2026/27 Undergraduate Module Catalogue

DESN1184 Visual Cultures, and Vivid Future

20 Credits Class Size: 100

Module manager: Dr Arjun Khara
Email: a.khara@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2026/27

This module is not approved as a discovery module

Module summary

This module introduces students to the ways in which artificial intelligence is producing, shaping, and mediating images, videos, and animation, along with the cultural experiences and consumption trends surrounding such machine-mediated media over the last decade. From generative art and AI-driven advertising to deepfakes, memes, and interactive installations, visual culture is increasingly being co-produced by humans and generative algorithms. This module enables students to develop their creative, critical, and cross-cultural literacies required to navigate the intersection of shifting trends and practices, while collaborating with AI platforms to explore how generative technologies can reconfigure the future of design and contemporary visual culture. Please note this is an optional module and runs subject to enrolments. If a low number of students choose this module, then the module may not run and you may be asked to choose another module.

Objectives

The module’s three key objectives / aims are:
AIM1 • Introduce students to the role of artificial intelligence in shaping contemporary visual cultures and media and explore the implications for design practice
AIM2 • Encourage critical reflection on issues of aesthetics, authorship, authenticity, ethics, and bias in AI-mediated cultural artefacts
AIM3 • Develop students’ confidence in articulating their unique perspectives as emerging world-builders by connecting exploration with critical reflection on the future role of AI as a creator / collaborator / competitor.

Learning outcomes

On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Analyse how creative technologies are being used in contemporary visual culture while recognising the social, cultural, and ethical implications
2. Understand how GenAI platforms can be used co-produce creative visual outcomes evidencing exploratory approaches to design practice and cultural critique.
3. Reflect critically on the challenges and opportunities AI presents for design, including questions of authorship, originality, and cultural meaning.

On successful completion of the module students will have demonstrated the following skills learning outcomes:
4. Identify and experiment proficiently with generative AI platforms to test, adapt, and refine visual ideas, demonstrating openness to discovery and iteration
5. Curate and present visual materials in a structured format, evidencing a strong design process and criticality of control over AI-driven creative outputs

Teaching Methods

Delivery type Number Length hours Student hours
Lectures 10 1 10
Practicals 10 3 30
Private study hours 160
Total Contact hours 40
Total hours (100hr per 10 credits) 200

Opportunities for Formative Feedback

Students on this module will receive regular feedback starting as they work on their assessment. Students will present initial concepts or ideas through short pitches and sketches during the practicals. Tutors and peers will provide dialogic feedback on the clarity of concepts, alignment with design principles, and potential cultural implications. These will take place during the seminars in mixed-mode sessions. Students will be encouraged to bring draft materials, including their research and findings into visual cultures and technologies for tutor and peer review. Feedback will be aimed at strengthening both the creative outcomes and the critical underpinnings of the work. Progress will be monitored across the semester through these checkpoints, ensuring that students feel supported in iterating their designs and building confidence in articulating the rationale behind their decisions.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Coursework Wiki 100
Total percentage (Assessment Coursework) 100

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading List

Check the module area in Minerva for your reading list

Last updated: 30/04/2026

Errors, omissions, failed links etc should be notified to the Catalogue Team