Skip to main content

Modeling the Dynamics of Knowledge Potential of Agents in the Educational Social and Communication Environment

  • Conference paper
  • First Online:
Advances in Intelligent Systems and Computing IV (CSIT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1080))

Included in the following conference series:

Abstract

The processes of information processing in the form of knowledge are at the forefront when considering the educational social and communication environment as a holistic system. In this paper, the authors examine the issue of modeling the personal educational (curriculum) program of a person who is studying during all life. The models of information processes for the redistribution of a knowledge potential of agents are created taking into account the units of its components. In particular, a multicomponent two-dimensional array of discrete values has been introduced to characterize procedures for the formation of agents’ professional competencies that are appropriate to their abilities, interests, motivations, psychodynamic and emotional characteristics, age and level of knowledge potential.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. New Ukrainian School: Conceptual principles of secondary school reform (2016)

    Google Scholar 

  2. Chen, Z., Liu, B.: Lifelong Machine Learning, p. 127. Morgan & Claypool Publishers, San Rafael (2016)

    Google Scholar 

  3. Fei, G., Wang, S., Liu, B.: Learning cumulatively to become more knowledgeable. In: Proceedings of the 22nd International Conference on Knowledge Discovery and Data Mining, pp. 1565–1574 (2016)

    Google Scholar 

  4. Meijers, F.: A dialogue worth having: vocational competence, career identity and a learning environment for twenty-first century success at work. In: de Bruijn, E., Billett, S., Onstenk, J. (eds.) Enhancing Teaching and Learning in the Dutch Vocational Education System, vol. 18, pp. 139–155. Springer, Cham (2017)

    Chapter  Google Scholar 

  5. Khetarpal, K., Sodhani, S., Chandar, S., Precup, D.: Environments for lifelong reinforcement learning. In: 2nd Continual Learning Workshop, Neural Information Processing Systems (2018)

    Google Scholar 

  6. Machado, M., Bellemare, M., Talvitie, E., Veness, J., Hausknecht, M., Bowling, M.: Revisiting the arcade learning environment: evaluation protocols and open problems for general agents. J. Artif. Intell. Res. 61, 523–562 (2018)

    Article  MathSciNet  Google Scholar 

  7. Nonaka, I., Krogh, G., Voelpel, S.: Organizational knowledge creation theory: evolutionary paths and future advances. Organ. Stud. 27(8), 1179–1208 (2006)

    Article  Google Scholar 

  8. Dobrynina, N.: Mathematical models of knowledge dissemination and management of the learning process of students. Sci.Theoret. J. Fundam. Res. 7, 7–9 (2009)

    Google Scholar 

  9. Artemenko, V.: Hybrid of an agent-based knowledge assessment model by distance learning participants. Educ. Technol. Soc. 2, 423–434 (2011)

    Google Scholar 

  10. Petrash, A.: Methodology of an informative mathematical model for the process. In: Innovative Computer Technology at the School, pp. 128–132 (2011)

    Google Scholar 

  11. Saviour, A., Mahama, F., Kuadey, N., Ankorah, C.: Mathematical model of knowledge management system in an organization. Global J. Manag. Bus. Res. Adm. Manag. 16 (2016)

    Google Scholar 

  12. Ibatullin, R., Anisimova, E.: Construction of individual educational trajectory of students based on e-learning. In: IEEE 10th International Conference on Application of Information and Communication Technologies (2016)

    Google Scholar 

  13. Bomba, A., Nazaruk, M., Kunanets, N., Pasichnyk, V.: Constructing the diffusion-like model of biocomponent knowledge potential distribution. Int. J. Comput. 16(2), 74–81 (2017)

    Google Scholar 

  14. Kunanets, N., Nazaruk, M., Pasichnyk, V., Nebesnyi, R.: Information technologies of personalized choice of professionals in smart cities. Inf. Technol. Learn. Tools 65(3), 277–290 (2018)

    Google Scholar 

  15. About Higher Education: The Law of Ukraine 01.07.2014, 1556-VII (2015)

    Google Scholar 

  16. Rashkevych, Yu.: Bologna Process and New Paradigm of Higher Education: Monograph, p. 168 (2014)

    Google Scholar 

  17. Bomba, A., Safonyk, A.: Mathematical simulation of the process of aerobic treatment of wastewater under conditions of diffusion and mass transfer perturbations. J. Eng. Phys. Thermophys. 91(2), 318–323 (2018)

    Article  Google Scholar 

  18. Pasichnyk, V., Bomba, A., Nazaruk, M., Kunanets, N., Bilak, Y.: Modeling the redistribution processes of knowledge potential in the formation of the professional competency system. In: IEEE 14th International Scientific and Technical Conference on Computer Sciences and Information Technologies (2019)

    Google Scholar 

  19. Galushkyn, A.: Theory of neural networks: a textbook for universities. Publishing Enterprise of the Radiotekhnika Magazine (2000). 215 p.

    Google Scholar 

  20. Flach, P.: Machine Learning: The Art and Science of Algorithms that Make Sense of Data, p. 396. Cambridge University Press, New York (2012)

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mariia Nazaruk .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bomba, A., Nazaruk, M., Kunanets, N., Pasichnyk, V. (2020). Modeling the Dynamics of Knowledge Potential of Agents in the Educational Social and Communication Environment. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing IV. CSIT 2019. Advances in Intelligent Systems and Computing, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-33695-0_2

Download citation

Publish with us

Policies and ethics