Unit Medieval sources, digital methods, and artificial intelligence for historical research
- Course
- Italian, classical studies and european history
- Study-unit Code
- A006257
- Curriculum
- In all curricula
- Teacher
- Stefania Zucchini
- Teachers
-
- Stefania Zucchini
- Hours
- 36 ore - Stefania Zucchini
- CFU
- 6
- Course Regulation
- Coorte 2026
- Offered
- 2026/27
- Learning activities
- Affine/integrativa
- Area
- Attività formative affini o integrative
- Sector
- HIST-01/A
- Type of study-unit
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- The course aims to provide both theoretical knowledge and practical skills for the analysis of medieval sources through digital tools and artificial intelligence applications. Particular attention will be devoted to the entire workflow of digital historical research: the identification and selection of sources, digitisation, the automated transcription of handwritten texts through Handwritten Text Recognition (HTR) systems, data extraction and organisation, the creation of historical databases, and the quantitative and qualitative analysis of historical information. The course includes hands-on laboratory activities based on original medieval sources or their digital reproductions.
- Reference texts
- 1) Ian Milligan, The Transformation of Historical Research in the Digital Age, Cambridge University Press, Cambridge, 2022 (Open Access).
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/30DFBEAA3B753370946B7A98045CFEF4/9781009012522AR.pdf/transformation_of_historical_research_in_the_digital_age.pdf
https://www.cambridge.org/core/elements/transformation-of-historical-research-in-the-digital-age/30DFBEAA3B753370946B7A98045CFEF4
2) G. Di Tonto, "Cultura digitale. Intelligenza artificiale, ricerca e insegnamento della storia", in C. Saltarelli, M.C. Sampaolesi (a cura di), Quale e quanta storia? La didattica della storia per un curricolo verticale che forma cittadinanza e pensiero critico, Mnamon, 2025, pp. 121-138
3) M. Valleriani, "Studi storici con l'IA: verso le Digital Humanities", Agenda Digitale, 2023: https://www.agendadigitale.eu/cultura-digitale/studi-storici-con-lia-verso-le-digital-humanities/
Additional scholarly readings on the use of Large Language Models (LLMs), Handwritten Text Recognition (HTR), and artificial intelligence in historical research, selected by the lecturer, will be made available throughout the course. - Educational objectives
- The course aims to provide introductory knowledge and basic skills in the field of digital historical research, with particular attention to the use of automated transcription tools, the organisation of historical data, and the applications of artificial intelligence in historical research.
By the end of the course, students will be able to:
understand the fundamental principles of the automated transcription of historical sources and the functioning of Handwritten Text Recognition (HTR) systems;
use, at an introductory level, selected digital tools for the transcription and organisation of information extracted from historical sources;
understand the main applications of artificial intelligence in historical research;
critically assess the potential and limitations of artificial intelligence tools used in the analysis of historical sources;
organise and structure simple datasets derived from digitised historical sources;
critically interpret the results produced through digital tools and automated procedures;
develop a methodological awareness of the opportunities and challenges associated with the use of digital technologies and artificial intelligence in historical research.
The learning outcomes are consistent with the Dublin Descriptors relating to knowledge and understanding, applying knowledge and understanding, making judgements, communication skills, and learning skills. - Prerequisites
- A general knowledge of medieval European history and a basic familiarity with the main types of historical sources are required. Basic digital literacy skills, corresponding to the ordinary use of digital tools for study and research purposes, are also recommended.
No prior knowledge of programming, database management, or the use of artificial intelligence tools is required. - Teaching methods
- The course will combine lectures, guided practical activities, and collaborative learning exercises aimed at applying the tools and methodologies introduced during the course.
Particular attention will be devoted to the analysis of digitised medieval sources and to the practical use of tools for automated transcription, historical data organisation, and the application of artificial intelligence to historical research. Students will be involved in both individual and group activities focused on the collection, structuring, and interpretation of information extracted from historical sources.
Throughout the course, case studies illustrating the use of Digital Humanities methodologies, Handwritten Text Recognition (HTR), and Large Language Models (LLMs) in historical research will be presented and discussed. Teaching materials and source collections used during the course will be made available through the Unistudium platform.
Students with disabilities and/or Specific Learning Disorders (SLD), after consultation with the lecturer, may request teaching materials in accessible formats (e.g. presentations, handouts, and exercise materials), which can be provided in advance of classes when necessary, as well as the use of other assistive technological tools to support their learning. For general information, students are invited to consult the University services available at https://lettere.unipg.it/home/disabilita-e-dsa and to contact the Department’s Disability and Inclusion Officer (Prof. Alessandra Di Pilla: alessandra.dipilla@unipg.it).
Students who believe they meet the University requirements for access to synchronous distance learning (DaD) are invited to consult the eligibility criteria and access procedures at:
https://www.unipg.it/didattica/didattica-telematica-sincrona - Other information
- Attendance is strongly recommended, as the course includes practical activities, group discussions, and guided experimentation with digital tools that contribute significantly to the achievement of the learning outcomes.
Specific information about the course, teaching materials, digitised sources, datasets, practical exercises, and supplementary readings will be made available through the Unistudium platform:
https://www.unistudium.unipg.it/unistudium/login/index.php
During the course, software and digital services for the automated transcription of texts, data organisation, and the analysis of historical sources may be used. No prior specialist computing skills are required.
Students with disabilities and/or Specific Learning Disorders (SLD) and/or ADHD or ADD: for information on the University’s support services, please consult https://www.unipg.it/disabilita-e-dsa and contact the Department’s Disability and Inclusion Officer (Prof. Alessandra Di Pilla: alessandra.dipilla@unipg.it).
Students who believe they meet the University requirements for access to synchronous distance learning (DaD) are invited to consult the eligibility criteria and access procedures at:
https://www.unipg.it/didattica/didattica-telematica-sincrona
The design of the course itself serves as a case study on the use of artificial intelligence in research, knowledge organisation, and scholarly communication. Some teaching materials and course activities may be developed with the support of artificial intelligence tools, always under the critical supervision of the lecturer. - Learning verification modality
- Assessment consists of a final oral examination and the evaluation of practical activities carried out during the course.
Throughout the course, students will complete individual and group exercises focusing on the automated transcription of historical sources, data organisation, the creation of simple datasets, and the use of digital tools for historical research. These exercises will be discussed in class and will contribute to the overall assessment of learning outcomes.
The final oral examination consists of a discussion of the course contents, the methodologies presented during the lectures, and the activities carried out during the practical exercises.
The examination aims to assess:
understanding of the main tools and methods of digital historical research;
the ability to use automated transcription tools and artificial intelligence applications in an informed and critical manner;
the ability to critically interpret data and results produced through digital tools;
knowledge of the principal methodological issues associated with the use of digital technologies in historical research.
Duration: the oral examination will normally last between 20 and 30 minutes.
Assessment: the final grade, expressed on a 30-point scale, will take into account both the oral examination and participation in the practical activities and exercises carried out during the course. Assessment will consider the knowledge acquired, the ability to apply the methodologies presented, independent critical judgement, and the ability to discuss tools, data, and results in a critical and informed manner.
The examination is considered passed with a mark of 18/30 or higher.
Students with disabilities and/or Specific Learning Disorders (SLD) and/or ADHD or ADD who have uploaded a valid certification through SOL may request the compensatory measures, accommodations, and inclusive technologies provided for by current regulations. Such arrangements should be agreed with the lecturer well in advance of the examination. For further information, please consult:
https://www.unipg.it/disabilita-e-dsa. - Extended program
- The course introduces students to the use of digital methods and artificial intelligence tools in historical research, with particular attention to the analysis of medieval sources that have been digitised or reproduced in digital format.
The following topics will be addressed:
historical sources and digital environments: online archives, digital collections, metadata, and criteria for the selection of historical sources;
digitisation, Optical Character Recognition (OCR), and Handwritten Text Recognition (HTR): principles, potential applications, and limitations of automated transcription;
introductory use of tools for the transcription, correction, and organisation of information extracted from historical sources;
creation of simple historical datasets: data extraction, normalisation, and structuring;
introduction to the use of Large Language Models (LLMs) and artificial intelligence in historical research;
critical evaluation of the results generated by digital tools and automated systems;
methodological, epistemological, and ethical issues related to the use of artificial intelligence in the study of the past.
The course includes individual and collaborative practical activities aimed at the guided experimentation of digital tools for automated transcription, data organisation, and the analysis of historical sources. - Obiettivi Agenda 2030 per lo sviluppo sostenibile
- Goals 4 and 9:
Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all;
Promote the development of digital and methodological skills for the informed use of digital technologies and artificial intelligence in historical research and the enhancement of cultural heritage.