Умный подход к обучению в высшем образовании: на примере Санкт-Петербурга

Магистерская диссертация посвящена роли внеучебной деятельности как формы самообучения в контексте умного обучения путем анализа концепции умного обучения с целью определения единиц измерения, характеристик и атрибутов для выявления уровня интеллектуальности, а также определения места внеучебной деятельности студента как формы самообучения в рамках умного обучения. Определены информационные потоки, связанные с внеучебной деятельностью в существующем образовательном процессе. Целью диссертации является разработка методов и рекомендаций по сокращению информационных потоков о внеучебной деятельности. Теоретическая часть включает обзор литературы по данной теме, изучение вторичной информации: исследования на национальном и глобальном уровнях, обзор опыта успешной реализации концепции умного обучения, а также основных базовых показателей, выявление характеристик и атрибутов умного обучения на основе контент-анализа определений. В качестве практической прикладной части на основе проведенного исследования автор разрабатывает ряд рекомендаций по сокращению информационных путей и адаптации передачи информации с точки зрения концепции smart, которые могут быть использованы для более структурированной, эффективной передачи информации от производителя к получателю. Основное ожидание заключается в том, что предлагаемые методы могут быть использованы в сфере высшего образования в Санкт-Петербурге.

Introduction…………………………………………………………………………………..……6
1. Theoretical foundations of the concept of smart learning
1.1. Smart learning: conceptual approach …………………………………………………..10
1.2. Smart learning characteristics and attributes ……………………………………………14
1.3. Existing smart status criteria ……………………………………………………………23
1.4. The role of self-learning of student in the context of smart learning and their forms… .27
1.5. Summary of Chapter I………………………………………………………………….32
2. Extracurricular activity of the student and methods of transmitting information in the field
of higher education
2.1. Stakeholders in the learning processes.………………………………….……………..33
2.2. Problems of transmitting information on extracurricular activities……………………..36
2.3. Information flows within the educational organization of higher education and external information flows in the field of higher education………………………….………….45
2.4. Available regional resources informing about extracurricular activities………….……54
2.5. Recommendations for reducing the ways of delivering information on extracurricular activities …………………………………………………………………………………56
2.6. Summary of Chapter II…………………………………………………………………63
Conclusion……………………………………………………………………………………….64
References………………………………………………………………………………………..67
Appendix 1. Interview Guideline for representatives of the authorities in the field of higher education……………………………………………………………………………..…73
Appendix 2. Interview Guideline for representatives of higher educational institutions located
on the territory of St. Petersburg……………………………………………..….……..74
Appendix 3. Interview Guideline for organizers of extracurricular activities……………………75
Appendix 4. Questionnaire for students …………………………………………………………77
Appendix 5. Students’ survey results ……………………………………………………………78
Appendix 6. The card of accounting of the incoming documents to the Committee on Science
and Higher Education, reflecting the performers on the received request……………….82
Appendix 7. Requests received by the Committee on Science and Higher Education with
a request to provide information support for competitions………………………….…83
Appendix 8. Interview Guideline for the Director of the Coordination Center for International Scientific, Technical and Educational Programs……………………………………….87
Appendix 9. Visualization of the portal of extracurricular activities……………………………..88

1. Afanasyev, A., Voit, N., Kanev, D., Afanaseva, T. 2016. Organization, development and implementation of intelligent learning environments. In: Proceedings of the 10th International Technology, Education and Development Conference, INTED-2016, pp. 2232–2242;
2. Alawamleh, M., Al-Twait, L.M. and Al-Saht, G.R. 2020. The effect of online learning on communication between instructors and students during the Covid-19 pandemic. Asian Education and Development Studies. https://doi.org/10.1108/AEDS-06-2020- 013;
3. Aletdinova A. A., Melnichenko A. A. 2015. Development of smart education as an innovative technology. Bulletin of the Ugra state University. № S2 (37). 14-16;
4. Alieva L. V. 2013. Extracurricular activities of the university – the space of polysubject education. Education of students: pedagogical search: collection of scientific works. Moscow: NOU VPO «Academy of MNEPU», 100 p.;
5. Alieva L. V., Rudenko I. V., etc. 2017. Theoretical foundations of formation general professional competencies of students in the process of educational organizations: monograph. M.: Publishing House of the Academy of Natural Sciences, p. 172;
6. Ashfaque M. W., Tharewal S., Shaikh A. S., Banu S. S., Sohail M. A., Hannan S. A. 2014. Trends in education smart learning approach. International Journal of Advanced Research in Computer Science and Software Engineering 4 (10). 319-327;
7. Avdeeva, Z. K., Taratuhina, Y. V., Omarova, N. O. 2015. Smart educational environment as a platform for individualized learning adjusted to student’s cultural-cognitive profile. In: Smart Innovation, Systems and Technologies, vol. 41, pp. 219-229;
8. Babin E. N. 2018. Digitalization of the university: Construction of the integrated informational environment. University Management: Practice and Analysis. 22 (6): 44-54. (InRuss.);
9. Bandura, A. 1986. Social foundations of thought and action: Asocial cognitive theory. Englewood Cliffs, NJ: Prentice Hall;
10. Bandura, A. 1997. Self-efficacy: The exercise of control. New York: Freeman;
11. Bankovskaya N. I. 2010. Research of motivational characteristics of students ‘ self-education. pp. 282-293;
12. Candy, P. C. 2004. Linking thinking: Self-directed learning in the digital age. Commonwealth of Australia: Department of Education, Science and Training;
13. Chan T., Roschelle J., Hsi S., Kinshuk K., Sharples M., Brown T., Patton C. et al. One-to-one technology-enhanced learning: An opportunity for global research collaboration. Research and Practice in Technology Enhanced Learning, 2006, no. 1 (1), pp. 3–29;
14. Dneprovskaya N. V., Yankovskaya E. A., Shevtsova I. V. 2015. Conceptual foundations of the concept of smart education. Open education. № 6. 43-51;
15. Doran, G. T. 1981. There’s a S.M.A.R.T. way to write management’s goals and objectives // Management Review. Vol.70, no. 11;
16. Dron J. 2018 Smart learning environments, and not so smart learning environments: a systems view. Smart Learning Environments, vol. 5, №. 25,
17. Duran-Sanchez A., Garcia, J. A., Rama, D. R., Sarango-Lalangui, P. (2018). Analysis of the scientific literature published on smart learning. Espacios, 39(10). http://www.revistaespacios.com/a18v39n10/18391007.html
18. Fetter I. V., Petrukhina O. A. Competition as a form of organization of extracurricular activities in a pedagogical university. Problems of modern pedagogical education. Ser.: Pedagogy and psychology. Yalta. RIO GPA № 50(3). pp. 191-197;
19. Finogeev A., Kravets A., Deev M., Bershadsky A. and Gamidullaeva L. 2018. Life-cycle management of educational programs and resources in a smart learning environment Smart Learning Environments, vol. 5, №. 9;
20. García-Peñalvo F. J., Casado-Lumbreras C., Colomo-Palacios R., and Yadav A. 2020. Smart Learning. Applied Sciences 10 (19);
21. Gros B. 2016. The design of smart educational environments. Smart Learning Environments. vol. 3: № 15;
22. Helder, E., Sosnovsky, S., Dimitrova, V. Adaptive intelligent learning environments. In: Duval, E., Sharples, M., Sutherland, R. (eds.) Technology Enhanced Learning: Research Themes, pp. 109–114. Springer, New York (2017);
23. Hoel T., Mason J. 2018. Standards for smart education – towards a development framework. Smart Learning Environments, Vol 5, Issue 1. 1-25;
24. Hwang Y., Jin Y., Shim C., Choi K., Kim K. 2011. Study on history class design using GBS under smart learning environment. The Korean Journal of the Learning Sciences 5(1), рр. 57-81;
25. Hwang, G-J. 2014. Definition, framework and research issues of smart learning environments – A context-aware ubiquitous learning perspective. Smart Learning Environments 1(1),
pp. 492–414. URL: https://doi.org/10.1186/s40561-014-0004-5;
26. Hwang G.J., Chu H.C., Yin C., Ogata H. 2015. Transforming the educational settings: innovative designs and applications of learning technologies and learning environments. Interact. Learn. Environ. 23(2), pp. 127–129;
27. IASLE. 2018. Smart learning. Retrieved July 9 from http://iasle.net/about-us/background/
28. Ivanayskaya T. A. 2010. Extracurricular activities as a factor of professional self-determination of the student. Orenburg, 217 p.;
29. Jemni M, Khribi MK. The ALECSO Smart Learning Framework. In: Proceedings of International Conference on Smart Learning Environments (ICSLE 2016). p. 28–30;
30. Kanaeva T. M. 2012. The concept of extracurricular activities in the aspect of professional development of secondary school students. Modern studies of social problems (electronic scientific journal). №. 11 (19). URL: www.sisp.nkras.ru;
31. Kapustina L. M., Kondratenko Yu. N., On the concept of «smart enterprise» in the digital economy, a series of reports (green books) within the framework of the project «Industrial and Technological Foresight of the Russian Federation». St. Petersburg: Center for Strategic Research Foundation North-West, 2012, Issue 4. 62;
32. Kim J. L. and J. Altmann, (2013). Adapting Smartphones as Learning Technology in a Korean University. Journal of Integrated Design and Process Science, 17(1), 5-16;
33. Kim S., Song S.-M., Yoon Y.-I. 2011. Smart learning services based on smart cloud computing. Sensors 11(8), рр. 7835–7850;
34. Kinshuk C. N., Cheng, I., Chew, S. W. (2016). Evolution is not enough: Revolutionizing current learning environments to smart learning. International Journal of Artificial Intelligence in Education, 26(2), 561–581;
35. Knowles, M. S. 1975. Self-Directed Learning. New York: Association Press.Association Press, 291 Broadway, New York;
36. Konanchuk D., Volkov A. 2013. The era of «Greenfield» in education. Research. Sedek.
37. Koper, R. 2014. Conditions for effective smart learning environments. Smart Learning Environments, 1(1), 5;
38. Kose, U., Deperlioglu, O. 2012. Intelligent learning environments within blended learning for ensuring effective C programming course. Int. J. Artif. Intell. Appl. 3(1), 20;
39. Kwak D.-H. 2010. Meaning and Prospect for Smart Learning. In Proceedings from the seminar for Korea e-learning industry association;
40. Lee J.E., Jin S.M. 2014. Implementation of smart learning model for improving digital communication competencies of middle aged. The Journal of the Korea Contents Association 14(4), 522–533;
41. Lee J.E., Zo H., Lee H. 2014. Smart learning adoption in employees and HRD managers. British Journal of Educational Technology. 45(6), 1082–1096;
42. Liu X., Huang R., and Chang T.-W. 2016. Design of Theoretical Model for Smart Learning, in State-of-theArt and Future Directions of Smart Learning, pp. 77–86;
43. Lorenzo, N., Gallon, R. 2019. Smart pedagogy for smart learning. In L. Daniela (Ed.), Didactics of smart pedagogy, pp. 41–69;
44. Marathe S. 2018. Digitalization in education sector. International Journal of Trend in Scientific Research and Development (IJTSRD), Special Issue: International Conference on Digital Economy and its Impact on Business and Industry, pp. 51-56;
45. Markova, A. K. Psychology of professionalism. – M.: Obrazovanie, 1996. – p. 308;
46. Molina-Carmona, R.; Villagrá-Arnedo, C.J. 2018. Smart learning. In TEEM’18: Sixth Edition Technological Ecosystems for Enhancing Multiculturality, Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality, Salamanca, Spain, 24–26 October 2018; García-Peñalvo, F.J., Ed.; ACM: New York, NY, USA, 2018; p. 645–647;
47. Neustroev S. S. 2012. On the assessment of the contribution of the innovation factor and the results of the economic development of the region, Vol. 3 (21), 86-91;
48. Official city portal of the higher professional education system of Saint Petersburg‑St. Petersburg. Education and science. «Scientific and educational potential»;
49. Official website of the Administration of St. Petersburg;
50. Ong E.-T. 2006. The Malaysian smart schools project: An innovation to address sustainability. Presented at the 10th UNESCO-APEID International Conference on Education (Thailand, Bangkok) Retrieved from http://www.teo-education.com/teophotos/albums/userpics/ong_6B.doc;
51. Philling-Cormick, J. and Garrison, D. R. 2007. Self-Directed and Self-Regulated Learning: Conceptual Links. Canadian Journal of University Continuing Education, Vol. 33, № 2, pp. 13-33;
52. Pintrich, P. R. (2000). Multiple goals, multiple pathways: The role of goal orientation in learning and achievement. Journal of Educational Psychology, 92(3), 544–555. https://doi.org/10.1037/0022-0663.92.3.544;
53. Pintrich, P. R., & Zeidner, M. 2000. Handbook of self-regulation. San Diego, CA: Academic.
54. Pintrich, P., & Zusho, A. 2002. The development of academic self–regulation: The role of cognitive and motivational factors. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp. 249–284). San Diego: Academic;
55. Ponomareva S. V., Zakharova R. G., Barg M. A. 2015. Building a scheme of information flows of an educational organization. p. 1-9;
56. Popenici. S. Kerr. S December, 2017. Exploring the impact of artificial intelligence on teaching and learning in higher education. Journal ResearchGate;
57. Rean A. A. 2004. Personality Psychology is used. Socialization, behavior, communication.
St. Petersburg;
58. Rodkina, T. A. 2001. Information logistics. M.: Exam. р.353;
59. Roumen, E. S., Kovatcheva, N. E. 2017. Conceptualising of Smart Education. Online: https://www.researchgate.net/publication/320623528_Conceptualising_of_Smart_Education;
60. Schunk, D. H. 2005. Self-regulated learning: The educational legacy of Paul R. Pintrich. Educational Psychologist, 40, 85-94;
61. Sharples M., Adams A., Ferguson R., Gaved M., McAndrew P., Rienties B., Weller M., Whitelock D. 2014. Innovating Pedagogy. Open University Innovation Report 3. The Open University, Milton Keynes;
62. Song, L., & Hill, J. R. 2007. A conceptual understanding of self-directed learning in online environments. Journal of Interactive Online Learning, 6(1), 27 – 41;
63. Spector, J. M. 2014. Conceptualizing the emerging field of smart learning environments. Smart Learning Environments, 1(1), 2;
64. Spector, J. M. 2016. Smart learning environments: Concepts and issues. In Proceedings of SITE 2016, pp. 2728-2737;
65. Sung M., 2015. A study of adults’ perception and needs for smart learning. Procedia-Social and Behavioral Sciences 191, 115–120;
66. Tan, S. C., Divaharan, S., Tan, L., & Cheah, H. M. 2011. Self-directed learning with ICT: Theory, practice and assessment. Singapore: Ministry of Education;
67. Thomas, J. W., Strage, A., & Curley, R. 1988. Improving self-directed learning: Issues and guidelines. The Elementary School Journal, 88(3), 313 – 326;
68. Tikhomirov V., Dneprovskaya N., Yankovskaya E. 2015. Three dimensions of smart education, vol 41, pp. 47–56;
69. Tikhomirov. V. P. 6 April, 2011. The world is on the path of smart education. New opportunities for development. The journal «New technologies» of the Moscow state University of Economics, statistics and Informatics;
70. Uskov, V.L., Bakken, J.P., Heinemann, C., Rachakonda, R., Guduru, V.S., Thomas, A.B., Bodduluri, D.P., 2017. Building smart learning analytics system for smart university. International Conference on Smart Education and Smart E-Learning, vol 75 Springer International Publishing, pp. 191–204;
71. Vakhitova G. H. 2012. Organization of extracurricular activities of students in the context of the formation of their professional pedagogical competencies. Bulletin of the Tomsk State Pedagogical University (Vestnik). Issue. Issue № 11 (126). pp. 84-87;
72. Vintin I. A. 2006. Pedagogical foundations of social self-determination students in extracurricular activities at a higher educational institution. Saransk.
73. Wang S., Feng M., Cui W. 2018. Adaptive learning goes to China. Artificial Intelligence in Education, LNCS (LNAI), vol. 10948, 2018, pp. 89-93;
74. Zagrebina E.I., Sharafetdinova Z.G., Lushchik I.V., Konyushenko S.M, Ermoshina N.V., Kosyakova E.Y., Ashrafullina G.S. 2015. The Electronic Learning System as a Means of Forming Professional Competencies among University Students. J. Sustain. Dev. 8(3).
pp. 178–184;
75. Zhu Z.-T., Yu M.-H., Riezebos P. 2016. A research framework of smart education. Smart Learning Environments. Vol. 3 (4);
76. Zimmerman, B. J., & Martinez-Pons, M. 1988. Construct validation of a strategy model of student self-regulated learning. Journal of Educational Psychology, 80(3), 284–290. URL: https://doi.org/10.1037/0022-0663.80.3.284;