2025
Introduction to Digital Humanities
Name: Introduction to Digital Humanities
Code: HIS12024L
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
History
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Presentation
Mastering the basic digital tools and discussing the main challenges that IT represent when applied to History and Cultural Heritage.
Sustainable Development Goals
Learning Goals
Knowledge of projects in Digital Humanities and of its scientific and cultural value
Basic technical skills in the use of tools used in digitalization of historical sources and other artifacts
coming from archeological collections, museums, libraries and archives, namely, through the creation,
use and availability of databases, text and network analysis, GIS and 3D virtualization.
Knowledge of informational resources in DH being of interest for historians and heritage technicians
Knowledge of principles of project development in DH in memory institutions
Ability to describe and modelate some type of documents acording to the international standards, using
proper tools.
To deepen the ability for the analysis of the representation of historical information in cultural and
memory institutions
Basic technical skills in the use of tools used in digitalization of historical sources and other artifacts
coming from archeological collections, museums, libraries and archives, namely, through the creation,
use and availability of databases, text and network analysis, GIS and 3D virtualization.
Knowledge of informational resources in DH being of interest for historians and heritage technicians
Knowledge of principles of project development in DH in memory institutions
Ability to describe and modelate some type of documents acording to the international standards, using
proper tools.
To deepen the ability for the analysis of the representation of historical information in cultural and
memory institutions
Contents
1. What are Digital Humanities? Key concepts and resources.
2. Analyses of DH Projects, plataforms and tools.
3. HTML and content modeling
4. Classification schemes
5. Metadata and metadata standards
6. Data collection and quantitative analysis.
7. Data mining and text analysis
8. Network analysis
9. Spacial analysis. Geographic Information Systems
10. Virtual spaces and 3D modeling
2. Analyses of DH Projects, plataforms and tools.
3. HTML and content modeling
4. Classification schemes
5. Metadata and metadata standards
6. Data collection and quantitative analysis.
7. Data mining and text analysis
8. Network analysis
9. Spacial analysis. Geographic Information Systems
10. Virtual spaces and 3D modeling
Teaching Methods
Classes are theoretical and practical in nature, prioritising active, participatory and student-centred learning methodologies. Contents are developed in an environment of experimentation, guided exploration and problem-solving, in order to promote the progressive acquisition of practical and critical skills in the use of Digital Humanities tools.
The sessions combine moments of conceptual framing with practical, individual and collaborative activities, enabling students to apply knowledge, test methodologies, discuss results and develop autonomy in the field of digital know-how. The aim is therefore to foster meaningful, inclusive learning oriented towards the development of transferable skills for different academic, cultural and professional contexts.
The teaching and learning process is continuously supported by the lecturer through personalised guidance, regular feedback and assistance with students? progression, taking into account different learning paces and levels of familiarity with digital tools.
In some sessions, students engage with invited specialists in specific areas of Digital Humanities and with ongoing projects, enabling them to recognise the scientific, social and professional relevance of this field of knowledge. This articulation with real practices and contexts contributes to a critical understanding of Digital Humanities and to the recognition of their application in different professional environments.
In this curricular unit, the use of AI tools is permitted as a learning support, provided that students critically validate all information and maintain human control over the content produced and written. Their use must be explicit and transparent, by stating in the methodology what was used and how it was used, and by citing it correctly. The fabrication of bibliographic references, the wholesale use of text generated by AI models, or the uncritical reproduction of content without human review constitute an ethical and academic violation. Breaches of the principles of transparency and academic integrity will be taken into account in the assessment of the curricular unit.
Acceptable uses of AI include: support in structuring and organising digital content, scientific texts and oral presentations; literature review, provided that it is duly validated through human oversight; support in data analysis and structuring; and the production of synthetic digital outputs. The use of false or insufficient references will be taken into consideration in the assessment.
Unacceptable uses include: submitting assignments, final outputs or presentations produced entirely by AI; copying and pasting material generated by AI; writing assignments using AI-generated text as the final submitted work; fabricating bibliographic references or citations without verification; and completing assessed work through AI.
The sessions combine moments of conceptual framing with practical, individual and collaborative activities, enabling students to apply knowledge, test methodologies, discuss results and develop autonomy in the field of digital know-how. The aim is therefore to foster meaningful, inclusive learning oriented towards the development of transferable skills for different academic, cultural and professional contexts.
The teaching and learning process is continuously supported by the lecturer through personalised guidance, regular feedback and assistance with students? progression, taking into account different learning paces and levels of familiarity with digital tools.
In some sessions, students engage with invited specialists in specific areas of Digital Humanities and with ongoing projects, enabling them to recognise the scientific, social and professional relevance of this field of knowledge. This articulation with real practices and contexts contributes to a critical understanding of Digital Humanities and to the recognition of their application in different professional environments.
In this curricular unit, the use of AI tools is permitted as a learning support, provided that students critically validate all information and maintain human control over the content produced and written. Their use must be explicit and transparent, by stating in the methodology what was used and how it was used, and by citing it correctly. The fabrication of bibliographic references, the wholesale use of text generated by AI models, or the uncritical reproduction of content without human review constitute an ethical and academic violation. Breaches of the principles of transparency and academic integrity will be taken into account in the assessment of the curricular unit.
Acceptable uses of AI include: support in structuring and organising digital content, scientific texts and oral presentations; literature review, provided that it is duly validated through human oversight; support in data analysis and structuring; and the production of synthetic digital outputs. The use of false or insufficient references will be taken into consideration in the assessment.
Unacceptable uses include: submitting assignments, final outputs or presentations produced entirely by AI; copying and pasting material generated by AI; writing assignments using AI-generated text as the final submitted work; fabricating bibliographic references or citations without verification; and completing assessed work through AI.
Assessment
Assessment is conducted through two modalities.
Continuous assessment is based exclusively on practical assignments covering the different course topics, with a maximum of three assignments. The final grade will be calculated as follows:
10% ? Attendance and participation
30% ? Assignment on the digitisation process and artificial intelligence
30% ? Data and databases
30% ? Digital cartography
Final assessment is conducted through a written final examination, consisting predominantly of practical exercises (100%).
If deemed necessary to verify the extent to which the student has developed the knowledge and competences specified for the curricular unit, the teaching team may require the student to take an oral examination, in accordance with Article 110(13) of the Academic Regulations of the University of Évora. The conditions set out in Article 116(4) and Article 118(1) of the same Regulations shall be duly ensured.
The oral examination shall account for 80% of the final grade for the curricular unit
Continuous assessment is based exclusively on practical assignments covering the different course topics, with a maximum of three assignments. The final grade will be calculated as follows:
10% ? Attendance and participation
30% ? Assignment on the digitisation process and artificial intelligence
30% ? Data and databases
30% ? Digital cartography
Final assessment is conducted through a written final examination, consisting predominantly of practical exercises (100%).
If deemed necessary to verify the extent to which the student has developed the knowledge and competences specified for the curricular unit, the teaching team may require the student to take an oral examination, in accordance with Article 110(13) of the Academic Regulations of the University of Évora. The conditions set out in Article 116(4) and Article 118(1) of the same Regulations shall be duly ensured.
The oral examination shall account for 80% of the final grade for the curricular unit
Teaching Staff
- Ana Sofia Vieira Ribeiro
- Maria Fernanda de Olival [responsible]
Accreditations and Certifications
