information on how to develop skills in reading scientific papers and
presenting them. In the second part, students will present papers on a variety of cognitive models from the literature, chosen from a list provided by the instructor (or approved by the instructor).
Topics covered by the instructor will include
- Introduction and overview of modelling approaches/philosophies.
- Model comparison and evaluation methods.
- Necessary background in probability and information theory.
- How to read, analyse, and present research papers in cognitive modelling (including general oral presentation skills).
- Example presentation(s) of papers.
Topics available for students to present will vary depending on the instructor, but will likely emphasize language learning and processing. Other topics may include visual processing, cognitive development, categorization, memory, decision-making, reasoning, and motor control. For specific topics, see the course web page or contact the instructor directly.
||There is no main textbook for the course. Readings will be chosen from classic and current research papers on cognitive modelling.
Timetabled Laboratories: 0
Non-timetabled assessed assignments: 50
Private Study/Other: 30
|Course organiser||Dr Mary Cryan
Tel: (0131 6)50 5153
|Course secretary||Miss Kate Farrow
Tel: (0131 6)50 2706
© Copyright 2013 The University of Edinburgh - 13 January 2014 4:28 am