EXPERIENCE IN THE APPLICATION OF NEURO-LINGUISTIC TECHNOLOGIES FOR THE TRAINING OF FUTURE SPECIALISTS IN THE EDUCATIONAL AND INFORMATION ENVIRONMENT OF THE TECHNICAL UNIVERSITY

Authors

  • Vitalii Rakhmanov National Aviation University

DOI:

https://doi.org/10.18372/2411-264X.23.18178

Keywords:

learning process; neuro-linguistic technologies; future specialists; educational and informational environment; technical university

Abstract

The article presents the experience of using neuro-linguistic technologies in the educational process of a technical university, which has a significant impact on the quality of education and the effectiveness of future specialists. The purpose of the article is to implement the experience of using neuro-linguistic technologies to solve educational tasks in future activities. This helps create personalized learning approaches and resources that take into account each student's needs and learning style. The use of automated systems for monitoring and measuring the effectiveness of knowledge contributes to the objective assessment of the competences of future specialists.

The task of the research is to reveal the experience of using neuro-linguistic technologies, which will help to create more accessible and integrated educational materials, including virtual laboratories, interactive textbooks and other resources. Research methods consist in the study and generalization of domestic and foreign experience for the formation of conceptual provisions for the training of future specialists in the conditions of an educational and informational environment, scientific analysis, as well as observation of the educational process.

The results. The proposed technologies can provide individual training of future specialists with different directions and level of preparation, as well as improve the educational process. Large volumes of data collected thanks to neuro-linguistic technologies can be used to analyze and improve the educational process. The use of neuro-linguistic technologies can make education accessible to students from different countries and language groups. Interactive classes built on the basis of neuro-linguistic technologies increase the motivation of future specialists to study.

Conclusion. The successful implementation of neuro-linguistic technologies in the educational process helps to plan, organize, provide and monitor the training of future specialists

References

Про схвалення Стратегії розвитку системи вищої освіти в Україні на 2022 – 2032 роки (2022). Розпорядження КМ України від 23 лютого 2022 року № 286-р. Режим доступу: https://zakon.rada.gov.ua/laws/show/286-2022-%D1%80#Text.

Aggarwal, C. (2018). Neural Networks and Deep Learning: A Textbook / IBM T. J. Watson Research Center International Business Machines Yorktown Heights, NY, USA, 497 р. Режим доступу:https://www.academia.edu/42981452/Neural_Networks_and_Deep_Learning_Charu_C_Aggarwal

Brown et al. (2020). Language Models are Few-Shot Learners. / Computation and Language, 25 р.

Режим доступу:https://proceedings.neurips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf.

Cer D. et al. Universal Sentence Encoder (2018). Computation and Language Режим доступу https://arxiv.org/abs/1803.11175.

Clark, K., Luong, M.-T., Le, Q., & Manning, C. (2020). ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators / Published as a conference paper at ICLR 2020. Режим доступу https://arxiv.org/pdf/2003.10555.pdf%3C/p%3E.

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding / Academia.edu, 24 May 2019, 16 р. Режим доступу: https://www.academia.edu/41552448/BERT_Pre_training_of_Deep_Bidirectional_Transformers_for_Language_Understanding.

Goldberg, Y. (2017). Neural Network Methods in Natural Language Processing / Synthesis lectures on human language technologies, 285 р. Режим доступу https: //www.academia.edu/35854753/Neural_Network_Methods_for_Natural_Language_Processing.

Jurafsky, D. & Martin, J. (2023). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition / Draft of January 7, 2023, 636 р. Режим доступу https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf.

Manning, C. & Schütze, H. (1999). Foundations of Statistical Natural Language Processing / The MIT Press Cambridge, Massachusetts London, England, 680 р. Режим доступу https://www.academia.edu/7452675/Foundations_of_Statistical_Natural_Language_Processing.

Vaswan, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A., Kaiser, Ł., & Polosukhin, I. (2023). Attention Is All You Need. 31st Conference on Neural Information Processing Systems, Long Beach, CA, USA. 2 Aug 2023, 15 р. Режим доступу https://www.semanticscholar.org/paper/Attention-is-All-you-Need-Vaswani-Shazeer/204e3073870fae3d05bcbc2f6a8e263d9b72e776

Published

2024-01-06

Issue

Section

Статті