Digital Humanities

Teaching language: English
EKA: H910012102
Assessment: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Master

Course ID: H910012101
ECTS value: 10

Date of Approval: 14-04-2020

Duration: 1 semester

Version: Archive

Course ID


ECTS value


Course Title

Digital Humanities

Number of lessons

40 hours per semester

Course Responsible

Name Email Department
Rolf Fagerberg Institut for Matematik og Datalogi, Datalogi
Stefan Jänicke Institut for Matematik og Datalogi, Datalogi

Overall description learning objectives

The described learning objectives for knowledge, skills and competences will be supported by the specific forms of instruction and work methods as described below. At the same time the forms of instruction and work methods are organised in accordance with the form of examination as described under Examination requirements, which is considered to be the most appropriate frame for testing the student's fulfilment  of the learning objectives of the subject.

Learnings objectives - Knowledge

On completion of the course students should have gained knowledge on:

  • digital humanities as a different approach to handle humanities data (e.g. cultural heritage)
  • workflows and models for processing humanities data (e.g. cultural heritage)
  • related state-of-the-art tools from digital humanities
  • computational thinking, including algorithmic thinking and data modeling
  • basics of programming (e.g. in Python)
  • basics of data visualization

Career Management Skills:

  • understand the correlation between the overall competence profile and the academic labour market

Learning objectives - Skills

On completion of the course students should have acquired the skills to:

  • generate data models for humanities information (e.g. cultural heritage)
  • compose digital humanities data sets
  • apply existing state-of-the-art digital humanities tools
  • utilize computational thinking in problem analysis and problem solutions
  • write basic programs for data processing (e.g. in Python)
  • generate visualizations reflecting patterns in humanities data

Career Management Skills:

  • communicate their own skills/competences in writing and verbally
  • identify and work on their own network from a career perspective

Learning objectives - Competences

On completion of the course students should be competent to:
  • assess what type of research questions can be supported by digital means and how
  • discuss strategies to modeling humanities data
  • adapt discussed humanities data processing scenarios to related problems
  • argue on the basis of quantitatively gained results (statistics and visual output)

Career Management Skills:

  • make personal career choices and set career goals


The following main topics are contained in the course:

  • overview of the digital humanities research domain including a discussion of related research projects
  • computational thinking
  • strategies for modeling humanities data and data set creation (e.g., a text corpus)
  • introduction to data visualization
  • quantitative humanities data analysis (e.g. social media)
  • close reading in digital environments
  • distant reading of text corpora with state-of-the-art tools from the digital humanities
  • operating with geospatial-temporal data sets
  • operating with image data sets
  • text alignment and visualization to support research questions in textual criticism
  • network structures in digital humanities and visual analysis thereof
  • basics of programming for data processing including: (1) data structures, (2) control flow element, (3) application of related existing libraries (e.g. in Python)

Through the sessions in Career Management Skills the student will be trained to exploit their own career resources in the project-oriented company. Themes in the sessions includes clarification of competences, written communication in a job seeking context i.e. applications and CV, understanding and using networking in a career perspective, understanding the dynamics in a job interview situation, as well as development of a personal career strategy.   

Forms of instruction and work

The following forms of instruction and work may be applied in the course: Lectures, class teaching, group work, presentations, discussions, exercises, peer and teacher feedback, problem-based learning.

The 4 mandatory sessions in Career Management Skills will be workshop based. 

Teaching is organised in such a way as to support the humanities model for active learning and activating teaching, cf. section Didactic, pedagogical basis and contact to research environment in the curriculum. The teacher will inform students about how study activities are organised on commencement of teaching. 

The activities in the course are primarily aimed at achieving learning objectives and preparing students for the form of examination being a group-based project presentation accompanied with a subsequent short individual 10 minute oral examination but may also consist of written (programming, applying tools, etc.) activities.

The teaching of the course activates the student in the following teaching spaces/learning spaces:

  • Teaching space where the university teacher has the responsibility for planning and is present
  • Study space where the university teacher has the responsibility for planning but is not present
  • Teaching space where the university teacher is present but the students have the responsibility for planning specific sub-activities
  • Study space where the students have the responsibility for planning, and the university teacher is not present


10 ECTS is equivalent to 280 working hours. The working hours are distributed between the activities described in the humanities model and listed under Forms of instruction and work as well as the exam including the preparation of this. The university teacher will provide an indicative distribution of the workload at the beginning of the course.

Teaching language


Examination regulations

Examination requirements


Examination requirements


At the end of the semester


Final examination




Final examination


The oral exam is based on a DH project that will be conducted throughout the semester. Around mid of the semester, students will choose or will be assigned a DH project.

Passed participation in classes in the instructions in Career Management Skills is a prerequisite for participation in the final examination. See examination requirements.

Form of examination

Written report with oral defense


Second examiner: Internal


7-point grading scale


Student Identification Card - Date of birth




Group examination, starting with maximum 10 minutes project presentation. 20 minutes for 1 student, 30 minutes for 2 students, 35 minutes for 3 students, 40 minutes for 4 students.

Assignment handin

Submission on SDU´s digital platform required.

ECTS value


Additional information

Assessment criteria: Considering the method of assessment and the current study level, specific emphasis will be put on the extent to which the student´s performance meets the learning objectives as well as to what extent the student masters the general competence objectives mentioned in the currculum, section Aim of Programme, including any professional profile and specialistions that the course pays special attention to.

The grade will be awarded according to the extent of the fulfilment of the learning objectives as described in the Grading Scale Order (karakterbekendtgørelsen). The grade is given based on both the written project and the oral exam.

Several students may contribute to the assignment:

Yes, a maximum of 4 students. It must be clear from the assignment who is responsible for what parts of the assignment. Individual grades will be given. 

Reexamination takes place in the same way as the ordinary examination.


Type Prerequisite name Prerequisite course
Exam H910011102, Career Management Skills H910011101, Career Management Skills

URL for MyTimetable

08 - 09
09 - 10
10 - 11
11 - 12
12 - 13
13 - 14
14 - 15
Class 1
Stefan Jänicke
Zhiru Sun
15 - 16
Class 1
Stefan Jänicke
Zhiru Sun
16 - 17
Class 1
Stefan Jänicke
Zhiru Sun
17 - 18
Class 1
Stefan Jänicke
Zhiru Sun
Show full time table

Further information

First lesson takes place: [Indsæt oplysning om dato og klokkeslæt]

For further information see MyTimetable.

Courses offered

Period Offer type Profile Programme Semester

Programmes the course description is part of

Profile Programme Semester Period