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Digital Editing Techniques

Code: 108495
Credits: 3
2026/2027
Degree programme Type Course
Translation and Interpreting OB 1

Contact lecturer

Name :
Adrià Martin Mor
Email :
adria.martin@uab.cat

Teaching staff

Sonia González Cruz
Itziar Andujar Garcia
Marc Riera Irigoyen
Sergi Alvarez Vidal

Group languages

You can consult this information at the end of the document.

Prerequisites

There are no prerequisites for this subject.

Objectives

The purpose of this subject is to introduce students to the use of general technological resources applied to translation and interpreting from a critical perspective. Upon completing the course, the student must be able to:

  • Demonstrate knowledge of general technological resources for file and data management in translation and interpreting.
  • Demonstrate knowledge of technological resources required for translating: managing files and data through specific resources.
  • Apply this knowledge to the editing and linguistic correction of texts in various formats.
  • Apply this knowledge to the basic automation of actions and objects in translation and interpreting (styles, formats, and accessibility).
  • Adopt a critical approach regarding the use of technology and AI applied to translation.
  • Work in a team: accept and comply with the group's rules.
  • Work in a team: collaborate in defining, organising, distributing, and carrying out group tasks.

Learning outcomes

  • CM40 (Critically integrate technological resources in the design of projects that have an honest, ethical, sustainable, socially responsible and respectful impact on human rights in the field of translation and interpreting.) Critically integrate technological resources in the design of projects that have an honest, ethical, sustainable, socially responsible and respectful impact on human rights in the field of translation and interpreting.
  • CM41 (Adapt the use of technology to the implementation of translation and interpreting projects that provide innovative responses to the needs and demands of society.) Adapt the use of technology to the implementation of translation and interpreting projects that provide innovative responses to the needs and demands of society.
  • KM32 (Describe the uses of the various technological tools available for translation and interpreting.) Describe the uses of the various technological tools available for translation and interpreting.
  • KM35 (Recognise the impact that the design of technological tools has on the perpetuation of sex/gender-based inequalities and discrimination in the field of translation and interpreting.) Recognise the impact that the design of technological tools has on the perpetuation of sex/gender-based inequalities and discrimination in the field of translation and interpreting.
  • SM42 (Use technological tools to create and edit digital content in the field of translation and interpreting.) Use technological tools to create and edit digital content in the field of translation and interpreting.
  • SM45 (Use both general and purpose-built tools to critically manage data and information in the field of translation and interpreting.) Use both general and purpose-built tools to critically manage data and information in the field of translation and interpreting.
  • SM46 (Critically analyse the social, economic and environmental implications of the use of technology in the field of translation and interpreting.) Critically analyse the social, economic and environmental implications of the use of technology in the field of translation and interpreting.

Contents

  • A techno-critical perspective applied to translation and interpreting technologies
  • Operating systems and software
  • Workspace management in translation and interpreting
  • Organisation, storage, and transfer of files/information
  • Tools for the production and editing of texts in print and digital formats
  • Tools for text comparison, revision, and correction: linguistic correction tools, track changes, document comparison, dictionaries
  • Resources for translation and interpreting
  • Tools for the automation of tasks and the translation process
  • Tools for the automation of editing (styles, formats, and accessibility)
  • Introduction to AI applied to translation: description and critical approach

Learning activities and methodology

Title Hours ECTS Learning outcomes
Text correction and revision exercise 2.6 0.104 SM42, SM45
Watching tutorials 7.5 0.3 KM32, SM42, SM45
Editing automation exercise (styles, formats, and accessibility) 4 0.16 CM41, SM42
Customization and task automation exercise 4 0.16 SM42, SM45
Preparation of group work 7.5 0.3 CM40, CM41, SM42
Reading of proposed texts 2.5 0.1 KM32, KM35, SM46
Attendance at follow-up sessions 2.5 0.1 CM40, CM41
Problem solving 7.5 0.3 KM32, SM42, SM45
Introduction to AI: description and critical approach 2.5 0.1 CM40, KM32, KM35, SM46
Cooperative work 15 0.6 CM40, CM41, SM46
Consultation of materials 7.5 0.3 KM32, KM35, SM45
Problem solving 5 0.2 KM32, SM42
Oral group presentation 4.75 0.19 CM40, KM32

The course alternates content sessions with practical sessions. Throughout the course, students must prepare a group oral presentation.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Progress test 2 35% 1 0.04 KM32, SM42, SM45
Oral group presentation 30% 0.15 0.006 CM40, CM41, KM32, KM35, SM46
Progress test 1 35% 1 0.04 KM32, SM42, SM45

Continuous Assessment

Assessment is continuous throughout the subject. Students must provide evidence of their progress by completing various tasks and tests. Task and test deadlines will be indicated in the course schedule on the first day of class. The information on assessment activities and their weighting is a guide. The subject lecturer will provide full information when teaching begins.

Review

When publishing final grades prior to recording them on students' transcripts, the lecturer will provide written notification of a date and time for reviewing assessment activities. Students must arrange reviews in agreement with the lecturer.

Students may retake assessment activities they have failed or compensate for any they have missed, provided that those they have actually performed account for a minimum of 66.6% (two thirds) of the final grade for the subject and that they have a weighted average mark of at least 3.5. In case of retaking, the maximum grade will be 5 (Pass).

The lecturer will inform students in writing of the retake procedure involved when publishing final grades prior to recording them on transcripts. The lecturer may set one assignment per failed or missed assessment activity or a single assignment to cover a number of such activities. Under no circumstances may an assessment activity worth 100% of the final mark be retaken or compensated for.

In the case of retake, the maximum grade will be 5 (Pass).

Classification as "not assessable"

In the event that the assessment activities a student has performed account for 25% or less of the final grade for the subject, their work will be classified as "not assessable" on their transcript.

Misconduct in assessment activities

Students who engage in misconduct (plagiarism, copying, personation, etc.) in an assessment activity will receive a mark of “0” for the activity in question. In the case of misconduct in more than one assessment activity, the student involved will be given a final grade of “0” for the subject. Assessment activities in which irregularities have occurred (e.g. plagiarism, copying, impersonation) are excluded from retake.

Use of artificial intelligence

In this course, the use of Artificial Intelligence (AI) technologies may or may not be permitted depending on the activity. The permitted and prohibited uses in each case will be detailed in the course introduction. Students must clearly identify which parts were generated using AI technologies, specify the tools used, and include a critical reflection on how these tools influenced the process and the final result of the activity. A lack of transparency regarding the use of AI in graded assignments will be considered a breach of academic integrity and may result in a partial or total penalty on the assignment grade, or more severe sanctions in serious cases.

Single assessment

This subject may be assessed under the single assessment system in accordance with the terms established in the academic regulations of the UAB and the assessment criteria of the Faculty of Translation and Interpreting.

Students must make an online request within the period established by the faculty and send a copy to the lecturer responsible for the subject, for the record.

Single assessment will be carried out in person on one day during week 16 or 17 of the semester. The Academic Management Office will publish the exact date and time on the faculty website.

On the day of the single assessment, teaching staff will ask the student for identification, which should be a valid identification document with a recent photograph (student card, DNI/NIE or passport).

Single assessment activities

  • Progress test 1 (35%)
  • Progress test 2 (35%)
  • Submission of a video-recorded presentation (30%)

Grade revision and retake procedures for the subject are the same as those for continual assessment. See the section above in this Study Guide.

Bibliography

  • Alvarez-Vidal, Sergi (2025). Activismo lingüístico digital para lenguas minoritarias: El caso del catalán. Mutatis Mutandis. Revista Latinoamericana de Traducción, 18(8). https://doi.org/10.17533/udea.mut.v18n2a14.
  • Association for Progressive Communications (2016). Feminist principles of the internet (Version 2.0). https://feministinternet.org/sites/default/files/Feminist_principles_of_the_internetv2-0.pdf.
  • Baker, Mona; Saldanha, Gabriela (eds.) (2009). Routledge encyclopedia of translation studies. London/New York: Routledge.
  • Diaz Fouces, Oscar; García González, Marta (eds.) (2008). Traducir (con) software libre. Granada: Comares.
  • Jiménez-Crespo, Miguel Ángel (2013). Translation and web localization. Milton Park, Abingdon, Oxon: Routledge.
  • Kenny, Dorothy (2022). Machine translation for everyone: Empowering users in the age of artificial intelligence. (Translation and Multilingual Natural Language Processing 18). Berlin: Language Science Press. DOI: 10.5281/zenodo.6653406.
  • Martín-Mor, Adrià; Piqué, Ramon; Sánchez-Gijón, Pilar (2016). Tradumàtica, tecnologies de la traducció. Vic: Eumo Editorial.
  • Matamala, Anna (2019). Accessibilitat i traducció audiovisual. Vic: Eumo Editorial.
  • Moniz, Helena; Parra Escartín, Carla (2023). Towards Responsible Machine Translation - Ethical and Legal Considerations in Machine Translation. ISBN 978-3-031-14688-6.
  • Oliver, Antoni (2016). Herramientas tecnológicas para traductores. Barcelona: UOC.
  • Oliver, Antoni; Moré, Quim (2007). Les tecnologies de la traducció. Barcelona: UOC.
  • Olohan, Maeve (2017). Technology, translation and society: A constructivist, critical theory approach. Target, 29(2), 264-283. https://doi.org/10.1075/target.29.2.04olo.
  • Open Letter: Stop the Uncritical Adoption of AI Technologies in Academia. https://openletter.earth/open-letter-stop-the-uncritical-adoption-of-ai-technologies-in-academia-b65bba1e.
  • Pérez-Ortiz, Juan Antonio; Forcada, Mikel L.; Sánchez-Martínez, Felipe (2022). How neural machine translation works. In Dorothy Kenny (Ed.), Machine translation for everyone: Empowering users in the age of artificial intelligence (Vol. 18). Language Science Press. Also available at: https://langsci-press.org/catalog/book/342.
  • Riera Irigoyen, Marc; Ivars Ribes, Xavier; Orga Esteve, Pere; Montané Camacho, Joan; Mas Hernández, Jordi; Vicedo Cremades, Artur. (2020). Softcatalà: Nous reptes per garantir la vitalitat del català a les tecnologies. Revista de Llengua i Dret, (73), Article 73. https://doi.org/10.2436/rld.i73.2020.3396.
  • Sin-wai, Chan (ed.) (2015). Routledge encyclopedia of translation technology. London/New York: Routledge.
  • Swartz, Aaron (2008). Guerrilla Open Access Manifesto. https://en.wikipedia.org/wiki/Guerilla_Open_Access_Manifesto#Text_of_the_Manifesto.

Software

The category of programs used for the subject is indicated below. The specific final product may vary depending on decisions by the faculty.

  • Operating systems (folder managers, internet browsers, file compression and decompression)
  • Office suites (word processors, spreadsheets, slide presentations)
  • PDF readers/editors
  • Computer-assisted translation and machine translation software
  • AI

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(SEM30) Seminaris (30 estudiants per grup) 1 Catalan first semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 2 Catalan first semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 3 Spanish first semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 4 Catalan first semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 5 Catalan second semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 6 Catalan second semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 7 Catalan second semester morning-mixed
(SEM30) Seminaris (30 estudiants per grup) 8 Catalan second semester morning-mixed