Elective course:Corpora and Artificial Intelligence in Language Teaching 3200-M1-PF-KNJAI
The aim of the course is to familiarize students with various applications of language corpora in foreign language teaching, as well as with the possibilities of complementing them through contemporary generative artificial intelligence tools. The course covers an introduction to language corpora and acquaints students with corpus resources available online. Students will also learn methods of corpus data analysis and how to use a range of corpus tools that enable precise retrieval of linguistic information, with attention to generative models that support work with language data. The course will present ways of using corpus-based information and generative AI tools to teach vocabulary, phraseology, grammar, and discourse organization, as well as methods of working with corpora and AI during lessons. The use of corpora and artificial intelligence in planning and preparing specialised language courses will also be discussed. Students will build their own mini-corpus and become familiar with methods and tools needed for its analysis for teaching purposes, with the option of using generative tools as analytical support. Examples of applications of corpora and artificial intelligence will be drawn from the teaching of English and Polish as foreign languages.
Student's workload:
Participation in classes 30 h
Preparation for classes 30 h
Preparation of the term project 25 h
Total 85 h
Format of work: instructor’s presentations, students’ presentations tasks involving analyzing corpus data or using generative artificial intelligence, and individual work outside the classroom
Course coordinators
Type of course
Mode
Prerequisites (description)
Learning outcomes
Knowledge: the graduate knows and understands
K_W01 the complex structure of language as a system, including findings from corpus linguistics in this area
K_W02 psycholinguistic and linguistic aspects of language use and language acquisition at an advanced level
K_W03 specialized terminology in the field related to the application of corpus linguistics and artificial intelligence in language teaching
K_W05 the main directions of development and current research trends in the use of language corpora, generative artificial intelligence, and data-driven learning
K_W06 the main analytical methods used in corpus linguistics
K_W07 concepts and principles of intellectual property protection and copyright law at a professional level, especially in the context of building language corpora
Skills: the graduate is able to
K_U01 apply the acquired knowledge to prepare syllabuses, lesson plans, and teaching materials using corpora and artificial intelligence, and with the use of appropriate methodology
K_U03 search for, analyze, evaluate, and select information about foreign languages using corpus tools and generative artificial intelligence
K_U04 use advanced corpus tools and artificial intelligence, and select teaching methods appropriate to instructional goals
K_U09 independently acquire knowledge in corpus linguistics and artificial intelligence tools, and assess the usefulness of the methods, practices, and procedures learned in their own teaching activity
Social competences: the graduate is ready to
K_K01 recognize the importance of the latest disciplinary knowledge and critically evaluate received content
K_K02 appropriately identify new corpus tools and artificial intelligence tools in foreign language teaching
K_K06 apply scientifically grounded criteria for evaluating syllabuses, lesson plans, and teaching materials created with the use of corpora and artificial intelligence
Assessment criteria
• completion of all in-class tasks
• completion of a project that includes:
– creation of a mini-corpus of specialised language and its analysis for pedagogical purposes
– preparation of two lesson plans with accompanying teaching materials, based on corpus analysis and using artificial intelligence tools
– writing a report
Final mark:
90% end-of-semester project (min-corpus, analyses and a lesson plans)
10% mean mark for homework assignments
Practical placement
does not apply
Bibliography
Corpus Linguistics textbooks for language teachers
Flowerdew, L. (2012). Corpora and Language Education. Palgrave Macmillan UK. https://doi.org/10.1057/9780230355569
Friginal, E. (2018). Corpus Linguistics for English Teachers: Tools, Online Resources, and Classroom Activities (1st Edition). Routledge.
Harrington, K., & Ronan, P. (Eds.). (2023). Demystifying Corpus Linguistics for English Language Teaching. Palgrave Macmillan.
O’Keeffe, A., McCarthy, M., & Carter, R. (2007). From Corpus to Classroom: Language Use and Language Teaching. Cambridge University Press.
Moorhouse, B. L., & Wong, K. M. (2025). Generative artificial intelligence and language teaching. Cam`bridge University Press.
Reppen, R. (2010). Using Corpora in the Language Classroom. Cambridge University Press.
Timmis, I. (Leeds B. U. (2015). Corpus Linguistics for ELT: Research and Practice. Routledge.
Corpus-based resource books
Anderson, W., & Corbett, J. (2017). Exploring English with online corpora: An introduction (Second edition). Palgrave Macmillan.
Bennett, G. (2010). Using Corpora in the Language Learning Classroom: Corpus Linguistics for Teachers (Illustrated Edition). Michigan ELT.
Poole, R. (2018). A Guide to Using Corpora for English Language Learners. Edinbourgh University Press. https://edinburghuniversitypress.com/book-a-guide-to-using-corpora-for-english-language-learners.html
Viana, V. (Ed.). (2022). Teaching English with Corpora: A Resource Book (1st edition). Routledge.
Corpus-based online resource materials
le Foll, E. (Ed.). (2021). Creating Corpus-Informed Materials for the English as a Foreign Language Classroom. Pressbooks. https://pressbooks.pub/elenlefoll/
Pinto, P. T., Crosthwaite, P., Carvalho, C. T. de, Spinelli, F., Serpa, T., Garcia, W., & Ottaiano, A. O. (2023). Using Language Data to Learn About Language: A Teachers’ Guide to Classroom Corpus Use. The University of Queensland. https://doi.org/10.14264/3bbe92d