Мақаланы E-mail арқылы жіберу Data Labeling as an Object of Teaching Social Sciences and Humanities Students
- Авторлар: Aleynikova D.V.1
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Мекемелер:
- Moscow State Linguistic University
- Шығарылым: № 4(845) (2022)
- Беттер: 15-19
- Бөлім: Pedagogical Studies
- URL: https://journals.rcsi.science/2500-3488/article/view/357059
- ID: 357059
Дәйексөз келтіру
Аннотация
Machine learning and artificial intelligence employ massive amounts of data to solve a wide range of profession-related problems. This practice, however, has not been reflected in the modern educational content. The article addresses issues of „human-machine“ interaction while updating the content of teaching social sciences and humanities students. What is crucial in this context is a qualitative revision of the educational strategies used in the training of modern specialists.
Негізгі сөздер
Авторлар туралы
Darya Aleynikova
Moscow State Linguistic University
Хат алмасуға жауапты Автор.
Email: festabene@mail.ru
PhD (Pedagogy), Associate Professor of the Department of Linguistics and Professional Communication in the Field of Law, Institute of International Law and Justice
РесейӘдебиет тізімі
- Polachowska K. AI in education: can AI improve the way we teach and learn? – Neoteric. Software House That Helps You Innovate, 2019. URL: https://neoteric.eu/blog/ ai-in-education-can-ai-improve-the-way-we-teach-and-learn/
- Kilgarriff A. Gold standard datasets for evaluating word sense disambiguation programs // Computer Speech and Language. 1998. № 3. Vol. 12. P. 453–472.
- Tseng T., Stent A., Maida D. Best Practices for Managing Data Annotation Projects, 2020. URL: https://www.researchgate.net/publication/344343968_Best_Practices_for_Managing_Data_Annotation_Projects
- Hein A. [et al.]. WOAR 2014: Workshop on Sensor-based Activity Recognition, chapter Towards causally correct annotation for activity recognition / A. Hein, A. F. Kruger, K. Yordanova, T. Kirste. Fraunhofer. 2014. P. 31–38.
- Atanassova I., Blais A., Descles J.-P. A Cross-Lingual Approach to the Discourse Automatic Annotation: Application to French and Bulgarian // Proceedings of the Twenty- First International FLAIRS Conference. 2008. P. 450–455.
- Wolf F., Gibson E. Representing discourse coherence: A corpus-based study // Computational Linguistics. 2005, № 2. Vol. 31 C. 249–288.
- Putra J. W. G. [и др.]. TIARA 2.0: an interactive tool for annotating discourse structure and text improvement / J. W. G. Putra, K. Matsumura, S. Teufel, T. Tokunaga // Language Resources & Evaluation. 2021. doi: 10.1007/s10579-021-09566-0 URL: https://link.springer.com/article/10.1007/s10579-021-09566-0
- Ильф И., Петров Е. Двенадцать стульев: роман. М. : ВАГРИУС, 2000.
- Кабалдин Ю. Г. [и др.]. Искусственный интеллект, интернет вещей, облачные технологии и цифровые двойники в современном механообрабатывающем производстве: монография / Ю. Г. Кабалдин, Д. А. Шатагин, П. В. Колчин, М. С. Аносов. Нижегородcкий государственный технический университет им. Р. Е. Алексеева. Нижний Новгород, 2019.
- Яроцкая Л. В. Иностранный язык как инструмент формирования современной профессиональной личности в условиях неязыкового вуза // Вестник Московского государственного лингвистического университета. Образование и педагогические науки. 2021. Вып. 1(838). С. 193–201. doi: 10.52070/2500-3488_2021_1_838_193.
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