Module overview
The Digital Humanities project enables students to engage with a traditional dissertation or a project responding to an industry problem using humanities data science techniques. Students will be guided by a personal supervisor.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Analyse data and information using a combination of data science techniques and disciplinary knowledge from the humanities
- Research and apply appropriate digital methods to data-driven projects, paying due attention to responsibility, integrity, and ethics in research and professional practice
- Demonstrate a practical understanding of established techniques of inquiry in humanities data science to create and interpret knowledge
- Critically engage with and evaluate theoretical approaches to combining justice-led and climate-oriented humanities thinking and data science
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Exercise self-direction and originality in planning and delivering a substantial project
- Act autonomously in planning and implementing tasks at a professional level
- Deal with complex issues both systematically and creatively by drawing from a range of evidence and knowledge bases
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Apply the use of generalist and specialist software for data analysis, management, and visualisation in appropriate research and professional practice contexts
- Perform practical data science techniques that are informed by environmental and social justice principles within professional, legal, and ethical frameworks
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Evidence a systematic insight into industry and professional contexts that make use of data science and digital methods
- Demonstrate systematic understanding of principles and methods of data science in the humanities
- Critical evaluation of the role of social and environmental justice in data science practices at an advanced level
Syllabus
The preparatory content for the module will include:
- Identifying and developing research questions and/or project requirements
- Engaging in ethical practice surrounding data and research
- Considering audience in the communication of research and its outcomes
Learning and Teaching
Teaching and learning methods
This module primarily relies on guidance and supervision from a personal supervisor. Students will also benefit from tutorial support in conducting independent research and collaborative peer discussion.
| Type | Hours |
|---|---|
| Guided independent study | 290 |
| Project supervision | 10 |
| Total study time | 300 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final project | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Final project | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Final project | 100% |