Module manager: Rachel Oldroyd
Email: r.oldroyd@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
| GEOG1400 | Digital Geographies |
This module is not approved as a discovery module
This module is designed to provide advanced training in social data statistics, spatial data analysis, and the theory of Geographical Information Systems (GIS). Weekly lectures and computer practicals introduce students to the application of advanced data analytics, visualisation, and mapping techniques to novel and traditional data. It also considers conceptual understandings of the representation of space. Students will develop advanced skills in summarising, visualising, and manipulating data as well as exploring spatial data relationships.
The overall aims of this module are to:
- provide students with advanced training in social data statistics, spatial data analysis and the theory behind Geographical Information Systems (GIS)
- enable students to develop advanced skills in summarising, visualising and manipulating data as well as exploring spatial data relationships
- develop core GIS, mapping and statistics skills in GIS and related theoretical approaches
- introduce students to the potential uses and applications of spatial data
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Identify and employ appropriate spatial analysis techniques to achieve specific tasks
2. Derive associations between variables using appropriate statistical analysis techniques
3. Recall the principles and advantages of different approaches for generating surfaces from data points
4. Identify and employ visualisation techniques appropriate for various data types
Skills learning outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
5. Critical thinking: The ability to gather spatial and social data from a range of sources, analyse, and interpret data to aid understanding and anticipate problems. To use reasoning and judgement to identify needs, make decisions, solve problems, and respond with actions.
6. Digital proficiency and productivity: The ability to select, use, and troubleshoot appropriate GIS technologies to achieve specific tasks
7. Technical skills: The ability to use technical skills in relation to social and spatial data which extend beyond traditional desktop GIS software
8. Digital creation, problem-solving and innovation: The ability to use digital technology and techniques to create digital items (such as maps and visualisations), and the willingness to engage with new practices and perspectives to solve problems, make decisions and answer questions.
Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Drop-in Session | 2 | 1 | 2 |
| Lectures | 7 | 1 | 7 |
| Practicals | 7 | 2 | 14 |
| Private study hours | 77 | ||
| Total Contact hours | 23 | ||
| Total hours (100hr per 10 credits) | 100 | ||
During interactive lectures, students understanding is assessed by use of polling software and comprehension of short tasks.
Each practical is formative and has self-test questions with answers against which students can test their understanding and data manipulation skills: students will be able to compare their “results” and understanding with model answers.
Staff will be able to monitor performance and provide formative feedback in practicals.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Assignment | coursework | 100 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
The reading list is available from the Library website
Last updated: 4/29/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team