The state of the art and perspectives of using adaptive cloud-based learning systems in higher education pedagogical institutions (the scope of Ukraine)

Authors

  • Юлія Носенко Institute of Information Technologies and Learning Tools National Academy of Education Sciences of Ukraine
  • Майя Попель Institute of Information Technologies and Learning Tools National Academy of Education Sciences of Ukraine
  • Марія Шишкіна Institute of Information Technologies and Learning Tools National Academy of Education Sciences of Ukraine

DOI:

https://doi.org/10.31812/pedag.v52i0.3776

Keywords:

cloud technology, learning-scientific environment, higher education pedagogical institution, adaptive cloud oriented learning system (ACLS)

Abstract

The article deals with the problems of using adaptive cloud-based learning systems (ACLS) in the modern high-tech educational environment and expanding access to them as tools of educational and research activity at higher education pedagogical institutions in Ukraine. The conceptual apparatus of cloud-based adaptive learning systems application and design is considered; their main characteristics are revealed; the ways of their pedagogical application are described. The experience of Institute of Information Technologies and Learning Tools of NAES of Ukraine on designing and applying of the cloud-based learning and research environment is outlined. The results of the survey of 31 higher education pedagogical institutions on using ACLS are presented. It is established that in the near future ACLS will become the driving force behind the development of new pedagogy, new strategies for personalizing education, and expanding opportunities for active learning.

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References

Brusilovsky, P., Peylo, С.: Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence 13 (2–4), 159–172 (2003).

Bykov, V. Yu., Shyshkina, M. P.: The conceptual basis of the university cloud-based learning and research environment formation and development in view of the open science priorities. Information Technologies and Learning Tools 68 (6), 1–19 (2018). doi: 10.33407/itlt.v68i6.2609 DOI: https://doi.org/10.33407/itlt.v68i6.2609

Fedoruk, P. I. Adaptyvna systema dystantsiinoho navchannia ta kontroliu znan na bazi intelektualnykh Internet-tekhnolohii (Adaptive system of distance learning and knowledge control based on intellectual

Internet technologies). Prykarpatskyi natsionalnyi universytet imeni Vasylia Stefanyka, Ivano-Frankivsk (2008).

Fedoruk, P. I.: Adaptatsiia protsesu navchannia v systemakh dystantsiinoi osvity na osnovi otsinky shvydkosti spryiniattia ta zasvoiennia znan studentamy (Adaptation of the process of education in the distance learning systems on the base of the quick perception and retention of knowledge by the students). Matematychni mashyny i systemy 2, 96–106 (2006).

Fedoruk, P. I.: Metodolohiia orhanizatsii protsesu indyvidualizovanoho navchannia iz vykorystanniam adaptyvnoi systemy dystantsiinoho navchannia ta kontroliu znan EduPro (Methodology of organizing process of individualized learning with using adaptive system of distance education and knowledge control EduPro). Medychna informatyka ta inzheneriia 2, 28–34 (2010).

Filiposka, S., Demchenko, Y., Karaliotas, T., de Vos, M., Regvart, D.:: Distributed cloud services based on programmable agile networks. European Journal of Higher Education IT 2, 1–16. http://www.eunis.org/download/TNC2016/08-paper-TNC2016-2.pdf (2016). Accessed 21 Mar 2018.

Fomin, V. N., Fradkov, A. L., Yakubovich, V. A.: Adaptivnoe upravlenie dinamicheskimi obektami (Adaptive Control of Dynamic Systems). Nauka, Moscow (1981).

Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., Hall, C.: NMC Horizon Report: 2016 Higher Education Edition. The New Media Consortium, Austin (2016).

Kasyanova, E. V.: Adaptivnaia sistema podderzhki distantcionnogo obucheniia programmirovaniiu (An adaptive system of support for distant education in programming). In: Kasyanov, V. N. (ed.) Problems of intellectualization and quality of informatics systems, pp. 85–112. Insitut sistem informatiki imeni A. P. Ershova SO RAN, Novosibirsk (2006).

Nakic, J., Granic, A., Glavinic, V.: Anatomy of Student Models in Adaptive Learning Systems: A Systematic Literature Review of Individual Differences from 2001 to 2013. Journal of Educational Computing Research 51 (4), 459–489 (2015). doi: 10.2190/EC.51.4.e DOI: https://doi.org/10.2190/EC.51.4.e

Petrova, M. Ye., Mintii, M.vM., Semerikov, S. O., Volkova, N. P.: Development of adaptive educational software on the topic of “Fractional Numbers” for students in grade 5. In: Kiv, A. E., Semerikov, S. O., Soloviev, V. N., Striuk, A. M. (eds.) Proceedings of the 1st Student Workshop on Computer Science & Software Engineering (CS&SE@SW 2018), Kryvyi Rih, Ukraine, November 30, 2018. CEUR Workshop Proceedings 2292, 162–192. http://ceur-ws.org/Vol-2292/paper19.pdf (2018). Accessed 15 Dec 2018.

Project “V4+ Academic Research Consortium integrating databases, robotics and languages technologies” (2018–2019). Institute of Information Technologies and Learning Tools of the NAES of Ukraine. http://iitlt.gov.ua/eng/working/academic-research-consortium.php (2018). Accessed 21 Dec 2018.

Pryima, S. M.: Osoblyvosti funktsionuvannia intelektualnykh adaptyvnykh navchalnykh system vidkrytoi osvity doroslykh (Features of functioning of intellectual adaptive educational systems of open adult

education). Visnyk Natsionalnoi akademii Derzhavnoi prykordonnoi sluzhby Ukrainy 3, 241–254 (2012).

Pugliese, L.: Adaptive Learning Systems: Surviving the Storm. EDUCAUSE Review. https://er.educause.edu/articles /2016/10/adaptive-learning-systems-surviving-the-storm (2016). Accessed 21 Mar 2018.

Pugliese, L.: The Visualization for an Ideal Adaptable Learning Ecosystem. IMS Global Learning Consortium. https://www.imsglobal.org/adaptive-adaptable-next-generation-personalized-earning#visualizationforidealadaptablelearningecosystem (2015). Accessed 21 Mar 2018.

Salomoni, D., Campos, I., Gaido, L., de Lucas, J. M., Solagna, P., Gomes, J., Matyska, L., Fuhrman, P., Hardt, M., Donvito, G., Dutka, L., Plociennik, M., Barbera, R., Blanquer, I., Ceccanti, A., Cetinic, E., David, M., Duma, C., L ́opez-Garc ́ıa, A., Molt ́o, G., Orviz, P., Sustr, Z., Viljoen, M., Aguilar, F., Alves, L., Antonacci, M., Antonelli, L. A., Bagnasco, S., Bonvin, A. M. J. J., Bruno, R., Chen, Y., Costa, A., Davidovic, D., Ertl, B., Fargetta, M., Fiore, S., Gallozzi, S., Kurkcuoglu, Z., Lloret, L., Martins, J., Nuzzo, A., Nassisi, P., Palazzo, C., Pina, J., Sciacca, E., Spiga, D., Tangaro, M., Urbaniak, M., Vallero, S., Wegh, B., Zaccolo, V., Zambelli, F., Zok, T.: INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures. Journal of Grid Computing 16 (3), 381–408 (2018). doi: 10.1007/s10723-018-9453-3 DOI: https://doi.org/10.1007/s10723-018-9453-3

Semerikov, S. O., Teplytskyi, I. O.: Metodyka uvedennia osnov Machine learning u shkilnomu kursi informatyky (Methods of introducing the basics of Machine learning in the school course of informatics). In: Problems of informatization of the educational process in institutions of general secondary and higher education, Ukrainian scientific and practical conference, Kyiv, October 09, 2018, pp. 18–20. Vyd-vo NPU imeni M. P. Drahomanova, Kyiv (2018).

Semerikov, S. O.: Zastosuvannia metodiv mashynnoho navchannia u navchanni modeliuvannia maibutnikh uchyteliv khimii (The use of machine learning methods in teaching modeling future chemistry teachers). In: Starova, T. V. (ed.) Technologies of teaching chemistry at school and university, Ukrainian Scientific and Practical Internet Conference, Kryvyi Rih, November 2018, pp. 10–19. KDPU, Kryvyi Rih (2018).

Sonwalkar, N.: The First Adaptive MOOC: A Case Study on Pedagogy Framework and Scalable Cloud Architecture. MOOCs FORUM 1 (P), 22–29. doi: 10.1089/mooc.2013.0007 DOI: https://doi.org/10.1089/mooc.2013.0007

Sragovich, V. G.: Adaptivnoe upravlenie (Adaptive control). Nauka, Moscow (1981).

Tseng, J. C. R., Chu, H.-C., Hwang, G.-J., Tsai, C.-C.: Development of an adaptive learning system with two sources of personalization information. Computers & Education 51 (2), 776–786 (2008). doi: 10.1016/j.compedu.2007.08.002 DOI: https://doi.org/10.1016/j.compedu.2007.08.002

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Published

19-12-2019

How to Cite

Носенко, Ю., Попель, М., & Шишкіна, М. (2019). The state of the art and perspectives of using adaptive cloud-based learning systems in higher education pedagogical institutions (the scope of Ukraine). Educational Dimension, 52, 56–69. https://doi.org/10.31812/pedag.v52i0.3776

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