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
- Demonstrate a practical understanding of established techniques of inquiry in humanities data science to create and interpret knowledge
- Research and apply appropriate digital methods to data-driven projects, paying due attention to responsibility, integrity, and ethics in research and professional practice?
- Critically engage with and evaluate theoretical approaches to combining justice-led and climate-oriented humanities thinking and data science?
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- the role of social and environmental justice in data science practices at an advanced level
- principles and methods of data science in the humanities?
- industry and professional contexts that make use of data science and digital methods
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:
- Perform practical data science techniques that are informed by environmental and social justice principles within professional, legal, and ethical frameworks?
- Apply the use of generalist and specialist software for data analysis, management, and visualisation in appropriate research and professional practice contexts
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 |
|---|---|
| Project supervision | 10 |
| Guided independent study | 290 |
| 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% |
Repeat Information
Repeat type: Internal & External