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COMP31080

Academic Year 2026/2027

Human AI Interaction (Conv) (COMP31080)

Subject:
Computer Science
College:
Science
School:
Computer Science
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Professor David Coyle
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

The ACM define Human Computer Interaction as "a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them.”

This module will introduce key concepts from Human-Computer Interaction and then consider how they can be applied to the design and study of Artificial Intelligence systems. It will draw on theories and methods at the intersection of computer science, behavioural sciences and design, and focuses on the development of AI systems that meet human needs and values.

About this Module

Learning Outcomes:

Knowledge and understanding
- Demonstrate an understanding of the theoretical foundations of Human-Computer Interaction as applied to AI systems
- Identify appropriate methods for the design and evaluation of AI systems

Applying Knowledge and Understanding
- Apply user-centred and value-based methods to identify user needs in AI systems
- Apply appropriate methods to the design of human-centred AI systems
- Apply concepts of human-centred AI to evaluate the impacts of intelligent systems on users and society

Making Judgements
- Identify the opportunities, limitations, and risks of emerging AI technologies

Communications and working skills
- Collaborate effectively in team-based design tasks, demonstrating professional communication and project management skills.

Learning Skills
- Engage independently with literature in the field of Human AI Interaction, demonstrating an ability to self-direct learning.

Indicative Module Content:

UNESCO highlights a set of key competencies that support individuals in their development and support society in achieving the UN Sustainable Development Goals (SDGs). UCD has adapted these competencies and is combining them with others to form a general framework of learning competencies. This module will help you develop the competencies below to the levels specified. 
Learning Competency Additional Information Level

Collaboration

 The ability to learn from others; to understand and respect the needs, perspectives and actions of others (empathy); to understand, relate to and be sensitive to others (empathic leadership); to deal with conflicts in a group; and to facilitate collaborative and participatory problem solving. Competent

Critical Thinking

 The ability to question norms, practices and opinions; to reflect on one’s own values, perceptions and actions. Competent

Systems Thinking

 The ability to recognize and understand relationships; to analyse complex systems; to think of how systems are embedded within different domains and different scales; and to deal with uncertainty. Competent

Strategic

 The ability to collectively develop and implement innovative actions that further sustainability at the local level and further afield. Competent

Anticipatory

 The ability to understand and evaluate multiple scenarios for the future – possible, probable and desirable; to create one’s own visions for the future; to apply the precautionary principle; to assess the consequences of actions; and to deal with risks and changes. Competent

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


Goal Name Description Coverage

Ensure healthy lives and promote well-being for all at all ages 3

Achieve gender equality and empower all women and girls 2

Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation 2
 

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Specified Learning Activities

36
Autonomous Student Learning

40
Total

100

Approaches to Teaching and Learning:
This module will include lectures, assigned reading and group design activities. Students are permitted to use AI to support learning activities, but the use must be cited and documented.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
COMP41740 - Human-Centred AI


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Group Work Assignment: Reading assignments will be due throughout the semester. Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11 Alternative linear conversion grade scale 40% No
20
 No
Exam (In-person): The final exam is based on the assigned reading and lecture materials. Week 12 Alternative linear conversion grade scale 40% No
80
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

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