Study information

Foundations of Human-Centred AI - 2025 entry

MODULE TITLEFoundations of Human-Centred AI CREDIT VALUE15
MODULE CODECOM3032 MODULE CONVENERDr Huma Samin (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 12
Number of Students Taking Module (anticipated)
DESCRIPTION - summary of the module content

You will study foundational concepts in how to use Artificial Intelligence in software systems that that interact with humans. This will involve learning about human psychology including computational theories of how people represent and process knowledge and how we learn and work together. You will learn about topics including, how people make decisions, how they perform perceptual/manual tasks, how human vision works. You will use these theories to build and critically evaluate Artificial Intelligence systems that work with people.

You will attend a weekly class in which an expert in Human-centred AI will lead discussions about a particular topic. You will work individually and in groups to investigate assigned topics and present your work.

Some mathematics and Python knowledge is needed for this module. No prior knowledge of human psychology is required

The module is recommended for interdisciplinary pathways.  

Please note this module has co-requisites of COM3028 and ECM3420, or ECM3401.

AIMS - intentions of the module

The module will cover topics such as recommender systems, emotion detection systems and decision support systems.  It will also cover topics including how to model humans with computer programs using techniques such as deep reinforcement learning, Bayesian inference, optimisation and game theory.

The module will be informed by the latest research in Artificial Intelligence and Human-Computer Interaction.

 

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

1. Explain how Artificial Intelligence can be used to support human-computer interaction.
2. Analyse human requirements and determine appropriate AI solutions.

Discipline Specific Skills and Knowledge

3. Design AI-based software systems that help humans achieve their goals.
4. Comprehension of recent algorithms for human-centred AI. 

Personal and Key Transferable / Employment Skills and Knowledge

5. Synthesise evidence concerning the effectiveness of human-centred AI.
6. Critically evaluate claims about AI-based software systems for interacting with humans.

 

SYLLABUS PLAN - summary of the structure and academic content of the module

The module will cover the following indicative topics:

  • Recommender systems
  • Emotion detection systems
  • Decision support systems
  • Computational modelling of human behaviour

We will explore these topics in context of state-of-the-art AI techniques, including deep reinforcement learning, Bayesian inference, optimisation, and game theory.

 

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 33 Guided Independent Study 117 Placement / Study Abroad 0
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning and Teaching Activities  33 Workshop sessions
Guided Independent Study 60 Coursework preparation and completion 
Guided Independent Study 57 Wider reading and self-study

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Practical exercises 10 All Answers to exercises and verbal 

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 50 Written Exams 50 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Continuous assessment  50 50 hours All  Written
Written exam 50 1 hour All Oral - on request

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Continuous assessment Continuous assessment All Referral/Deferral period
Written exam Written exam All Referral/Deferral period

 

RE-ASSESSMENT NOTES
RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic reading:

  • Howes, A. Jokinen, J., Oulasvirta, A. (2023). Towards machines that understand people. AI Magazine, 44(3), 312-327.

Web-based and electronic resources:

  • ELE 

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 6 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Thursday 19th June 2025 LAST REVISION DATE Thursday 19th June 2025
KEY WORDS SEARCH user-centred design, decision making, explainability, human-computer interaction, artificial intelligence

Please note that all modules are subject to change, please get in touch if you have any questions about this module.