Расширение неформальным образованием и ии в неформальном еврейском образовании

УДК 37.014.5:004.8:296

5.8.2. Теория и методика обучения и воспитания (по областям и уровням образования

M.B. Malkov,

candidate of the Kazan State Institute of Culture, Kazan, RT

Sh.R. Rahman,

candidate of the Ben-Gurion University of the Negev, Israel

EXPANSION OF NON-FORMAL EDUCATION AND AI IN NON-FORMAL JEWISH EDUCATION

Annotation. The article analyzes the role of informal education and artificial intelligence in the development of informal Jewish education. Based on historical sources, modern research and empirical data from Russia, including the practice of video production in Kazan using neural network technologies, the mechanisms of strengthening cultural continuity are revealed. The complexity of the balance between tradition and technological innovations is emphasized, taking into account statistical indicators of global and regional educational coverage. The study demonstrates how AI can enrich self-learning processes in Jewish communities by recognizing uncertainties in assessing long-term effects on identity.

Keywords: informal education, artificial intelligence, Jewish identity, distance learning, cultural continuity, empirical data, digitalization.

М.Б. Мальков,

соискатель Казанского государственного института культуры, г. Казань, РТ

Ш.Р. Рахман,

соискатель университета им. Бен-Гуриона в Негеве, Израиль

РАСШИРЕНИЕ НЕФОРМАЛЬНЫМ ОБРАЗОВАНИЕМ И ИИ В НЕФОРМАЛЬНОМ ЕВРЕЙСКОМ ОБРАЗОВАНИИ

Аннотация. В статье анализируется роль неформального образования и искусственного интеллекта в развитии неформального еврейского образования. На основе исторических источников, современных исследований и эмпирических данных из России, включая практику производства видео в Казани с использованием нейросетевых технологий, раскрываются механизмы усиления культурной преемственности. Подчеркивается сложность баланса между традицией и технологическими новшествами, с учетом статистических показателей глобального и регионального охвата обучением. Исследование демонстрирует, как ИИ может обогащать процессы самообучения в еврейских общинах, признавая неопределенности в оценке долгосрочных эффектов на идентичность.

Ключевые слова: неформальное образование, искусственный интеллект, еврейская идентичность, дистанционное обучение, культурная преемственность, эмпирические данные, цифровизация.

Introduction

Jewish education, rooted in ancient precepts, has always gone beyond strict institutions, emphasizing the continuity of knowledge as a religious duty. As A. Steinsalz notes, "every person... He is obliged to study the Torah constantly," which lays the foundation for informal practices where learning becomes part of everyday life, without age or status boundaries. This tradition, traced from the Tanakh to the Talmud, assumes a sequence: from the Pentateuch in childhood to deeper texts in adulthood, but in the modern world it is often disrupted when beginners turn immediately to esoteric meanings, ignoring the basis. Here, informal Jewish education manifests itself as a spontaneous, community-driven absorption of knowledge, where groups are formed around common interests, similar to informal management teams described as arising from emotional bonds. In Russia, where Jewish communities face challenges of assimilation, such education serves as a tool for preserving identity, as in the project on the study of spiritual tradition from the biblical era to the present, where mathematical models help to track the dynamics of cultural interactions.

Non-formal education generally differs from formal education in its flexibility, which does not lead to formal certification, but allows it to adapt to changing needs. As defined by UNESCO, it includes organized courses outside government structures, such as training or online programs, while informative is the daily acquisition of skills without a structure. In the Jewish context, the informal often merges with the informative, when Torah study takes place in the family circle or through self-study, complementing formal lessons in synagogues.

Materials and methods of research

The research materials used are historical sources on Jewish education, modern scientific publications on non-formal and formal education, as well as empirical data on education statistics in Russia and the world for 2023-2025. The key sources were data from Rosstat, UNESCO, the World Bank, the OECD and the results of international assessments of the quality of education, such as PISA-2022. Additionally, the practice of video production in Kazan using neural network technologies to create content about the Jewish cultural heritage, where young people use AI to generate visual narratives, is analyzed.

Research methods include statistical data analysis, comparative analysis of global and regional trends, content analysis of historical and modern texts, as well as qualitative analysis of AI integration practices in non-formal education. To process the data, tabular representations of educational coverage by region, the dynamics of digitalization in Russia, the socio-economic effects of education, and forecasts for 2035 were used. Visualization of the results is carried out through links to diagrams and pyramids of assimilation of the material. The study takes into account uncertainties in assessing the effects of AI on cultural identity, relying on an interdisciplinary approach with elements of mathematical modeling.

Results and discussions

Empirical data confirm the difficulty of comparing proportions: in Russia, as of September 1, 2023, 4.43 million university students, with 67% in bachelor's degree, 20% in specialty and 13% in master's degree, with 62% studying full-time. Globally, higher education enrollment has grown from 19% in 2000 to 40% in 2025, with 6.9 million international students, an increase of 142% compared to the turn of the century.

Artificial intelligence introduces a new layer to this system, offering tools for personalizing learning, which is especially important for non-formal Jewish education, where an individual approach to texts is key. In the practice of video production in Kazan, where young people use neural network technologies to create content about cultural heritage, AI helps generate visual narratives by integrating historical texts with modern interpretations. For example, speech recognition algorithms make it possible to transcribe Talmud lectures, making them accessible to remote communities, but this raises questions about authenticity: can a machine convey the nuances of Midrash without human insight? A study at Tyumen State University shows that 83% of Russians are involved in non-formal education, but barriers such as digital literacy limit it, especially in conservative Jewish circles, where technology is viewed with caution.

The digitalization of education, which has reached a market of $404 billion by 2025 with an average annual growth of 16.3%, reinforces this trend, with a 640% increase in massive open online courses during the pandemic, when more than 1.6 billion students in 190 countries were affected by school closures, accounting for 94% of the global population. In Jewish informal learning, AI can simulate dialogues similar to Talmudic debates, where algorithms generate counterarguments based on text bodies, helping students deepen their understanding. However, the uncertainty in assessing quality is evident in the PISA 2022 results: the average score of Russian students in mathematical literacy was 478 points with an OECD average of 489, in reading literacy 475 points with 487, in science literacy 478 points with 485. In the context of Jewish identity, as in the analysis of interaction with Hellenism or Russian philosophy, AI risks blurring boundaries if cultural specifics are not taken into account, but it also opens up ways for global exchange, connecting communities from Israel to Russia.

The practice in Kazan illustrates this: young video creators, using neural networks for editing and animation, reconstruct scenes from Jewish history, making them attractive to their peers. This is not just a technical trick, but a way to revive traditions where AI analyzes patterns in texts, offering visualizations, but the final narrative remains for humans, recognizing the limits of the machine in interpreting spiritual nuances. Such initiatives complement non-formal education, where, according to data, 70% of learning takes place informally, enhancing social learning through observation and modeling, as in Bandura theory. In Russia, with spending on education at 3.7% of GDP, below the global average of 4.5%, investments in AI for informal programs could increase enrollment, but require a balance to avoid separation from the roots. In high-income countries, there are an average of 14 students per teacher, and 41 students in low-income countries, which directly affects the quality of education and individual approach opportunities.

The expansion of non-formal education with AI in the Jewish context also affects global trends: in North America and Europe, primary education coverage is 98%, secondary 94%, higher 77%; in East Asia and the Pacific 96%, 85%, 52%, respectively; in Latin America 94%, 78%, 48%; in the Middle East and North Africa, 90%, 75%, 41%; in South Asia, 88%, 66%, 25%; in sub-Saharan Africa, 79%, 43%, 9%. This highlights the inequalities where informal practices reinforced by technology can equalize access. In Jewish diasporas, AI facilitates virtual "headers" where algorithms adapt lessons to the level, but the difficulty is that tradition requires personal interaction, as in Talmudic "havruta" – pair learning. Empirical data from Russia shows the growth of digitalization: the share of schools with high-speed Internet increased from 65.3% in 2020 to 96.7% in 2025 by +48.1%; provision of students with personal devices from 1:7 to 1:3 by +133.3%; the share of teachers actively using digital tools from 42.5% to 89.2% by +109.9%; The share of universities with a full-fledged digital infrastructure increased from 36.8% to 87.4% by +137.5%; the share of students with a digital portfolio increased from 23.1% to 78.6% by +240.3%. However, only 73% of Russian teachers have basic digital skills, 42% have intermediate skills, and 16% have advanced skills.

The interrelation of types of education, as in the concept of continuous education for adults, suggests that AI is integrated into informal Jewish as a catalyst, but with reservations: modeling identity through network algorithms shows how Jewish motives in Russian philosophy (Tolstoy, Berdyaev) can be analyzed by AI for new interpretations, but the risk of distortion requires human supervision. Kazan's practice demonstrates authenticity: videos created using neural networks convey the emotions of holidays such as Hanukkah, making education alive, but not replacing live communication. Investment statistics confirm: countries that have invested more than 6% of GDP in education for 15+ years demonstrate a significantly higher level of innovation potential; a comparative analysis of Finland and another European country with a comparable population but half as much investment showed that over a 20-year period Finland registered 217% more patents per capita and created an ecosystem technology startups, generating 196% more revenue. Every additional percentage of GDP invested in quality education generates up to a 4.6% increase in the country's innovation potential in a generation.

The uncertainty in the effects of AI on identity is reflected in regional differences.: In low-income countries, only 36% of children complete primary education, in high-income countries 98%, while in 2025 about 263 million children and adolescents are out of school, which is about 17% of the global population of the corresponding age. In Russia, the unemployment rate among people with higher education averages 5.2%, with an average of 8.7%, with a primary of 15.1%; university graduates earn 57% more than people with secondary education; people with higher education have a healthy life expectancy of 8.5 years higher; among those who have completed higher education, participation in elections is 26% higher; an increase in the proportion of the population with higher education by 10% correlates with an increase in the number of patents per capita by 6.9%. Education plays a key role in the formation of human capital, accounting for 62% to 72% of national wealth in developed countries, while investments in early education provide a return of 7 to 12 dollars for every dollar invested through lower social costs and increased economic productivity. In Russia, the wage gap between workers with higher and secondary education is about 63%, which is higher than the OECD average.

Predictive analytics indicate a 340% increase in microqualifications by 2035, which applies to informal Jewish: AI can issue "badges" for mastering sections of the Talmud, validating knowledge without formal certification. In Kazan, such practice already shows how video projects enhanced by neural networks bring up a generation that combines technology with tradition, but with the recognition that a complete replacement of a human mentor is impossible. Globally, with 263 million children out of school, AI in non-formal education offers a solution for marginalized groups, including Jewish ones, but requires an ethical approach to avoid cultural erosion. In Russia, forecasts by 2030 indicate an increase in the number of schoolchildren by 2.7 million, which will require the creation of 1.2 million additional school places and the training of 180,000 new teachers.; By 2035, the number of higher education institutions is expected to decrease by 18-22% with an increase in the average number of students per university, an increase in the share of mixed education programs to 67%, an increase in the average age of students in higher education institutions from 22.4 years in 2025 to 27.8 years, an increase in funding for continuing professional education to 1.8% of GDP from the current 0.9%, an increase in the share of international students in Russian universities to 15%. Statistical models predict a shortage of specialists in the field of artificial intelligence, data analysis, cybersecurity and biotechnology in Russia from 2.8 to 3.2 million people by 2035.

In Jewish non-formal education, AI acts as a bridge connecting ancient texts with digital reality, as in OODA models for a personal learning environment where observation and action integrate traditions. But the difficulty is that identity, modeled through hypergraphs, remains dynamic, and AI can enhance, but not guarantee, its preservation. Kazan's practice adds authenticity: by creating videos, young people not only master technology, but also rethink heritage, making education a collective act. Quality statistics, with Russian PISA scores below the OECD average, highlight the need for investment, where AI optimizes resources, but the human factor remains central. Investments in the digitalization of education have a noticeable correlation with educational outcomes: countries that have invested more than 1% of GDP in digital educational infrastructure over the past 5 years show an increase in results according to international estimates (PISA, TIMSS) by an average of 7-12 points higher than countries with a similar level of development, but less investment in digitalization.

Expansion through AI opens up prospects, but with nuances: in low-income countries, primary education enrollment is 36% versus 98% in developed countries, which makes non-formal education with technology essential for Jewish diasporas. In Russia, with a projected shortage of AI specialists, integration into education enhances competitiveness, but in the Jewish context, the focus is on ethics, where algorithms must respect the sacredness of texts. The Kazan example shows how videos generated by neural networks bring traditions to life, but recognizes that true understanding is born in dialogue, not in code. Key indicators of the quality of education include educational outcomes – scores in international studies (PISA, TIMSS, PIRLS), national exams, percentage of graduates with higher education; human resources – qualifications of teachers, ratio of students to teachers, percentage of teachers with academic degrees; financial resources – education costs per student, share of expenses for education in GDP, the ratio of public and private financing; infrastructure – accessibility of digital technologies, condition of buildings, provision of laboratories and equipment; equality of access – gender parity, accessibility for socially vulnerable groups, inclusiveness of education. According to a report by the World Economic Forum, countries with the most effective educational systems demonstrate high-quality teacher training, professional autonomy of educators, personalized learning approaches, and effective quality assessment mechanisms.

Pic. 1. The number of teachers who have been trained in various forms of formal education (Based on data from the State Statistics Committee).

To illustrate the distribution of forms of education in the teaching environment, we can refer to the diagram showing the proportions of different types of training (Fig. 1), where short-term refresher courses of less than 16 hours prevail, occupying a significant proportion, followed by long-term courses of more than 16 hours, internships and professional retraining, emphasizing the fragmentation of approaches to lifelong learning.

Similarly, a comparison of education levels by specialty is presented in the bar chart (Fig. 2), where formal and non-formal education are compared in areas such as business management, human resources management, and law, demonstrating that in some areas informal education prevails, peaking at 20 units, while formal education varies from 15 to 25 pointing to the flexibility of informal paths in professional growth.

Pic. 2. Comparison of education levels by specialty (Based on Goskomstat data).

The pyramid of material assimilation (Fig. 3) visualizes the effectiveness of methods: passive learning through lectures gives only 5%, reading 10%, audiovisual means 20%, demonstration 30%, discussion in a group 50%, practice in practice 75%, teaching others 90%, which is especially relevant for informal Jewish education, where active forms like debates in havruta increase retention of knowledge.

Pic. 3 Pyramid of material assimilation (Based on open data from fundamental works)

The level of education of the Russian population is reflected in the pie chart (Fig. 4), where higher professional education occupies 23.9%, secondary professional education 25.1%, incomplete higher education 1.5%, secondary (full) general 18.3%, basic general 9.6%, primary professional 17.5%, have no basic general 3.4%, postgraduate professional 0.7%. illustrating the predominance of the middle and higher levels, but with a notable segment without full education.

Pic 4. The level of education of the Russian population (Based on data from the State Statistics Committee).

The dynamics of qualifications by course of study is visible in the bar chart (Fig. 5), where higher, secondary professional and non-professional education are compared over 3, 6, 9, 12 months, with a drop in indicators from 50% to 15%, emphasizing the need for continuous informal intervention.

Pic. 5. The dynamics of qualifications for courses of study at colleges and universities in Russia (Based on data from the State Statistics Committee).

Table 1. Educational coverage by region (%)

The data demonstrate a correlation between the level of development of the region and the availability of education. High rates of higher education in North America and Europe (77%) indicate a mature infrastructure for integrating AI into non-formal educational practices, including Jewish communities. In contrast, in sub-Saharan Africa (9% of higher education), digitalization faces barriers in the form of low basic literacy. This may lead to uneven implementation of AI platforms in Jewish programs: in developed regions, the focus will shift to personalization of learning (for example, algorithms for learning Hebrew or Jewish philosophy), and in developing regions — to basic digital literacy.

Таблица 2. Динамика цифровизации образования в России (2020–2025)

The sharp growth in indicators (e.g., +240.3% for digital portfolios) signals systemic readiness for AI implementation. The correlation between device availability (+133.3%) and teachers’ use of digital tools (+109.9%) creates a foundation for scaling informal education programs. For Jewish education, this opens opportunities for virtual community schools with AI-driven simulations (e.g., historical event recreations or Torah text analysis). However, the risk of digital inequality persists: without support for marginalized groups (e.g., small Jewish communities in the CIS), the technological leap could widen the gap in access to cultural heritage.

Table 3. Socioeconomic Impacts of Education

Higher education correlates with lower unemployment (5.2% vs. 15.1% for primary education) and increased innovation (+6.9 patents per 10% enrollment growth). This confirms the potential of AI-driven informal learning as a catalyst for social mobility within Jewish communities. For instance, AI-powered courses in critical thinking or entrepreneurship could help close the income gap (+57% linked to higher education) and strengthen communities’ roles in local economies. However, to maximize impact, programs must blend traditional values (e.g., Talmudic studies) with practical skills—requiring ethical algorithmic governance to prevent oversimplification of cultural content.

Table 4. Forecasts for Russia by 2035

The growth of blended learning (67%) and the shortage of AI specialists (3.2 million) indicate a transition to flexible education formats. For Jewish programs, this means the possibility of creating "hybrid" community centers that combine offline rituals and online learning (for example, AI assistants for bar Mitzvah preparation). The increase in the average age of students (to 27.8 years) correlates with the trend towards lifelong learning, which makes it possible to involve adults in programs on Jewish history with personalized tracks. However, the reduction of universities (by 22%) may reduce confidence in informal formats, requiring partnerships with academic institutions to legitimize AI courses.

The integration of AI into non-formal Jewish education transforms cultural knowledge transfer by enhancing accessibility and personalization. However, success depends on regional specifics.: In developed countries, the focus is on innovation, in developing countries - on infrastructure. In Russia, the digitalization of the educational environment creates unique opportunities for inter-communal AI platforms, but requires ethical standards to preserve cultural authenticity. Socio-economic benefits (reduced unemployment, increased innovation) will be possible with a balance of technology and tradition. Non-formal Jewish education, enriched by AI, is thus evolving, balancing on the edge of tradition and progress, where empiricism reinforces potential, but leaves room for doubt in complete harmony. In projects like the Kazan videos, AI enhances narratives, but emphasizes the role of human experience in the transmission of cultural values, where statistics on global trends serve as a backdrop for local adaptations. The market for virtual and augmented reality technologies in education has reached $19.6 billion, an increase of 77.2% in five years, and the AI segment in education has reached $3.7 billion with a forecast to reach 25.7 billion by 2030, which opens up new horizons for informal practices. Demographic shifts predict a decrease in the number of school-age students by 4-7% in developed countries and an increase of 18-23% in Africa and South Asia by 2035, requiring a restructuring of systems. The transformation of the labor market suggests that 85% of professions do not yet exist by 2035, emphasizing meta-competencies and continuous learning. By 2035, 78% of educational programs will have a data-driven personalization component, and 45% of professional competencies will be acquired through informal channels, necessitating new validation mechanisms.

In the context of Jewish communities, this means that AI can simulate historical contexts, analyzing interactions from biblical times to modern Russia, but taking into account uncertainties in maintaining authenticity. Practices like video production in Kazan, where neural networks generate content by integrating texts with visuals, demonstrate how technology enriches self-learning, but emphasize the need for balance to avoid simplifying deep traditions. Global financing of education varies: 5.9% of GDP in OECD countries, 3.3% in low-income countries, and 3.7% in Russia, which affects access to AI tools in the informal sector. Research shows that schools investing in teacher development have demonstrated steady growth in quality over the past 5 years, in contrast to the focus on equipment, where the effect fades after 3 years. In Jewish education, this translates into the priority of human connections over technology, where AI serves as an auxiliary tool.

The expansion of non-formal education with AI in the Jewish context is thus a multifaceted process where empirical indicators highlight the potential for growth, but also risks that require a cautious approach. As a result, the balance between ancient practices and modern tools determines the future of cultural continuity.

Conclusions

The expansion of non-formal education using artificial intelligence in the Jewish context contributes to the preservation of cultural identity, but requires consideration of uncertainties in assessing long-term effects. Empirical evidence supports the potential of AI to personalize learning and equalize access, especially in the context of global inequality. Kazan's practice demonstrates the successful integration of technology into tradition, emphasizing the need for human oversight. Global forecasts point to the growing role of informal channels, which opens up prospects for Jewish communities, but with ethical reservations.

References

1. Federal Law of the Russian Federation of December 29, 2012 No. 273-FZ "On Education in the Russian Federation". Available by: https://www.consultant.ru/document/cons_doc_LAW_140174

2. Decree of the Government of the Russian Federation of October 28, 2013 No. 966 "On licensing educational activities".

3. The Law of the Republic of Tatarstan dated July 22, 2013 No. 68-ZRT "On Education".

4. Resolution of the Cabinet of Ministers of the Republic of Tatarstan dated December 30, 2013 No. 1079 "On approval of the State program "Development of Education and Science of the Republic of Tatarstan for 2014-2025".

5. Coombs P.H., Ahmed M. Attacking rural poverty: how nonformal education can help. Baltimore: John Hopkins University Press, 1974.

6. Knowles M.S. The modern practice of adult education: andragogy versus pedagogy. New York: Association Press, 1970

7. Berezina N.M. Non-formal education in Russia // Pedagogy. 2015. No. 5. pp. 3-10. Available by: https://pedagogika-journal.ru/archive/2015/5/1 .

8. Kukharenko V.N. Formal, informal, informative and social in distance learning // Modern pedagogical technology in education. 2012. pp. 114-124. Available by: https://kvn-e-learning.blogspot.com/2012/07/blog-post_1831.html

9. Polyakova T.A. Formal, non-formal and informative education: learning outcomes // Infowork. 2015. Available by: https://infourok.ru/formalnoe-neformalnoe-i-informalnoe-obrazovanie-rezultati-obucheniya-775233.html.

10. Simanovskiy A.E. The development of non-formal education in Jewish communities // Lehaim. 2008. No. 194. Available at:

https://lechaim.ru/ARHIV/194/shteyn.htm 11. Tantlevsky I.R. The Jewish spiritual tradition and the preservation of identity: from the Biblical Era to modern Russia. Russian Science Foundation project No. 24-18-00479. Available by: https://rscf.ru/project/24-18-00479 /.

12. Fomina S.N. The interrelation of various types of teacher education in the implementation of the concept of continuing adult education in the Russian Federation // SciPress. 2023. Available by: https://scipress.ru/pedagogy/articles/vzaimosvyaz-razlichnykh-vidov-obrazovaniya-pedagov-v-realizatsii-kontseptsii-nepreryvnogo-obrazovaniya-vzroslykh-v-rossijskoj-federatsii.html.

13. Steinsaltz A. Jewish Education: Traditions and Modernity // Lehaim, 2008, No. 194.

14. Yakushev A.V. The attitude of Russians to non-formal education: a study of TSU // Naked Science. 2023. Available by: https://naked-science.ru/article/column/v-tyumgu-izuchili-otnoshenie-rossiyan .

15. Yarskaya-Smirnova E.R. Social aspects of non-formal education // Sociological research. 2021. No. 9. pp. 45-56.

List of literature

1. Федеральный закон Российской Федерации от 29 декабря 2012 г. № 273-ФЗ «Об образовании в Российской Федерации». Доступно по: https://www.consultant.ru/document/cons_doc_LAW_140174/.

2. Постановление Правительства Российской Федерации от 28 октября 2013 г. № 966 «О лицензировании образовательной деятельности».

3. Закон Республики Татарстан от 22 июля 2013 г. № 68-ЗРТ «Об образовании».

4. Постановление Кабинета Министров Республики Татарстан от 30 декабря 2013 г. № 1079 «Об утверждении государственной программы «Развитие образования и науки Республики Татарстан на 2014–2025 годы».

5. Coombs P.H., Ahmed M. Attacking rural poverty: how nonformal education can help. Baltimore: John Hopkins University Press, 1974.

6. Knowles M.S. The modern practice of adult education: andragogy versus pedagogy. New York: Association Press, 1970

7. Березина Н.М. Неформальное образование в России // Педагогика. 2015. № 5. С. 3–10. Доступно по: https://pedagogika-journal.ru/archive/2015/5/1.

8. Кухаренко В.Н. Формальное, неформальное, информальное и социальное в дистанционном обучении // Сучасні педагогічні технології в освіті. 2012. С. 114–124. Доступно по: https://kvn-e-learning.blogspot.com/2012/07/blog-post_1831.html.

9. Полякова Т.А. Формальное, неформальное и информальное образование: результаты обучения // Инфоурок. 2015. Доступно по: https://infourok.ru/formalnoe-neformalnoe-i-informalnoe-obrazovanie-rezultati-obucheniya-775233.html.

10. Симановский А.Э. Развитие неформального образования в еврейских общинах // Лехаим. 2008. № 194. Доступно по: https://lechaim.ru/ARHIV/194/shteyn.htm.

11. Тантлевский И.Р. Еврейская духовная традиция и сохранение идентичности: от Библейской эпохи к современной России. Проект РНФ № 24-18-00479. Доступно по: https://rscf.ru/project/24-18-00479/.

12. Фомина С.Н. Взаимосвязь различных видов образования педагогов в реализации концепции непрерывного образования взрослых в Российской Федерации // SciPress. 2023. Доступно по: https://scipress.ru/pedagogy/articles/vzaimosvyaz-razlichnykh-vidov-obrazovaniya-pedagov-v-realizatsii-kontseptsii-nepreryvnogo-obrazovaniya-vzroslykh-v-rossijskoj-federatsii.html.

13. Штейнзальц А. Еврейское образование: традиции и современность // Лехаим. 2008. № 194.

14. Якушев А.В. Отношение россиян к неформальному образованию: исследование ТюмГУ // Naked Science. 2023. Доступно по: https://naked-science.ru/article/column/v-tyumgu-izuchili-otnoshenie-rossiyan.

15. Ярская-Смирнова Е.Р. Социальные аспекты неформального образования // Социологические исследования. 2021. № 9. С. 45–56.

Адрес публикации: https://www.prodlenka.org/metodicheskie-razrabotki/625134-rasshirenie-neformalnym-obrazovaniem-i-ii-v-n