MO5162 Skills in Digital History: Maps and Text
Academic year
2024 to 2025 Semester 1
Curricular information may be subject to change
Further information on which modules are specific to your programme.
Key module information
SCOTCAT credits
30
SCQF level
SCQF level 11
Planned timetable
To be arranged.
Module coordinator
Dr K M Lawson
Module description
This digital humanities module provides students with an introduction to digital mapping in the form of historical GIS (HGIS) and computational approaches to the analysis of text. No specific technical knowledge is required before taking the course. Students will gain proficiency in the use of the software package QGIS to digitise historical maps, visualise and analyse geographical information, and produce rich maps for the illustration and heuristic exploration of historical information. In order to analyse large bodies of digitised text, students will learn regular expressions and named-entity extraction, carry our frequency and sentiment analysis, and the module will offer a survey of more advanced approaches such as topic modeling and the classification of texts. Finally, students will engage with scholarship in the critical digital humanities in order to critically evaluate the challenges and shortcomings of some of these methodologies.
Assessment pattern
100% coursework
Re-assessment
100% coursework
Learning and teaching methods and delivery
Weekly contact
7 x 2-hour seminars and 4 x 2-hour practical classes over the semester.
Scheduled learning hours
20
Guided independent study hours
280
MO5162 Skills in Digital History: Maps and Text
Academic year
2024 to 2025 Semester 2
Curricular information may be subject to change
Further information on which modules are specific to your programme.
Key module information
SCOTCAT credits
30
SCQF level
SCQF level 11
Planned timetable
To be arranged.
Module coordinator
Dr K M Lawson
Module description
This digital humanities module provides students with an introduction to digital mapping in the form of historical GIS (HGIS) and computational approaches to the analysis of text. No specific technical knowledge is required before taking the course. Students will gain proficiency in the use of the software package QGIS to digitise historical maps, visualise and analyse geographical information, and produce rich maps for the illustration and heuristic exploration of historical information. In order to analyse large bodies of digitised text, students will learn regular expressions and named-entity extraction, carry our frequency and sentiment analysis, and the module will offer a survey of more advanced approaches such as topic modeling and the classification of texts. Finally, students will engage with scholarship in the critical digital humanities in order to critically evaluate the challenges and shortcomings of some of these methodologies.
Assessment pattern
100% coursework
Re-assessment
100% coursework
Learning and teaching methods and delivery
Weekly contact
7 x 2-hour seminars and 4 x 2-hour practical classes over the semester.
Scheduled learning hours
20
Guided independent study hours
280