education; learning opportunities; quality job; socio-economic development; social policies

Algarni, A. (2016). Data mining in education. International Journal of Advanced Computer Science and Applications, 7(6). ALzubi, J. A., Bharathikannan, B., Tanwar, S., et al. (2019). Boosted neural network ensemble classification for lung cancer disease diagnosis. Applied Soft Computing, 80, 579-591. Barantsov, I. A., Pnev, A. B., Koshelev, K. I., et al. (2023). Classification of Acoustic Influences Registered with Phase-Sensitive OTDR Using Pattern Recognition Methods. Sensors, 23(2), 582. Becker, M., & Tetzner, J. (2021). On the relations of sociocognitive childhood characteristics, education, and socioeconomic success in adulthood. Contemporary Educational Psychology, 67, 102024. Berezan, V. (2019). The impact of information and communication technologies on professional formation and development of social educator. Available online: http://dspace.pnpu.edu.ua/bitstream/123456789/21668/1/The%20impact%20of%20information.pdf. (accessed on 2 August 2024). Bukhtoyarov, V. V., Tynchenko, V. S., Nelyub, V. A., et al. (2023). A Study on a Probabilistic Method for Designing Artificial Neural Networks for the Formation of Intelligent Technology Assemblies with High Variability. Electronics, 12(1), 215. Gairin, J., Triado, X. M., Feixas, M., et al. (2014). Student dropout rates in Catalan universities: profile and motives for disengagement. Quality in Higher Education, 20(2), 165-182. Godor, B. P. (2017). Academic fatalism: Applying Durkheim’s fatalistic suicide typology to student drop-out and the climate of higher education. Interchange, 48(3), 257-269. Haenggli, M., & Hirschi, A. (2020). Career adaptability and career success in the context of a broader career resources framework. Journal of vocational behavior, 119, 103414. Harris, D. N., & Sass, T. R. (2011). Teacher training, teacher quality and student achievement. Journal of public economics, 95(7-8), 798-812. Hatos, A., & Pop, A. (2019). Commitment to the goal of completing studies in higher education: Dropout risk of the students from social science specialization from three Romanian public universities. Journal of Adult Learning, Knowledge and Innovation, 3(1), 12-19. Hodges, L. C. (2018). Contemporary issues in group learning in undergraduate science classrooms: A perspective from student engagement. CBE—Life Sciences Education, 17(2), es3. Huffman, W. E. (1974). Decision making: The role of education. American Journal of Agricultural Economics, 56(1), 85-97. Irvine, N., Nugent, C., Zhang, S., et al. (2019). Neural network ensembles for sensor-based human activity recognition within smart environments. Sensors, 20(1), 216. Issah, I., Appiah, O., Appiahene, P., & Inusah, F. (2023). A systematic review of the literature on machine learning application of determining the attributes influencing academic performance. Decision Analytics Journal, 100204. Jia, D. W., & Wu, Z. Y. (2021). Seismic fragility analysis of RC frame-shear wall structure under multidimensional performance limit state based on ensemble neural network. Engineering Structures, 246, 112975. Khan, R. U., Almakdi, S., Alshehri, M., et al. (2022). Probabilistic Approach to COVID-19 Data Analysis and Forecasting Future Outbreaks Using a Multi-Layer Perceptron Neural Network. Diagnostics, 12(10), 2539. Kingsford, C., & Salzberg, S. L. (2008). What are decision trees? Nature biotechnology, 26(9), 1011-1013. Kovács, K., Ceglédi, T., Csók, et al. (2019). Students who dropped out 2018 (Hungarian). Hungarian Educational Research Journal, 12(11), 804. Li, S., Yao, Y., Hu, J., et al. (2018). An ensemble stacked convolutional neural network model for environmental event sound recognition. Applied Sciences, 8(7), 1152. Maringe, F. (2006). University and course choice: Implications for positioning, recruitment and marketing. International journal of educational management, 20(6), 466-479. Markos, V., Kocsis, Z., & Dusa, Á. R. (2019). Different Forms of Civil Activity and Employment in Hungary and Abroad, and the Development of Student Drop-out. Central European Journal of Educational Research, 1(1), 41-54. Masich, I. S., Tyncheko, V. S., Nelyub, V. A., et al. (2022). Paired Patterns in Logical Analysis of Data for Decision Support in Recognition. Computation, 10(10), 185. Masich, I. S., Tynchenko, V. S., Nelyub, V. A et al. (2022). Prediction of Critical Filling of a Storage Area Network by Machine Learning Methods. Electronics, 11(24), 4150. Mikhalev, A. S., Tynchenko, V. S., Nelyub, V. A., et al. (2022). The Orb-Weaving Spider Algorithm for Training of Recurrent Neural Networks. Symmetry, 14(10), 2036. Priyam, A., Abhijeeta, G. R., Rathee, A., et al. (2013). Comparative analysis of decision tree classification algorithms. International Journal of current engineering and technology, 3(2), 334-337. Pusztai, G., & Kocsis, Z. (2019). Combining and balancing work and study on the eastern border of Europe. Social Sciences, 8(6), 193. Pusztai, G., Fényes, H., & Kovács, K. (2022). Factors influencing the chance of dropout or being at risk of dropout in higher education. Education Sciences, 12(11), 804. Pusztai, G., Fényes, H., Szigeti, F., et al. (2019). Dropped-out Students and the Decision to Drop-out in Hungary. Central European Journal of Educational Research, 1(1), 31-40. Romanova, I. K. (2022). Applying intelligent data analysis technologies for detecting damages to UAVs. In: AIP Conference Proceedings. AIP Publishing. Sá, M. J. (2023). Student Academic and Social Engagement in the Life of the Academy—A Lever for Retention and Persistence in Higher Education. Education Sciences, 13(3), 269. Sansone, C., & Harackiewicz, J. M. (2000). Intrinsic and extrinsic motivation: The search for optimal motivation and performance. Elsevier. Schreck, T., Bernard, J., Von Landesberger, T., et al. (2009). Visual cluster analysis of trajectory data with interactive kohonen maps. Information Visualization, 8(1), 14-29. Shafranov-Kutsev, G. F., & Efimova, G. Z. (2019). The place of professional education system in formation of graduates’competitiveness. The Education and science journal, 21(4), 139-161. Smirnov, S. D. (2004). Psychological factors of successful study of university students. Vestnik Moskovskogo universiteta, 1, 10-35. Solutions, S. (2019). Correlation. Pearson, Kendall, Spearman. Ting, C. Y., Cheah, W. N., & Ho, C. C. (2013). Student engagement modeling using bayesian networks. In: Proceedings of 2013 IEEE International Conference on Systems, Man, and Cybernetics. IEEE. pp. 2939-2944. Uusiautti, S., & Hyvärinen, S. (2021). Defining the new concept of sustainable success–A state-of-the-art analysis on the phenomenon. New Ideas in Psychology, 60, 100819. Váradi, J., Demeter-Karászi, Z., & Kovács, K. (2019). The connection between extracurricular, leisure time activities, religiosity and the reasons for drop-out. Central European Journal of Educational Research, 1(1), 55-67. Volchenko, T. V., Ruzhanskaya, L. S., & Fokeev, M. A. (2021). Non-cognitive skills of employees and their influence on voluntary turnover. Upravlenets, 12(2), 87-101. Zając, T. Z., & Komendant-Brodowska, A. (2019). Premeditated, dismissed and disenchanted: Higher education dropouts in Poland. Tertiary Education and Management, 25, 1-16.