This course provides students an opportunity to explore their choice of topic in cognitive science in depth while honing their science communication skills and broadly surveying the foundations of cognitive science.
The course aims to expose students to a variety of cognitive models and modelling approaches. For example readings will touch on Bayesian models, rational and resource-rational, heuristic models, neural network approaches, reinforcement learning, graphical models, agent based models, drift diffusion models, hidden Markov models, Markov decision processes, quantum models, large language models, simulator models.
Students will be expected to discuss, present, and critique classic and recent research articles from the cognitive modelling literature, including papers chosen by the instructor as well as papers of their own choosing.
Learning objectives:
Special thanks to Neil Bramley, who organized last year’s version of this course. Many aspects of course design, readings, and website content and structure are from his edition.
Semester 2
All students will be assigned to one of two groups (to be determined). Each group will (mostly) alternate having presentation days and discussion days.
Week | Day | Topic | Required Reading | Group1 Activity | Group2 Activity |
---|---|---|---|---|---|
1 | Tue, Jan 14 | Welcome back & Ant problem solving | — | meet all together | meet all together |
1 | Thu, Jan 16 | Marshmallow Challenge | — | meet all together | meet all together |
2 | Tue, Jan 21 | Dr. Zhao research presentation | — | meet all together | meet all together |
2 | Thu, Jan 23 | Essay time - Office hours | — | meet all together | meet all together |
3 | Tue, Jan 28 | Essay time - Peer feedback activity | — | meet all together | meet all together |
3 | Thu, Jan 30 | Essay time - Office hours (no portfolio - class attendance optional) | — | meet all together | meet all together |
4 | Tue, Feb 04 | presentation day | discussion day | ||
4 | Thu, Feb 06 | discussion day | presentation day | ||
5 | Tue, Feb 11 | presentation day | discussion day | ||
5 | Thu, Feb 13 | discussion day | presentation day | ||
— | Tue, Feb 18 | reading week - no class | — | — | — |
— | Thu, Feb 20 | reading week - no class | — | — | — |
6 | Tue, Feb 25 | presentation day | discussion day | ||
6 | Thu, Feb 27 | discussion day | presentation day | ||
7 | Tue, Mar 04 | presentation day | discussion day | ||
7 | Thu, Mar 06 | discussion day | presentation day | ||
8 | Tue, Mar 11 | presentation day | discussion day | ||
8 | Thu, Mar 13 | discussion day | presentation day | ||
9 | Tue, Mar 18 | presentation day | discussion day | ||
9 | Thu, Mar 20 | discussion day | presentation day | ||
10 | Tue, Mar 25 | presentation day | discussion day | ||
10 | Thu, Mar 27 | discussion day | presentation day | ||
11 | Tue, Apr 01 | presentation day | discussion day | ||
11 | Thu, Apr 03 | discussion day | presentation day |
All students are assigned to one of two groups: Sharks or Dolphins (see Learn for group assignments). Each group will (mostly) alternate having presentation days and discussion days.
Week | Day | Topic | Required Reading | Sharks Activity | Dolphins Activity |
---|---|---|---|---|---|
1 | Tue, Sep 17 | Welcome, and What Is Cognitive Science? | — | full class meeting | full class meeting |
1 | Thu, Sep 19 | A Story about Models of Visual Thinking | — | full class meeting | full class meeting |
2 | Tue, Sep 24 | CRUM | • Thagard 2005 | discussion day | discussion day |
2 | Thu, Sep 26 | Representation | • Markman 1998 | discussion day | discussion day |
3 | Tue, Oct 01 | People | • Henrich et al. 2010 (p. 1-23) | no class meeting: see Learn for activities |
no class meeting: see Learn for activities |
3 | Thu, Oct 03 | Guest Presentations | • Murphy 2004 - Chapter 2 | full class meeting: guest presentations by our TAs! |
full class meeting: guest presentations by our TAs! |
4 | Tue, Oct 08 | Concepts & Categories | • Murphy 2004 - Chapter 3 | discussion day | presentation day • Medin & Schaffer 1978; • Love et al 2004 |
4 | Thu, Oct 10 | Concepts & Categories | • Spelke 1990 | presentation day • Medin & Schaffer 1978; • Love et al 2004 |
discussion day |
5 | Tue, Oct 15 | Objects & Events | • Zacks & Tversky 2001 | discussion day | presentation day • Munakata et al 1997; • Reynolds et al 2007 |
5 | Thu, Oct 17 | Objects & Events | • Tolman 1948; • Peer et al. 2021 |
presentation day • Munakata et al 1997; • Reynolds et al 2007 |
discussion day |
6 | Tue, Oct 22 | Space & Number | • Feigenson et al 2004; • Pica et al 2004; • Frank et al 2008 |
discussion day | presentation day • Kuipers 2000; • Dehaene & Changeux 1993 |
6 | Thu, Oct 24 | Space & Number | • Gopnik et al 2004 | presentation day • Kuipers 2000; • Dehaene & Changeux 1993 |
discussion day |
7 | Tue, Oct 29 | Causality & Time | • Elman 1990 | discussion day | presentation day • Coenen et al 2015; • Bramley et al 2018 • Quillien & Lucas 2023 |
7 | Thu, Oct 31 | Causality & Time | • Tversky & Kahneman 1981; • Todd & Gigerenzer 2000 (main article - first 15 pages only) |
presentation day • Coenen et al 2015; • Bramley et al 2018 |
discussion day |
8 | Tue, Nov 05 | Decision Making & Emotions | • Lerner et al. 2015 | discussion day | presentation day • Smith & Ratcliff 1995; • Wallach et al 2010 |
8 | Thu, Nov 07 | Decision Making & Emotions | • Miller 1956; • Baddeley 2003 |
presentation day • Smith & Ratcliff 1995; • Wallach et al 2010 |
discussion day |
9 | Tue, Nov 12 | Short & Long Term Memory | • Collins & Quillian 1969; • Collins & Loftus 1975 |
discussion day | presentation day • Anderson 1996; • Farah & McClelland 1991 |
9 | Thu, Nov 14 | Short & Long Term Memory | • Gentner 1983; • Slade 1991 |
presentation day • Anderson 1996; • Farah & McClelland 1991 |
discussion day |
10 | Tue, Nov 19 | Analogy & Theory of Mind | • Dennett 1981 | discussion day | presentation day • Doumas 2008; • Baker et al 2009 |
10 | Thu, Nov 21 | Analogy & Theory of Mind | • Tomasello 1999; • Kirby et al. 2008 |
presentation day • Doumas 2008; • Baker et al 2009 |
discussion day |
11 | Tue, Nov 26 | Culture & Cognition | • Shore 1998 - Intro & Chapter 1 | discussion day | presentation day • Kirby 2000; • Muthukrishna & Schaller 2020 |
11 | Thu, Nov 28 | Culture & Cognition | • Lakoff & Johnson 1980; • Shore 1998 - Chapter 2 |
presentation day • Kirby 2000; • Muthukrishna & Schaller 2020 |
discussion day |
Slides of lectures will be made available via links on this website.
Each lecture/seminar will include 1 or more required readings, to be completed by students prior to coming to class. PDFs of all readings can be found on Learn.
(Note: These guidelines have been revised after the first week of the semester.)
On discussion days:
On presentation days:
The course assumes knowledge of cognitive science and, by the second semester, knowledge of probability theory (discrete and continuous univariate random variables, expectations, Bayes rule), basic linear algebra (vectors/matrix multiplication, orthogonality, eigenvectors), statistics (linear/logistic regression) and model evaluation as would be acquired in Computational Cognitive Science.
Data visualisation and programming experience will be useful but there is no required programming.
The assessment for this course consists of:
Students will also be required to make a presentation in the first semester and will be provided feedback.
When you sign up for the course, you will have access to:
For general questions, please use the Learn discussion forums. If you have specific questions for the teaching team, please email the course organizer Maithilee Kunda, making sure to include “SCM” in the subject line.
Individual assignments must be completed individually, you may not directly share or discuss answers / code with anyone other than the instructors and tutors. You are welcome to discuss the problems in general and ask for advice.
Certain assignments may allow collaboration, only when explicitly allowed in the assignment instructions.
The University takes academic misconduct very seriously and is committed to ensuring that so far as possible it is detected and dealt with appropriately. Find out more about the University’s official policies around academic misconduct here.
Cheating or plagiarising on assignments, lying about an illness or absence and other forms of academic dishonesty are a breach of trust with classmates and faculty, violate the University policies, and will not be tolerated. Such incidences will result in a 0 grade for all parties involved. Additionally, there may be penalties to your final class grade along with being reported to the School Academic Misconduct Office.
All work is due on the stated due date. Due dates are there to help guide your pace through the course and they also allow us (the course staff) to return marks and feedback to you in a timely manner. However, sometimes life gets in the way and you might not be able to turn in your work on time.
Extensions: The University has an extension policy whereby you can request an extension for certain assignments where late work is accepted. If your extension request is approved, you can turn in the assignment late and not incur the late penalty.
In this course, you can request an extension for the essay. To request an extension you must visit the Extensions website and Apply for an extension there. Note that decisions are made by an external committee, not the course teaching staff, so requests for extensions must go through this form and not through course organisers and lecturers.
Portfolios (reading responses and group discussions) are not eligible for extensions. However, we have a generous policy of dropping a number of portfolio entries each semester; see the Portfolio section for details.
Presentations are also not eligible for extensions. If you are ill, you get one chance to reschedule.
Special circumstances: You can think of special circumstances as one level above an extension request, where there is a documented reason why you’re unable to complete any assignment in the course. Special circumstances decisions are made at the end of the semester by an external committee. To request a special circumstances waiver you must visit the Special Circumstances website and Apply for special circumstances there.
If you’re not sure whether your personal circumstance should be filed under an extension or special circumstances, we recommend you reach out to your Cohort lead and/or Student Support Team (inf-sst@inf.ed.ac.uk).
It is our intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength, and benefit. It is our intent to present materials and activities that are respectful of diversity: gender identity, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, and culture. Your suggestions are encouraged and appreciated. Please let us know ways to improve the effectiveness of the course for you personally, or for other students or student groups.
Furthermore, we would like to create a learning environment for our students that supports a diversity of thoughts, perspectives and experiences, and honours your identities (including gender identity, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, and culture). To help accomplish this:
No – you will pass if (and only if) your combined mark is above 40%.
Please email the course organiser (Maithilee Kunda), with “SCM COURSE CONFLICT” in the subject line, and include the following information:
Please email this information as early in the semester as possible, and no later than the end of week 2.
For the portfolio, there are no extensions. You can miss a few entries per semester, no questions asked; see the Portfolio section for details.
For the presentation, there are no extensions. If you are ill, you get one chance to reschedule. That said, special circumstances happen and are handled by the ITO.
For the essay, the ITO is responsible for granting extensions. They can grant extensions that are requested BEFORE the assignment deadline.
For more information, see the school’s guidance on late coursework and extension requests.
If you submitted a partially complete assignment before the deadline, that is what will be marked. If you submitted an empty assignment or the wrong file before the deadline, you can submit after the deadline but it will be treated as a late submission. After you submit an assignment, download and open what you submitted to be sure you submitted the correct file.
No.
All of the readings are be available online via the course Learn page.
Yes. This is a seminar course 😀
You need to show up to class ready to discuss the readings. That doesn’t mean you have to understand everything or have a strong opinion about it.
This website was prepared with accessibility in mind. Accessibility was assessed using WAVE on multiple browsers. Of course standards are not perfect and we aim to make this course accessible to all students. Therefore, please email the course organizer (Maithilee Kunda) if you have any accessibility issues that we can try and address.