2025/26 Undergraduate Module Catalogue

LISS1080 Data Analytics for a Sustainable World

10 Credits Class Size: 30

Module manager: Jenny Sexton
Email: j.l.sexton@leeds.ac.uk

Taught: 1 Jul to 31 Aug View Timetable

Year running 2025/26

Pre-requisite qualifications

GPA of 2.5 (US) or equivalent and enrolled at a university

This module is not approved as a discovery module

Module summary

This module uses real-world datasets to explore the world's most pressing challenges from climate change to global inequality. Throughout the module, you will develop a case study and use global development statistics to quantify progress towards the UN sustainable development goals (SDGs). In 2020, Gapminder ran a project called “Flip your world view” that surveyed people to demonstrate that many people living in Western Europe significantly underestimated the global progress on the sustainable development goals over the last 30 years. This module will equip you with the data literacy skills to examine the real trends in global statistics and understand how choices about how data is presented can perpetuate or challenge existing inequalities. You'll learn to create compelling visualisations and dashboards that tell stories, challenge misconceptions and can influence decisions while navigating the ethical complexities of working with data that affects real people's lives.

Objectives

During this module students will work collaboratively to design a case study about a specific country’s development and global progress towards the UN Sustainable Development Goals.

Students will develop technical proficiency in Excel and Tableau while building awareness of the social impact of data. Students will learn how data collection methods and presentation choices can change how data is interpreted. No prior experience of using these tools is required and the focus will be on accurately communicating with quantitative data in the context of global development.

Learning outcomes

1. Select appropriate visualization types based on data characteristics and communication objectives.

2. Create dashboards and visualizations that communicate data insights effectively to diverse audiences.

3. Identify how data collection methods and presentation choices can perpetuate or challenge existing inequalities.

Skills outcomes

On successful completion of the module students will be able to:

4. Collaborate effectively with peers to interpret and iteratively refine data visualisations. (Work ready, Sustainability)

5. Identify ethical considerations in representing data about real populations and development outcomes. (Sustainability)

6. Demonstrate self-awareness by reflecting on personal contributions to teamwork and identifying areas for development. (Work ready, Academic)

Teaching Methods

Delivery type Number Length hours Student hours
Fieldwork 1 8 8
Fieldwork 1 10 10
Seminar 8 3 24
Independent online learning hours 15
Private study hours 43
Total Contact hours 42
Total hours (100hr per 10 credits) 100

Opportunities for Formative Feedback

Students will prepare their case study during a series of interactive workshops. These will allow students to immediately apply their learning to a component of their assessment and get regularly feedback from their peers and the module lead. Varied daily reflective activities will help students track progress, identify areas for improvement, and build confidence in their iterative approach to data visualization and teamwork.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Group Project Group Project – Students work as a small group (3-4 students per group) to produce a case study. They will each contribute to presenting their work as a group (10 minutes + short Q&A) and submit an annotated copy of their slide deck. 80
Self/Peer Assessment Self Assessment – Students submit a coversheet (max 300 words) that: (i) documents their contribution to the group project, and (ii) identifies a specific point where they adapted their approach in response to feedback or project developments. 20
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: 18/02/2026

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