Science for Education Today, 2026, vol. 16, no. 3, pp. 98–123
© Tretyakova V. S., Kaigorodova A. E., Shchipanova D. E., 2026
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A cognitive approach to the process of developing predictive competence in university students: Justification of the use of mental structures

Tretyakova V. S. 1 (Yekaterinburg, Russian Federation), Kaigorodova A. E. 1 (Yekaterinburg, Russian Federation), Shchipanova D. E. 2 (Еkaterinburg, Russian Federation)
1 Ural State Pedagogical University
2 Russian State Vocational Pedagogical University
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Abstract: 

Introduction. This article presents a review of publications in cognitive psychology, cognitive linguistics, and neuroscience on the problem of identifying and describing the essence of the cognitive approach and its implementation in scientific research and education. The goal is to identify the cognitive (mental) structures that represent the essence of the cognitive approach and to justify its application to the development of predictive competence in university students.
Materials and Methods. The methodological basis of the study was a systems-oriented approach, ensuring a complete and systematic description of the research object, and a contextual approach, allowing for an understanding of the relationship of the results with existing concepts. Research methods included theoretical and methodological analysis of scholarly literature, content and comparative analyses, abstraction, and interpretation.
Results. A theoretical analysis of over two hundred research papers in cognitive psychology, psycholinguistics, and neuroscience was conducted. As a result, the authors substantiated the structure of cognitive activity and identified the cognitive abilities that determine the success of predictive activity. It was established that the cognitive approach is one of the fundamental approaches to the study of cognitive activity, particularly predictive activity. It was found that the development of predictive competence occurs in three stages, which correspond to the logic of cognitive activity: perception, transformation, and reproduction of knowledge.
Conclusions. The authors concluded that a cognitive approach, as a methodological foundation for developing predictive competence, provides researchers with the opportunity for a more complete and profound understanding of human predictive activity. Developments in cognitive psychology and cognitive linguistics have shown that predicting the future is inextricably linked to mental activity, and mental activity, as the study showed, is determined by how a person predicts (constructs) future events based on conscious mental search. It has been proven that the ability to predict is a fundamental property of the psyche and can be fulfilled as a result of the “launch” of cognitive mechanisms and their functioning.

Keywords: 

Predictive competence; Cognitive psychology; Cognitive approach; Cognitive processes; Cognitive abilities.

For citation:
Tretyakova V. S., Kaigorodova A. E., Shchipanova D. E. A cognitive approach to the process of developing predictive competence in university students: Justification of the use of mental structures. Science for Education Today, 2026, vol. 16, no. 3, pp. 98–123. DOI: http://dx.doi.org/10.15293/2658-6762.2603.05
References: 
  1. Boldyrev N. N. Cognitive approach in linguistics and related areas of research. Issues of Cognitive Linguistics, 2020, no. 2, pp. 5-25. URL: https://elibrary.ru/gfmflv DOI: https://doi.org/10.20916/1812-3228-2020-2-5-25
  2. Bukhalenkova D. A., Chichinina E. A., Chursina A. V., Veraksa A. N. The relationship between the use of digital devices and cognitive development in preschool children: Evidence from scholarly literature. Science for Education Today, 2021, vol. 11 (3), pp. 7–25. DOI: http://dx.doi.org/10.15293/2658-6762.2103.01
  3. Vasetskaya N. O. Cognitive competencies of graduates in the conditions of formation of the knowledge-digital economy. The World of the New Economy, 2020, vol. 14 (1), pp. 101-107. (In Russian) URL: https://elibrary.ru/ulwpyj  DOI: https://doi.org/10.26794/2220-6469-2020-14-1-101-107
  4. Gershkovich V. A., Falikman M. V. Cognitive psychology in search of itself. Russian Journal of Cognitive Science, 2018, vol. 5 (4), pp. 28-42. URL: https://elibrary.ru/hskhlf
  5. Gilev A. A. Main indicators of cognitive competencies. Bulletin of Samara State Technical University, Series Psychological and Pedagogical Sciences, 2014, vol. 11 (1), pp. 52-59. (In Russian) URL: https://elibrary.ru/tetbxn
  6. Zakharchenko D. A. Readiness of future teachers to prognostic activity: Essence, structure and specific features. Izvestiya VSPU, 2024, no. 8, pp. 88-93. (In Russian) URL: https://elibrary.ru/fxqmri
  7. Zeer E. F., Krezhevskikh O. V. Conceptual and theoretical foundations of personalised learning. Education and Science, 2022, vol. 24 (4), pp. 11-39. (In Russian) URL: https://elibrary.ru/jxgkax DOI: https://doi.org/10.17853/1994-5639-2022-4-11-39
  8. Karpykova G. U. Cognitive competence of future teacher: Content and diagnostics. Innovative Development of Professional Education, 2020, no. 3, pp. 39-42. (In Russian) URL: https://elibrary.ru/aweraz
  9. Kudaka M. A., Smirnova O. V. Psychological features of the interaction positions among medical workers with different levels of forecasting ability. Bulletin of Moscow State Regional University, Series: Psychological Sciences, 2021, no. 4, pp. 78-89. (In Russian) URL: https://elibrary.ru/cugkyu DOI: https://doi.org/10.18384/2310-7235-2021-4-78-89

10.Neborsky E. V. Predictive approach to research of education: Analysis and interpretation. Values and Meanings, 2024, no. 2, pp. 81–96. (In Russian) URL: https://elibrary.ru/pzykcj

11.Novikova A. A. Research on the influence of modern educational technology on the students' cognitive competence formation. Science for Education Today, 2023, no. 2, pp. 57–75. (In Russian)  URL: https://elibrary.ru/bnkccq DOI: http://dx.doi.org/10.15293/2658-6762.2302.03

12.Postavnev V. M., Postavneva I. V., Dvoynin A. M., Romanova M. A. Predictors of the child's academic success in the early stages of education. Bulletin of Moscow State Pedagogical University: Series: Pedagogy and Psychology, 2021, no. 4, pp. 64-73. (In Russian) URL: https://elibrary.ru/vfqxbt DOI: https://doi.org/10.25688/2076-9121.2020.54.4.05

13.Tretyakova V. S. Forecasting the professional future as an innovative technology for managing the professional development of students. Professional Education and the Labor Market, 2022, no. 1, pp. 112-126. (In Russian) URL: https://elibrary.ru/gkoziw DOI: https://doi.org/10.52944/PORT.2022.48.1.007

14.Tretyakova V. S. Scenario forecasting for students' professional future. Education and Science, 2024, vol. 26 (1), pp. 54-81. (In Russian) URL: https://elibrary.ru/uqmvii DOI: https://doi.org/10.17853/1994-5639-2024-1-54-81

15.Tretyakova V. S., Kaigorodova A. E., Sharov A. A., Zeer E. F. Basic components of a personal resource determining a personified subject of activity: The impact on university students' academic achievement. Science for Education Today, 2024, vol. 14 (2), pp. 206-230. (In Russian) URL: https://elibrary.ru/ugsjoq DOI: https://doi.org/10.15293/2658-6762.2402.09 

16.Fedina N. V., Dormidontov R. A., Eliseev V. K. Main trends and priorities in Russian and international studies on cognitive and non-cognitive predictors of academic success. Science for Education Today, 2022, vol. 12 (6), pp. 7-31. (In Russian) URL: https://elibrary.ru/riztkh DOI: https://doi.org/10.15293/2658-6762.2206.01

17.Frolova T. N., Shashurina G. V. The systematic approach and its role in scientific research. Psychology and Pedagogy of Service Activity, 2023, no. 1, pp. 158-161. (In Russian) URL: https://elibrary.ru/dggyeu

18.Andre L., van Vianen A. E. M., Peetsma T. T. D., Oort F. J. Motivational power of future time perspective: Meta-analyses in education, work, and health. Plos One, 2018, vol. 13 (1), pp. e0190492. DOI: https://doi.org/10.1371/journal.pone.0190492

19.Ballesteros S. Selective attention modulates information processing and implicit memory. Acción Psicológica, 2014, vol. 11 (1), pp. 7-20. DOI: https://doi.org/10.5944/ap.11.1.13788

20.Chaudhary D., Prajapati H., Rathod R., Patel P., Gurjwar R. Student future prediction using machine learning. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019, vol. 5, pp. 1104-1108. DOI: https://doi.org/10.32628/CSEIT1952300 

21.Clément E. Successful solution discovery and cognitive flexibility. Cognitive Flexibility: The Cornerstone of Learning, 2022, pp. 113-142. DOI: https://doi.org/10.1002/9781119902737.ch5

22.Kim H., Shin G.-H., Hwang H. Integration of verbal and constructional information in the second language processing of English dative constructions. Studies in Second Language Acquisition, 2020, vol. 42 (4), pp. 825-847. DOI: https://doi.org/10.1017/S0272263119000743

23.Paculanang S. Teachers innovative work behavior, professional competence and learners academic achievement. International Journal on Science and Technology, 2026, vol. 17 (1). DOI: https://doi.org/10.71097/IJSAT.v17.i1.9919

24.Safir K. B. The scenario-based approach (S.B.A) as a new approach to prevent school violence: theories vs., real world contextualized situations. European Journal of Education and Pedagogy, 2022, vol. 3 (5). 46–54. DOI: https://doi.org/10.24018/ejedu.2022.3.5.438

25.Sobol-Kwapinska M., Jankowski T. Positive time: Balanced time perspective and positive orientation. Journal of Happiness Studies, 2016, vol. 17, pp. 1511-1528. DOI: https://doi.org/10.1007/s10902-015-9656-2

Date of the publication 30.03.2026