78671 - French Linguistics 1 (LM)

Learning outcomes

The global aim of this course which includes lectures and language classes - is to provide students with an expert knowledge of a number of aspects of French linguistics, enabling them not only to communicate effectively in French, but also to think critically about and describe the metalinguistic factors at play in language use. This aim will be achieved by providing students with theoretical knowledge related to one or more of the following areas of French linguistics: phonology, morphology, syntax, lexicology, semantics, pragmatics, sociolinguistics, psycholinguistics, stylistics and corpus linguistics. The focus of the course will be on real language use, with authentic texts (written and/ or spoken, belonging to different registers) and electronic language corpora used as examples. At the end of the two years course, the student is able to apply such knowledge by means of the use of suitable tools ; he/she knows how to plan a linguistic search in a correct way. Language classes aim to improve students’ linguistic competence; over the two year period students’ knowledge of French should reach level C2 according to the European framework in all four abilities, which allows students to effectively interpret the partner-linguistic and cultural codes in any subject within a communicative relationship. These classes will work in connection with the lectures to improve students writing, skills in particular.

Course contents

The course aims to provide students with advanced knowledge of French linguistics, enabling them not only to communicate effectively in French, but also to critically analyse the linguistic, metalinguistic, and cultural factors involved in real language use.

More specifically, the course aims to:

• consolidate students’ knowledge of the main branches of French linguistics: phonetics and phonology, semantics, pragmatics, lexicology and lexiculture, sociolinguistics, and languages for specific purposes;
• introduce the fundamental principles of lexicography and terminology, developing students’ ability to consult and compare dictionaries, terminological databases, and corpora as essential reference tools for linguists and translators;
• introduce the methods and tools of corpus linguistics and Natural Language Processing;
• train students in the design, compilation, and exploration of comparable and parallel corpora;
• illustrate the applications of corpus-based data to translation and terminography;
• develop students’ ability to critically evaluate machine translation systems and generative artificial intelligence;
• strengthen their awareness of diastratic, diaphasic, and diatopic variation, as well as of the pluricentric nature of the French language;
• promote a transparent, responsible, and methodologically sound use of artificial intelligence tools.

The course adopts an approach oriented towards careers in multilingual and multimodal communication, translation, writing and editing, terminology, lexicography, computational linguistics, and the language industries, with particular attention to tourism, artistic, and cultural communication.

Readings/Bibliography

Required Reading

• Landragin, F., Comment parle un robot ? Les machines à langage dans la science-fiction, Saint-Mammès, Le Bélial, 2020.
• L’Homme, M.-C., La terminologie. Principes et techniques, Presses de l’Université de Montréal, 2004; nuova edizione 2020 disponibile in OpenEdition Books.
• Loock, R., La traductologie de corpus, Villeneuve-d’Ascq, Presses Universitaires du Septentrion, 2016.
• Zotti, V., “Have electronic corpora made dictionaries obsolete? Some encouraging results from an international teaching experiment in the field of French artistic vocabulary”, in Dictionary Use and Dictionary Teaching: New Challenges in a Multilingual, Digital and Global World, Berlin-Boston, De Gruyter, 2024, pp. 221-246, «Lexicographica. Series Maior». Open Access.

Recommended Reading and Supplementary Materials

• Condamines, A., “Terminologie, intelligence artificielle, psychologie cognitive : réflexions sur les interactions possibles dans l’étude de la variation en langue spécialisée”, pp. 131-148.
• Farina, A. e Zotti, V., a cura di, Industries des langues France-Italie, «Synergies Italie», n. 17, 2021.
• Kilgarriff, A. et al., “The Sketch Engine”, Proceedings of Euralex, Lorient, France, July 2004, pp.105-116.
• Villa, M. L., Zanola, M. T. e Dankova, K., “Langages et savoirs : intelligence artificielle et traduction automatique dans la communication scientifique”, pp. 107-127.
• Zotti, V., “Corpora multilingui rispettosi della diatopia: il caso del Québec”, in Per un’intelligenza artificiale a favore del multilinguismo europeo. Raccomandazioni strategiche rivolte ai decisori europei, Milano, Ledizioni, 2023, pp. 65-68. Open Access.
• Zotti, V., “‘The limits of LLMs are the limits of the world’: considerations on the role of linguistics in enhancing AI-generated language quality”, in Inclusione ed elaborazione del linguaggio naturale nell’era dell’intelligenza artificiale generativa, Milano, Ledizioni LediPublishing, 2025, pp. 201-210.

Additional articles, excerpts, corpora, practical worksheets, and digital resources will be made available on the University of Bologna’s Virtuale platform.

Teaching methods

The course consists of lectures taught by Professor Valeria Zotti and language classes conducted by Professor Daniel Caddoux, a native French-speaking instructor. These two components are conceived as closely integrated parts of the learning pathway.

The lectures combine the presentation of theoretical content with practical activities, demonstrations of digital resources, and computer-based workshops. Students work individually and in small groups to consult and compare dictionaries, terminological databases, and corpora, and to build and explore corpora using tools such as BootCat and Sketch Engine. Starting from concrete linguistic, terminological, and translation-related problems, they are guided in formulating research questions, selecting appropriate sources, analysing data, and critically evaluating machine translation and generative artificial intelligence systems.

The language classes aim to strengthen oral and written comprehension and production, with particular attention to argumentative discourse. Through the analysis of authentic texts, visual documents, and audiovisual materials belonging to different genres, students identify discourse structure, intended audience, thesis, arguments, discourse markers, and rhetorical strategies. Activities include listening, reading, summarising, debating, and written production, as well as comparing student-produced texts with AI-generated texts in order to recognise their potential, limitations, errors, and biases.

Regular attendance is strongly recommended, as the language and laboratory activities follow a structured progression and contribute directly to the preparation of the assessed coursework.

Assessment methods

Assessment for the main course consists of one examination relating to the first module and one applied assessment relating to the second module.

For information about the assessment for the language classes associated with the same course, please refer to the relevant page: [LINK].

First-Module Assessment

The assessment takes place on the EOL platform and includes:

• multiple-choice questions;

• open-ended questions;

• exercises involving the consultation and comparison of lexicographical and terminological resources;

• exercises relating to the use and evaluation of machine translation tools.

Second-Module Assessment

Practical skills relating to the use of BootCat and Sketch Engine, as well as to machine translation and generative artificial intelligence, are assessed primarily in the second module.

The assessment consists of an oral presentation supported by PowerPoint slides, followed by an individual critical discussion. It takes place during the official examination sessions and focuses on the Travaux dirigés (TD 1 and TD 2) completed during the course.

During the presentation, students are required to illustrate:

• the research question;

• the corpus and resources used;

• the methodology adopted;

• the main results obtained;

• the use of digital tools and AI;

• the limitations encountered;

• the procedures used to verify and revise automatically generated outputs.

Policy on the Use of Artificial Intelligence

AI can be a useful tool to support independent study through further exploration, summaries, and self-assessment activities. With regard to assessment, the examination includes one component requiring substantial use of AI, for example in problem solving or content generation, and one compulsory component devoted to critical analysis.

The use of AI is required in activities involving the comparison of human-produced texts, machine translation outputs, and texts generated by language models.

Students must:

• declare the tools used;

• retain the main prompts;

• document the relevant outputs;

• clearly distinguish automatically generated content from their own contribution;

• verify data, information, and references through corpora and reliable sources;

• justify the revision and post-editing procedures carried out.

Students remain fully responsible for the scientific, linguistic, and bibliographical quality of their work. The formal fluency of an automatically generated text does not, in itself, guarantee its accuracy, appropriateness, or overall quality.

Automatically generated content cannot replace the individual critical discussion. Undeclared use of AI, where transparency is required, constitutes a methodological shortcoming and will affect the assessment.

Teaching tools

Teaching activities make use of textual, lexicographical, and digital resources employed both during lectures and in laboratory sessions. In particular, the following tools and resources will be used:

• the University of Bologna’s Virtuale platform, for sharing teaching materials, assignments, and supplementary resources;
• teaching materials and presentations provided by the lecturer;
• authentic written, oral, and multimodal texts;
• monolingual and bilingual dictionaries;
• terminological databases;
• comparable and parallel corpora;
• machine translation systems and large language models;
• BootCat, for compiling specialised corpora;
• Sketch Engine, for corpus exploration and analysis;
• the EOL platform, used for the first-module assessment.

Office hours

See the website of Valeria Zotti