Problem of cheating with neural networks in language learning; Язык. Общество. Образование

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Parent link:	Язык. Общество. Образование.— 2023.— С. 141-148
Autore principale:	Зайда А. В.
Ente Autore:	Национальный исследовательский Томский политехнический университет Школа базовой инженерной подготовки Отделение иностранных языков
Altri autori:	Согуляк Я. А. (научный руководитель), Аксёнова Н. В. Наталия Валерьевна
Riassunto:	This study explores the performance of commercially available large language models in common language learning tasks. Structure and working principles of neural networks were considered to hypothesize which tasks would perform better. Experiments were conducted to verify the assumptions. Several variants of task adaptations were compared in tests to discover the most resistant to cheating Текстовый файл
Lingua:	inglese
Pubblicazione:	2023
Serie:	Актуальные векторы исследований и подходы в современной лингвистике
Soggetti:	электронный ресурс труды учёных ТПУ language learning cheating large language models task evaluation task adaptation
Accesso online:	http://earchive.tpu.ru/handle/11683/77924
Natura:	Elettronico Capitolo di libro
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=671978

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