[THE USE OF NEURAL NETWORK TECHNOLOGIES BY TEACHERS OF OLDER AGE GROUPS: A COMPARATIVE ANALYSIS OF REPRESENTATIVES OF MEDICAL AND SOCIOLOGICAL SCIENCES].

Q4 Medicine

Problemy sotsial''noi gigieny i istoriia meditsiny / NII sotsial''noi gigieny, ekonomiki i upravleniia zdravookhraneniem im. N.A. Semashko RAMN, AO ''Assotsiatsiia ''Meditsinskaia literatura'' Pub Date : 2025-08-31 DOI:10.32687/0869-866X-2025-33-s1-863-866

E V Malinovich, I E Nadutkina, I V Konev, N S Danakin

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引用次数: 0

Abstract

The article presents the results of an empirical study on the use of neural network technologies by elderly university teachers representing medical and sociological sciences. The study is based on survey data from 524 academic professionals, with a focus on 60 respondents aged 60 and older. Special attention is given to the comparative analysis of digital activity, engagement with generative AI, and preferred tools (GPT, DeepSeek, GigaChat, etc.). The findings show that medical educators are more likely to use neural networks in research, while sociologists integrate them more into teaching practices. The selection of these two disciplines is justified as representative for analyzing digital adaptation in academia. The article concludes with limitations and directions for future research.

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[老年教师对神经网络技术的使用：医学和社会学代表的比较分析]。

本文介绍了一项针对老年大学教师使用神经网络技术的实证研究结果，这些教师分别代表医学和社会学。该研究基于对524名学术专业人士的调查数据，重点关注60名60岁及以上的受访者。特别关注数字活动的比较分析，与生成式人工智能的接触，以及首选工具（GPT, DeepSeek， GigaChat等）。研究结果表明，医学教育者更有可能在研究中使用神经网络，而社会学家则更多地将其融入教学实践。选择这两个学科作为学术界分析数字适应的代表是合理的。文章最后指出了研究的局限性和未来的研究方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Problemy sotsial''noi gigieny i istoriia meditsiny / NII sotsial''noi gigieny, ekonomiki i upravleniia zdravookhraneniem im. N.A. Semashko RAMN, AO ''Assotsiatsiia ''Meditsinskaia literatura''

CiteScore

0.40

自引率

0.00%

发文量

234