Neural network technologies in the self-development of adults’ life skills

The article explores the integration of neural network technologies into the process of developing and enhancing life skills in adults. The relevance of the topic is determined by the rapid advancement of artificial intelligence and the urgent need to adapt educational processes to the demands of the digital society. The study highlights a lack of comprehensive pedagogical models that could fully realize the potential of AI in adult education. Based on the analysis of recent research, the authors define adults’ life skills in the digital era as a dynamic, integrative set that includes: self-directed learning and knowledge management; digital literacy; online interaction skills; creativity and innovative thinking; critical thinking and digital ethics; emotional competence and resilience. The pedagogical potential of neural network technologies is revealed in several key areas: personalization of learning trajectories, development of digital competence, fostering skills for operating under uncertainty, stimulating creativity, and increasing motivation for lifelong learning. The possibilities of creating intelligent mentors for adaptive career development and personal growth are demonstrated. At the same time, the study identifies several barriers hindering the full integration of AI into adult education: insufficient digital literacy, psychological resistance to change, ethical and legal dilemmas, shortage of qualified teaching staff, and infrastructural constraints. A comprehensive approach to overcoming these barriers is proposed. The key outcome of the research is a working model for applying neural network technologies within a master’s degree program. The model includes target, content, procedural, organizational, and assessment components and demonstrates how AI integration can contribute to the formation of individual educational trajectories and self-development. The model’s application is illustrated through the elective course “Adult Education Technologies” in the master’s program “Pedagogy of Higher School.”

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Publication Details

Journal
Vìsnik pìslâdiplomnoï osvìti.
Published
2025-09-23
DOI
https://doi.org/10.58442/3041-1831-2025-33(62)-197-213
Primary Topic
Educational Innovations and Challenges
Type
article
Field-Weighted Citation Impact
0.00
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article

Neural network technologies in the self-development of adults’ life skills

Олена Купенко, Olena Pehota, Serhii Bieliaiev
Vìsnik pìslâdiplomnoï osvìti.
Educational Innovations and Challenges
article

Neural network technologies in the self-development of adults’ life skills

Олена Купенко, Olena Pehota, Serhii Bieliaiev
article en

Abstract

The article explores the integration of neural network technologies into the process of developing and enhancing life skills in adults. The relevance of the topic is determined by the rapid advancement of artificial intelligence and the urgent need to adapt educational processes to the demands of the digital society. The study highlights a lack of comprehensive pedagogical models that could fully realize the potential of AI in adult education. Based on the analysis of recent research, the authors define adults’ life skills in the digital era as a dynamic, integrative set that includes: self-directed learning and knowledge management; digital literacy; online interaction skills; creativity and innovative thinking; critical thinking and digital ethics; emotional competence and resilience. The pedagogical potential of neural network technologies is revealed in several key areas: personalization of learning trajectories, development of digital competence, fostering skills for operating under uncertainty, stimulating creativity, and increasing motivation for lifelong learning. The possibilities of creating intelligent mentors for adaptive career development and personal growth are demonstrated. At the same time, the study identifies several barriers hindering the full integration of AI into adult education: insufficient digital literacy, psychological resistance to change, ethical and legal dilemmas, shortage of qualified teaching staff, and infrastructural constraints. A comprehensive approach to overcoming these barriers is proposed. The key outcome of the research is a working model for applying neural network technologies within a master’s degree program. The model includes target, content, procedural, organizational, and assessment components and demonstrates how AI integration can contribute to the formation of individual educational trajectories and self-development. The model’s application is illustrated through the elective course “Adult Education Technologies” in the master’s program “Pedagogy of Higher School.”

Vìsnik pìslâdiplomnoï osvìti.Vol. 33(62)
Openalex Percentile: Top 62%
Educational Innovations and Challenges
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