Conceptual and theoretical foundations of personalised learning

Introduction. The urgency of the problem related to personalised learning in future teacher training is associated with the creation of an optimal range of choices in the conditions of intensive development of the informal and non-formal educational environment in the global (interstate) educational space. At the same time, the slogan “teach everyone and everything” is disappearing into the past; instead, the importance of unique specialists, who are able to implement their own pedagogical startups and introduce them into educational practice, is increasing.

Aim. The aim of the article is to describe the development and testing of a structural and functional model of personalised learning in education of future teachers.

Methodology and research methods. The methodological research framework is based on V. A. Petrovsky’s concept of personology, methodology of nonlinear educational systems and transdisciplinary approach in science and education. In the course of the research, the following tools and methods were used: analysis, comparison and generalisation, the authors’ interpretation of psychological and pedagogical literature in the field of accounting for individual characteristics of the student, structural and functional modelling of pedagogical systems. The method of studying the advanced pedagogical experience of Internet education based on the analysis of open online platforms was applied. During the testing of the structural and functional model of personalised education, 178 students (1st–5th year students) were involved in the educational programme “Preschool Education” of full-time and part-time forms of education at Shadrinsk State Pedagogical University. The analysis of students’ diaries and the final questionnaire were employed to determine whether students were satisfied with the personalization in education.

Results. The conceptual and theoretical characteristics of personalised learning are defined: nonlinearity, redundancy, transdisciplinarity, adaptability, openness. The parameters of personalised learning are highlighted: at the level of the subject of social and professional development, the purpose of education, and the content and applied educational technologies. The approbation of the structural and functional model of personalised learning in future teacher training demonstrated a high and average level of satisfaction of students; however, the recorded insufficiency of their own ability to determine the main characteristics of personalized learning was reflected in the quantitative data of satisfaction.

Scientific novelty. In contrast to the existing research in the field of individual approach and personalisation in education, a model of personalised learning in education for future teachers is proposed, which allows them to independently design an individual educational route in the current time and to take into account changing cultural and educational needs in the conditions of the modern global educational space in a broad sense and conditionally divided into interuniversity (international and intra-state interuniversity competitions, forums, conferences, etc.), digital (digital online platforms, electronic educational environments), and professional and personal (participation in individual projects).

Practical significance. According to the intensive development of the global educational space, it is proposed to integrate the available resources to develop personalised learning in future teacher training.

1. Gasanova R., Kassymova G., Arpentieva M., Pertiwi F., Duisenbayeva S. Individual educational trajectories in additional education of teachers. In: Challenges of Science: Materials of International Practical Internet Conference. Almaty; 2020. p. 59–68. DOI: 10.31643/2020.009

2. Sagitovaa R. R., Garaeva A. K. Designing of individual educational routes of university students in the process self-directed language learning. In: IFTE 2016: 2nd International Forum on Teacher Education; 2016 May 19–21; Kazan. Kazan; 2016. p. 371–377. DOI: 10.15405/epsbs.2016.07.59

3. Yunusova G. R., Karunas E. V. Designing and realization of an individual educational program. International Journal of Environmental & Science Education. 2016; 11 (9): 2299–2310. DOI: 10.12973/ijese.2016.606a

4. Fomina S., Tikhonova E., Kvitkovskaya A., Khorokhorina G. Development of an individual educational route for a student as a tool for a new educational landscape. In: 11th annual International Conference of Education, Research and Innovation; 2018 Nov 12–14; Seville, Spain. Seville, Spain; 2018. p. 4203–4211. DOI: 10.21125/iceri.2018.1927

5. Koldaev V. D. Methodological aspects of the design of individual educational routes. Psychological Science and Education [Internet]. 2013 [cited 2021 Sept 10]; 4 (18): 15–22. Available from: https://psyjournals.ru/files/66272/pno_2013_4_koldaev.pdf

6. Sheng J. Song, Tan K. Hua, Awang M. Generic digital equity model in education: Mobile-assisted personalized learning (MAPL) through e-modules. Sustainability. 2021; 13 (19): 2–21. DOI: 10.3390/su131911115

7. Hopkins D. Personalized learning in school age education. In: Peterson P., Baker E., McGaw B. (Eds.). International Encyclopedia of Education. 3rd edition. Oxford: Elsevier Science; 2010. p. 227–232. DOI: 10.1016/B978-0-08-044894-7.01073-3

8. Shemshack A., Kinshuk S., Jonathan P. A comprehensive analysis of personalized learning components. Journal of Computers in Education. 2021; 1(8): 1–19. DOI: 10.1007/s40692-021-00188-7

9. Popova N. E., Lobut A. A. Individual approach to university education. Pedagogicheskoye obrazovaniye v Rossii = Pedagogical Education in Russia [Internet]. 2013 [cited 2022 Jan 24]; 6. Available from: https://cyberleninka.ru/article/n/individualnyy-podhod-k-obucheniyu-v-vuze (In Russ.)

10. Petrovskiy V. A. Logika «Ya»: personologicheskaya perspektiva = Logic “I”: A personological perspective. Moscow: Publishing House SamGU; 2009. 304 p. (In Russ.)

11. Fiedler S., Väljataga T. Personal learning environments: Concept or technology? IJVPLE. 2011; 2: 1–11. DOI: 10.4018/jvple.2011100101

12. Raj N., Renumol V. A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020. Journal of Computers in Education. 2021 Aug. DOI: 10.1007/s40692-021-00199-4

13. Murad D., Heryadi Y., Isa S., Budiharto W. Personalization of study material based on predicted final grades using multi-criteria user-collaborative filtering recommender system. Education and Information Technologies. 2020 June 05. DOI: 25.10.1007/s10639-020-10238-9

14. Jagadeesan S., Jayashri S. Real-time personalization and recommendation in adaptive learning management system. Journal of Ambient Intelligence and Humanized Computing. 2020; Nov: 1–11. DOI: 10.1007/s12652-020-01729-1

15. Sarwar S., Qayyum Z., García C., Raúl, Safyan M., Faisal R. Ontology based E-learning framework: A personalized, adaptive and context aware model. Multimedia Tools and Applications. 2019; 1 (78). DOI: 10.1007/s11042-019-08125-8

16. Muhammad A., Ariatmanto D. Understanding the role of individual learner in adaptive and personalized e-learning system. Bulletin of Electrical Engineering and Informatics. 2021; 6 (10): 3313–3324. DOI: 10.11591/eei.v10i6.3192

17. Cheung S., Wang F. L., Kwok L., Poulová P. In search of the good practices of personalized learning. Interactive Learning Environments. 2021; 29: 179–181. DOI: 10.1080/10494820.2021.1894830

18. García Martínez J., César Rosa-Napal, Romero-Tabeayo I., Lopez S., Fuentes-Abeledo E. Digital tools and personal learning environments: An analysis in higher education. Sustainability. 2020; 12. DOI: 10.3390/su12198180

19. C. K. M. Che Ku Nuraini, Shahbodin F., Md S. Mohd S., Nori A. M., Mohamad Siti N. M., Saaya Z. Educational technologies in a personalised learning environment (PLE): An overview. World Transactions on Engineering and Technology Education [Internet]. 2020 [cited 2021 Sep 10]; 18: 485–490. Available from: https://www.researchgate.net/publication/346371490_Educational_technologies_in_a_personalised_learning_environment_PLE_an_overview

20. Peng H., Ma S., Spector J. Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments. 2019; 6: 171–176. DOI: 10.1186/s40561-019-0089-y

21. Zaslavsky A. Design of automation system for building personal education trajectories of students. RUDN Journal of Informatization in Education. 2019; 16: 149–161. DOI: 10.22363/2312-8631-2019-16-2-149-161

22. Zeer E. F., Symaniuk E. E. Theoretical and applied foundations of personalized education: development prospects. Pedagogicheskoye obrazovaniye v Rossii = Pedagogical Education in Russia [Internet]. 2021 [cited 2021 Sep 10]; 1: 17–25. Available from: https://www.pedobrazovanie.ru/jour/article/view/547/547 (In Russ.)

23. Zeer E. F. Personalized learning activities of students as a factor in their preparation for their professional future. Professional’noye obrazovaniye i rynok truda = Vocational Education and Labor Market [Internet]. 2021 [cited 2021 Sep 10]; 1 (44): 104–114. Available from: https://elibrary.ru/download/elibrary_44807096_11404549.pdf (In Russ.)

24. Reilly D. The pace of instructional presentation, nonlinear systems, effectiveness of cognitive processing, and needed research in the use of technology for instruction. Journal of Instructional Psychology [Internet]. 1998 [cited 2021 Sep 10]; 3 (25): 151–165. Available from: http://directory.umm.ac.id/DataElmu/journal/I/InternationalJournalofEducationalManagement/Vol14.Issue1.2000/06014aa2.pdf

25. Berezhnaya I. F. On the issue of designing a non-linear educational process in the higher education system. Vestnik Voronezhskogo gosudarstvennogo tekhnicheskogo universiteta = Voronezh State Technical University Bulletin [Internet]. 2014 [cited 2021 Sep 10]; 10 (5–2): 16–20. Available from: https://elibrary.ru/item.asp?id=24094625 (In Russ.)

26. Nelineynaya model’ rossiyskogo vysshego obrazovaniya v makroregione: teoreticheskaya kontseptsiya i prakticheskiye vozmozhnosti = Nonlinear model of Russian higher education in the macroregion: Theoretical concept and practical possibilities [Internet]. Ed. by G. E. Zborovsky. Ekaterinburg: Humanities University; 2016 [cited 2021 Sep 10]. 336 p. Available from: http://elar.urfu.ru/handle/10995/43856 (In Russ.)

27. Mokiy V. S., Lukyanova T. A. From disciplinarity to transdisciplinarity in concepts and definitions. Universum: Obshchestvennyye nauki = Universum: Social Sciences [Internet]. 2016 [cited 2021 Sep 10]; 7. Available from: http://7universum.com/ru/social/archive/item/3435 (In Russ.)