HIS32730 The Digital Humanities

Academic Year 2024/2025

The fusion of technology and historical inquiry is revolutionising our understanding of the past. By taking this course, you can embark on an intellectual adventure through this dynamic and rapidly evolving landscape. You will dive deep into the digital transformation of historical studies, and be offerred a way to engage hands-on with some of the cutting-edge techniques that are reshaping research. Supported by your peer group as much as by the coordinator, you will engage directly with the tools and methodologies at the forefront of the field, tackling complex projects such as data harvesting from the catalogues of institutions like the Imperial War Museum, managing relational databases with cases like the slave trade, and mastering visualization techniques that bring data to life.

The module invites you to delve into advanced text analysis and mining, leverage the power of deep learning, and harness Python's simple but robust capabilities to uncover historical insights. Through these immersive sessions, you'll gain not just theoretical knowledge but also practical skills that will serve as both a foundation and a springboard for your own research. Your capstone will be a bespoke research project, overseen by the coordinator. This will be an opportunity to apply what you have learned to a topic that fires your own personal curiosity. This course doesn't just aim to equip you with skills; it's designed to expand your vision of what's possible, both in academic research and real-world applications, while also candidly addressing the limitations of digital methodologies.

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Curricular information is subject to change

Learning Outcomes:

Understand the Role of Technology in Humanities Research: You'll emerge with a clear understanding of the diverse and innovative ways technology is applied in humanities research, opening new avenues for exploration and analysis.

Acquire Practical Skills in Digital Techniques: Not only will you be introduced to pivotal digital humanities techniques, but you'll also gain hands-on experience and confidence in applying these tools to your own projects.

Apply Concepts to Personal Research: You'll develop the ability to adapt and apply general concepts and technical methods to your specific research interests, enhancing the depth and scope of your scholarly work.

Enhance Problem-Solving Abilities: Your problem-solving skills will be sharpened as you navigate the challenges of using and integrating technology in research, enabling you to find innovative solutions to complex issues.

Understand Digital Project Dynamics: You'll gain insights into the construction of major digital humanities projects, recognising the potential opportunities and limitations of various methodologies and how they can impact your work.

Indicative Module Content:

Introductions
Data Harvesting
Relational Database Principles
Relational Database Queries
Data Visualisation including GIS
Deep Learning, Neural Networks & Image Recognition
Text Analysis and Mining
PYTHON
Data Management Principles
Individual Project Presentations & Feedback

Student Effort Hours: 
Student Effort Type Hours
Seminar (or Webinar)

20
Project Supervision

1
Specified Learning Activities

95
Autonomous Student Learning

95
Online Learning

20
Total

231
Approaches to Teaching and Learning:
You will learn primarily through weekly practicals (Active task-based learning; case-based learning), but also
by working on a digital research project of your own supported by one to one meetings with the module coordinator.

The practicals typically involve a short video introduction and detailed step by step instructions. These will be undertaken at your convenience each week. A coffee ZOOM session will be held every Thursday morning to address issues you might be facing, and to give us the opportuntiy to reflect on some of the uses to which digital research techniques can (and cannot) be put.


 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment(Including Essay): Essay plan (1,000 words) based outlining the DH techniques to be employed in the final essay n/a Graded No

20
Assignment(Including Essay): 3,500-4,000 word essay. The subject and scope of the essay must be agreed in advance with the module coordinator. n/a Graded No

50
Participation in Learning Activities: Based on your contributions to seminars and on the grades for the best 6 of 8 x 500-word reflective learning journals outlining your experience of each core practical n/a Graded No

30

Carry forward of passed components
No
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.