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PSY2030 : Cognitive Computations: Real and Artificial Intelligence

  • Offered for Year: 2026/27
  • Available to incoming Study Abroad and Exchange students
  • Module Leader(s): Dr Joel Wallenberg
  • Owning School: Psychology
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 2 Credit Value: 20
ECTS Credits: 10.0
European Credit Transfer System
Pre-requisite

Modules you must have done previously to study this module

Code Title
SEL1028Introduction to Language Structure 2: Syntax, semantics and pragmatics
SFY0025Introduction to Computing
Pre Requisite Comment

Pre-Requisites can be relaxed at module leader’s discretion, given relevant background. Single honours Psychology students, for instance, may take this module without the required pre-requisites if they are willing to undertake some supplementary reading.

Co-Requisite

Modules you need to take at the same time

Co Requisite Comment

N/A

Aims

This module explores the Computational Theory of Mind, a foundational idea underlying modern cognitive science. We begin with the question, "What, exactly, is 'computation'?" Students will be able to give a precise answer to this question, and one which holds regardless of whether the computation is performed by a human visual cortex, the human language faculty, a barn owl, or a computing machine. Students will also learn how to mathematically characterise different types of computation, and meaningfully ask what level of computational power is involved in various things humans (and non-human animals) do every day, including language and memory. Probabilistic (or, stochastic) behaviour presents a particularly interesting problem. Along the way, students will learn about Information Theory, a framework which allows one to, for instance, compare the properties of interpersonal communication to those of neuronal communication.

We will explore both the usefulness and limitations of computing machines (including archaic and modern computers) as a metaphor for understanding the brain and a number of its cognitive functions, not accepting the Computational Theory of Mind uncritically. We will also discuss technical, socioeconomic, and ethical issues surrounding “AI,” and come to a more precise understanding of that problematic term and its historical context.

As part of the module, students will develop their own proposals for an open-ended research essay, and will also gain practical coding skills in Python as they complete a collaboratively coded computational project.

Outline Of Syllabus

1. The Computational Theory of Mind
2. What is Computation? Abstract Computing Machines
3. Language and Movement as Simple Machines
4. Concrete Digital Computing
5. Biological Computation
6. Information Theory and Communication
7. Bayes in Human and Artificial Cognition
8. “Good Old Fashioned AI (GOFAI)”, Machine Learning, and LLMs
9. Societal and Ethical Implications of ML and LLMs

10-11. Coding Mini-Module and Project

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture91:3013:30Lecture plus following dialogue session. Dialogues are a bespoke format in which a subset of students are asked questions (which they have discussed beforehand), and engage in a dialogue with the instructor.
Guided Independent StudyAssessment preparation and completion731:0073:00
Guided Independent StudyDirected research and reading661:0066:00
Scheduled Learning And Teaching ActivitiesSmall group teaching91:009:00
Scheduled Learning And Teaching ActivitiesWorkshops22:004:00
Guided Independent StudyProject work91:009:00
Guided Independent StudyStudent-led group activity91:3013:30Preparation for dialogue sessions.
Scheduled Learning And Teaching ActivitiesDrop-in/surgery121:0012:00
Total200:00
Teaching Rationale And Relationship

The module involves four distinct types of skills: the learning of specific declarative information, learning how to critique and dialogue on technical subjects in real-time, technical and mathematical skills, and learning how to code in pairs. For this reason, the module includes lecture periods, dialogue sessions (see above), seminar sessions with problem sets, and workshops for coding.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Oral Presentation302M20A 30 minute, oral, group presentation of a coding project, with Q & A, with other students in attendance. Running code must be submitted prior to the presentation.
Other Assessment
Description Semester When Set Percentage Comment
Essay2M80A semi-independent 2,500 word research essay based on technical literature.
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Prob solv exercises2MWeekly problem sets and discussion questions, to be completed before each week’s seminar. Students will receive these with the syllabus in Week 1.
Assessment Rationale And Relationship

The essay fosters independent thinking, critique, and learning to read literature in the field. The coding project demonstrates competency in computer programming and teamwork, and the presentation plus Q & A is intended to promote the skills of self-critique and open discussion in real-time. The oral session also helps ensure that the code was not generated automatically by a third-party programme. The formative exercises and discussions help the students learn necessary skills for the module, learn to work in a team, critically evaluate concepts, and communicate their views.

If the oral exam is failed or deferred (e.g. with a PEC), the student can sit a resit exam during the Summer resit period.

Reading Lists

Timetable