Online Courses in Digital Ukrainian Philology Spring 2024

The aim of this course is to develop knowledge of text data pre-processing and transformation for the subsequent automation of computational linguistics tasks. Students will explore the capabilities of big data processing libraries using Python tools and assess the applicability of machine learning methods for linguistic analysis of text corpora.

The objective of the course is to reinforce programming skills in Python and develop an understanding of how Python tools can be used to work with datasets (corpora), databases, and websites. The course also aims to introduce the concept of machine learning through the use of Python libraries for data processing.

Students will explore the application of regular expressions to simplify text processing, as well as the use of the sqlite3 library, DataFrame, and the Django framework. By the end of the course, students will be able to efficiently process, visualise, and analyse data, as well as develop Python programmes for data manipulation.

Minimum requirements for participants: students should have a basic understanding of data types and the fundamental syntax of a programming language. They should be able to write simple Python code, including the use of variables, conditional statements, loops, and functions. A certificate from the Python for Philologists course or an equivalent programme would be an advantage.

Lecturer: Dr. Nadiia Babkova (Kharkiv Polytechnic Institute, Kharkiv, Ukraine)

Course Details

• Start date: 12 February 2024
• Duration: 12 weeks
• Language of instruction: Ukrainian

Study Load:

• Lectures: 24 academic hours
• Practical sessions: 24 academic hours
• Self-study: 72 hours 
• ECTS credits: 4  

The aim of the course is to equip linguists with the most advanced technological approaches and toolkits, as well as to provide them with the best methodologies for conducting systematic research and analysing textual data.

The objective of the course is to teach students how to apply natural language processing (NLP) algorithms and standard text data analysis pipelines. Participants will gain hands-on experience in text pre-processing and normalisation, text data visualisation, and conducting structural analysis of raw textual data using the NLTK library. The course topics, examples, and practical tasks cover both Ukrainian and English.

Minimum requirements for participants: knowledge of data types and the basic syntax of a programming language, as well as the ability to write simple Python code using variables, conditional statements, loops, and functions. A certificate from the Python for Philologists course or a similar programme would be an advantage.

Lecturers: Prof. Dr Nina Khairova (Kharkiv Polytechnic Institute, Kharkiv, Ukraine; Umeå University, Sweden), Dr. Nadiia Babkova (Kharkiv Polytechnic Institute, Kharkiv, Ukraine)

Course Details

• Start date: 5 February 2024
• Duration: 16 weeks
• Language of instruction: Ukrainian

Study Load:  

•  Lectures: 32 academic hours  
•  Practical sessions: 32 academic hours  
•  Self-study: 56 hours  
•  ECTS credits: 4  

The purpose of the course is to develop knowledge about the application of basic quantitative methods in philology, including linguistics and literary studies, linguistic expertise, stylometry, forensic linguistics, sociolinguistics, cognitive and historical linguistics, language learning and second language acquisition, ethnolinguistics, folkloristics, and dialectology, as well as in cultural studies, gender studies, etc.

The objectives of the course are:

1. To reflect on the significant quantitative turn in linguistics: over the last 20 years, the proportion of statistical and quantitative methods in global linguistics has been steadily increasing, while the proportion of qualitative approaches has been markedly decreasing (Kortmann 2021).
2. To provide students with an understanding of how to improve the quality of their research by implementing basic quantitative tools, thereby enhancing their competitiveness in the international academic field.
3. To analyse the main statistical tools available in existing text corpora, including Sketch Engine, Stylo, CQL charts, Word and Excel software, etc. and develop skills in their use; learn to visualize text data.
4. To clarify the role of quantitative analysis in the study of language and text and its place within the digital humanities.
5. To demonstrate the value of foundational quantitative concepts (e.g., frequency, relative frequency and comparison, normalisation, key words, collocation measurement, multidimensional analysis, etc.) and their relevance to the aforementioned disciplines.

The practical sessions include the use of corpus and other digital technologies, the format of an academic discussion, teamwork, sociolinguistic experiments, frequency dictionary compilation, and quantitative analysis of language and text. These components, along with the final essay, determine the students' overall success in the course.

Minimum requirements for participants: Basic theoretical knowledge of linguistics (having completed Introduction to Linguistics or Introduction to Applied Linguistics) is highly desirable but not strictly necessary for successfully completing the course. We also invite students of linguistics-related specialties, including literary studies, linguodidactics, folklore studies, dialectology, cultural studies, gender studies, etc.

Lecturer: Prof. Dr Solomija Buk (Ivan Franko National University of Lviv) 

Course Details

• Start date: 12 February 2024
• Duration: 9 weeks
• Language of instruction: Ukrainian

Study Load:  

• Lectures: 16 academic hours  
•  Practical sessions: 32 academic hours 
• Self-study: 42 hours 
• ECTS credits: 3 

This course serves as an introduction to Corpus Linguistics, a branch of applied linguistics concerned with the creation and organisation of large text collections—corpora—as well as the study of language based on such collections. The course primarily focuses on Ukrainian-language corpora, with particular attention given to the General Regionally Annotated Corpus of Ukrainian (GRAC), its improvement, and methods of working with it. During the course, students will participate in filling and annotating GRAC, acquire proficiency in the search software Sketch Engine, the Ukrainian grammatical analysis tool Nlp-uk, and the parallel corpora creation tool InterText. They will also develop skills in analysing corpus data and conducting independent

Within the course framework, students will gain knowledge of Ukrainian and other language corpora, learn to apply corpus functionalities for solving specific research tasks, work with main corpus tools, and independently create both monolingual and parallel corpora.

Minimum requirements for participants: to successfully complete the course, students should have basic knowledge of Ukrainian grammar and lexicology, general linguistics, and an A2+ level of English proficiency.

Lecturer: Dr Mariia Shvedova (Kharkiv Polytechnic Institute, Kharkiv, Ukraine; Jena University, Germany)

Course Details

• Start date: 12 February 2024
• Duration: 13 weeks
• Language of instruction: Ukrainian

Study Load:  

•  Lectures: 24 academic hours  
•  Practical sessions: 24 academic hours  
•  Self-study: 42 hours  
•  ECTS credits: 3 

The purpose of the course is to provide the participants with systematic understanding of social and political influence on language development and usage.  

Within the course the students explore Ukrainian and other (European) languages and their varieties in order to reveal both common trends and unique features in them. The students will learn such important concept as language standard, and explore how many standards a language may have. Apart from that, the students will explore how language contacts influence particular language development and change. They will look into the specifics of communication in a multilingual environment: what language choices people make to express their thoughts in a particular communicative situation and why. As a part of systematic linguistically-annotated-corpora driven investigation, students will reveal what are the most common triggers for the language code switching. 

Every student will have a chance to perform their own home assignment and research project for a language(s) of their choice utilizing the state-of-the-art linguistic-corpus-based techniques.

Minimum requirements for participants: to successfully complete the course, students should have basic knowledge of Ukrainian grammar and lexicology, general linguistics, history and culture of Ukraine, and an A2+ level of English proficiency.

Lecturer: Dr Mariia Shvedova (Kharkiv Polytechnic Institute, Kharkiv, Ukraine; Jena University, Germany)

Course Details

• Start date: 19 February 2024
• Duration: 13 weeks
• Language of instruction: Ukrainian

Study Load: 

• Lectures: 24 academic hours 
• Practical sessions: 24 academic hours 
• Self-study: 42 hours 
• ECTS credits: 3 

This course introduces students to the features of the Ukrainian dialect landscape, the role of dialects in the formation and functioning of the standard language, and modern methods of preserving and processing dialect data. The course aims to develop an understanding of dialects as a form of the national language, dialects as key markers of local identity, and the value of dialect data for research in historical linguistics, ethnolinguistics, ethnography, etc.

Throughout the course, students will engage with dialect atlases, chrestomathies, and dictionaries, as well as listen to audio recordings from various dialect regions. They will learn to identify dialect elements in texts and analyse them through the lens of both the history of the Ukrainian language and contemporary standard Ukrainian. Additionally, students will acquire knowledge of modern principles and tools for digitising dialect materials and will contribute to the Corpus of Ukrainian Dialects project.

Minimum requirements for participants: the course is designed for philology students with a basic theoretical background, having previously studied Introduction to Linguistics, Introduction to Phonetics, and/or Introduction to Slavic Philology.

Lecturer: Dr. Liudmyla Dyka (National University of Kyiv-Mohyla Academy, Kyiv, Ukraine)

Course Details

• Start date: 5 February 2024
• Duration: 10 weeks
• Language of instruction: Ukrainian

Study Load: 

• Lectures: 24 academic hours 
• Practical sessions: 16 academic hours 
• Self-study: 50 hours 
• ECTS credits: 3 

The updated course Modern Ukrainian Literature: Authors, Genres, Trends (Conversatorium) is a reading-based course designed to familiarise students with key figures, genres, and artistic trends in contemporary Ukrainian literature. It provides an opportunity to engage in discussions about modern literature, interpret texts representing various genres and styles, and reflect on pressing issues in Ukrainian writing and culture in the context of the Russian-Ukrainian war. The course offers guidance through the diversity of contemporary literature, fosters deep and thoughtful reading, develops literary analysis skills, enhances an understanding of literature’s role in the modern world, and refines aesthetic sensibilities.

We offer students to study the texts of Serhiy Zhadan, Oksana Zabuzhko, Taras Prokhasko, Sofia Andrukhovych, Kateryna Kalytko, Irena Karpa, Lyubko Deresh, Max Kidruk, Illarion Pavlyuk, and other popular and well-known Ukrainian authors.

Minimum requirements for participants: the course is designed for students with basic theoretical knowledge of literary studies, having previously completed Introduction to Literary Studies or Fundamentals of Literary Theory.

Lecturers:

Prof. Dr Sofiya Filonenko (Ukrainian Catholic University, Lviv, Ukraine) 

Dr Ostap Slyvynsky (Ukrainian Catholic University, Lviv, Ukraine) 

Dr Tetiana Trofymenko (V. N. Karazin Kharkiv National University) 

Course Details

• Start date: 5 February 2024
• Duration: 13 weeks
• Language of instruction: Ukrainian

Study Load:  

•  Lectures: 24 academic hours  
•  Practical sessions: 18 academic hours  
•  Self-study: 48 hours  
•  ECTS credits: 3