Undergraduate Programme and Module Handbook 2026-2027
Module COMP3781: Digital Humanities
Department: Computer Science
COMP3781: Digital Humanities
| Type | Open | Level | 3 | Credits | 20 | Availability | Available in 2026/2027 | Module Cap | Location | Durham |
|---|
Prerequisites
- COMP2271 Data Science AND COMP2261 Artificial Intelligence
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- To enable students to understand and critically evaluate the application of computational modelling to problems in the humanities and social sciences.
- To introduce students to algorithms and approaches relevant to the modelling of humanities and social science data.
- For students to explore computational modelling of music as a specific topic in digital humanities in more depth.
Content
- Computational models of text, language and music
- Text and data mining, reasoning about text, language, and music corpora
- Critical evaluation of computational models
- Specific topics in computational modelling of music, for example:
- o Processing music data (symbolic and audio)
- o Modelling rhythm, melody, and harmony
- o Creative music generation and sound synthesis
Learning Outcomes
Subject-specific Knowledge:
- On completion of the module, students will be able to:
- Explain how computational modelling can be applied to humanities and social science research.
- Critically evaluate computational approaches to modelling text and to representing, manipulating, and analysing music.
- Have an understanding of data mining techniques.
Subject-specific Skills:
- On completion of the module, students will be able to:
- Apply computational modelling to humanities and social science data.
- Use standard implementations of representing musical data for manipulation and analysis by computer.
Key Skills:
- On completion of the module, students will be able to:
- Think critically.
- Undertake general problem solving.
- Represent and manipulate symbolic data.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures introduce the principles and techniques covered in the module, and examples of their application to practical cases.
- Computer classes enable students to acquire the necessary coding skills, learn about relevant libraries and packages and receive feedback on their work.
- Formative and summative assessments assess the understanding of core concepts and the application of methods and techniques.
- The first coursework assignment consists of a report with code.
- The second coursework assignment consists of a report, code and audiovisual output.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 20 | 1 per week | 1 hour | 20 | |
| Practicals | 20 | 1 per week | 1 hour | 20 | |
| Preparation and Reading | 160 | ||||
| Total | 200 |
Summative Assessment
| Component: Coursework | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Assignment | 50% | ||
| Assignment | 50% | ||
Formative Assessment:
Example formative exercises are given during the course for familiarising students with relevant packages and libraries. Feedback will be provided to the students on the summative assignments and lecture materials during the practicals.
■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.