Научно-исследовательский семинар "Компьютерные методы обучения иностранному языку"

Бакалавриат 2019/2020

Лучший по критерию «Полезность курса для Вашей будущей карьеры»

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»

Лучший по критерию «Новизна полученных знаний»

Статус: Курс по выбору (Фундаментальная и компьютерная лингвистика)

Направление: 45.03.03. Фундаментальная и прикладная лингвистика

Кто читает: Школа лингвистики

Где читается: Факультет гуманитарных наук

Когда читается: 2-й курс, 1, 2 модуль

Формат изучения: без онлайн-курса

Преподаватели: Виноградова Ольга Ильинична

Язык: русский

Кредиты: 3

Контактные часы: 30

Полная версия программы учебной дисциплины

Аннотация

Students enrolled in the course "Computer methods in foreign language teaching" have to get experience before and in class of working on acquiring new language skills on different sites recommended by the instructor: they test the tools what those sites offer, watch video materials and make attempts at estimating their own proficiency in a language they are studying, they search corpora available to them in the attempt to find out linguistic features of their native language and languages they are learning; they evaluate tendencies in the native speakers’ and learners’ languages; they apply computational tools for working with corpora, they collect databases from their corpus observations and make a 15-minute presentation in class outlining the results of their data-driven research.

Цель освоения дисциплины

to familiarize students with the key approaches and specific tools of using language corpora in their studies of English and other languages
to help them develop effective strategies for using language corpora in their individual language learning trajectory
to apply the necessary computer programs and statistical methods in carrying out corpus observations
to advance their linguistic competence in analysing second language materials
to improve critical thinking and reasoning skills

Планируемые результаты обучения

understands the benefits of turning to a corpus of a language they are studying for information, examples, or answers in case of uncertainty
understands the linguistic importance of availability of big data corpora
makes empirical observations and theoretical generalizations concerning acquisition of a new language
applies their own or existing corpus computer tools for working with various problems in the area of data-driven learning
presents projects in exploring ways of data-driven learning

Содержание учебной дисциплины

The notion of data-driven learning
Language corpora and their role in independent learning trajectory. Examples of data-driven learning tasks.
Corpora for research in linguistics
Corpus research as a field in computer linguistics. Academician Plungyan on Postnauka site.
Introduction to the main national language corpora
Efficiency of searches in the Russian National Corpus.
Using Sketchengine for corpus research (part 1)
Tasks from the book “Learn English with SketchEngine”
Using Sketchengine for corpus research (part 2)
Independent tasks by students’ choice.
Learner corpora, their types
Error annotation practices and uses of annotation for teaching a foreign language.
Learner corpora at the School of Linguistics
Annotation of learner errors and their correction.
LancBox set of tools for corpus research
LancBox set of tools for corpus research.
Work with one of the platforms: SketchEngine and REALEC
Work with one of the platforms: SketchEngine and REALEC
Statistics in corpus research
Tools and principles.

Элементы контроля

activities in class
work with systems of proficiency evaluation and error detection
work on SketchEngine
Пересдается в течение недели после окончания пропуска по уважительной причине, но не позднее 10 дней до сессии, если преподавателем не указано иное
presentation of one's own achievements on SketchEngine and REALEC
Пересдается в течение недели после окончания пропуска по уважительной причине, но не позднее 10 дней до сессии, если преподавателем не указано иное

Промежуточная аттестация

Промежуточная аттестация (2 модуль)
0.2 * activities in class + 0.3 * presentation of one's own achievements on SketchEngine and REALEC + 0.3 * work on SketchEngine + 0.2 * work with systems of proficiency evaluation and error detection

Программа дисциплины