CLOUD TECHNOLOGIES IN EDUCATION: THE BIBLIOGRAPHIC REVIEW
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DOI
Authors
a.yurchenko@fizmatsspu.sumy.ua
e.semenikhina@fizmatsspu.sumy.ua
Abstract
The paper considers the use of cloud technologies in education through the prism of bibliographic analysis. The article characterizes the current state of cloud technologies in education, summarizes the trends, and forecasts the directions of recent scientific research. The leading research methods were bibliographic (visual and quantitative) analysis of keyword networks and qualitative discussion. The bibliographic analysis is based on publications indexed by the scientometric database Web Of Science over the past 20 years. The sample for analysis was formed by searching for the words cloud technology, education, learning, and teaching. The results of the study showed: a significant increase in the popularity of cloud technologies in education in recent years; an increase in the number of studies related to various aspects of educational activities under the influence of Industry 4.0; a gradual increase in the number of studies on the virtualization of the educational process and the use of artificial intelligence in education; dissemination of research on the effectiveness of various types of training using cloud services and teaching methods based on artificial intelligence; the relevance of the trend of visualization of educational material and visual analysis in education. The qualitative discussion provided grounds to identify general trends regarding future research directions.: development of mass online courses and learning technologies (immersive, the use of virtual, augmented, and mixed reality, gaming learning technologies, BYOD approach); further virtualization of universities; development of inclusive education, educational analytics, and assessment (formative and adaptive computer assessment); early training of teachers to use cloud technologies and specialized services in subject learning; research related to visualization (big data, design, simulation, simulation of various processes, etc.) and the designing of relevant new academic disciplines; research of STEM and STEAM education.
Keywords:
References
Adtani R. et al.: Embracing ICT in academia: adopting and adapting to the new normal pedagogy. Global Knowledge Memory and Communication, 2023 [http://doi.org/10.1108/GKMC-03-2023-0089]. DOI: https://doi.org/10.1108/GKMC-03-2023-0089
Ahmad I. et al.: MOOC 5.0: A Roadmap to the Future of Learning. Sustainability 14(18), 2022, 11199 [http://doi.org/10.3390/su141811199]. DOI: https://doi.org/10.3390/su141811199
AL-Kebsi S. I., Mostafa A. O. M. S.: Trends and Challenges of Virtual Reality in Architectural Design Education. Journal of Architecture and Planning-king saud university 33(2), 2021, 191-215 [http://doi.org/10.33948/JAP-KSU-33-2-3]. DOI: https://doi.org/10.33948/JAP-KSU-33-2-3
Almusaed A. et al.: Enhancing Student Engagement: Harnessing "AIED"'s Power in Hybrid Education-A Review Analysis. Education Sciences 13(7), 2023, 632 [http://doi.org/10.3390/educsci13070632]. DOI: https://doi.org/10.3390/educsci13070632
Alotaibi N. S., Alshehri A. H.: Prospers and Obstacles in Using Artificial Intelligence in Saudi Arabia Higher Education Institutions-The Potential of AI-Based Learning Outcomes. Sustainability 15(13), 2023, 10723 [http://doi.org/10.3390/su151310723]. DOI: https://doi.org/10.3390/su151310723
Al-Qaysi N. et al.: Social media adoption in education: A systematic review of disciplines, applications, and influential factors. Technology in Society 73, 2023, 102249 [http://doi.org/10.1016/j.techsoc.2023.102249]. DOI: https://doi.org/10.1016/j.techsoc.2023.102249
Buhl M.: Computational Thinking Utilizing Visual Arts, or Maybe the Other Way Around. Proceedings of the 18th European Conference on E-learning, 2019, 102-108 [http://doi.org/10.34190/EEL.19.138]. DOI: https://doi.org/10.34190/EEL.19.138
Chen Y. et al.: Applications of Blockchain in Industry 4.0: a Review. Inf Syst Front, 2022 [http://doi.org/10.1007/s10796-022-10248-7]. DOI: https://doi.org/10.1007/s10796-022-10248-7
Dron V.: Formation of research competencies in students during computer modeling of physical phenomena and processes in distance learning. Physical and Mathematical Education 35(3), 2022, 19-25 [https://doi.org/10.31110/2413-1571-2022-035-3-003]. DOI: https://doi.org/10.31110/2413-1571-2022-035-3-003
Drushlyak M. et al.: Use of specialized software for the development of visual thinking of students and pupils. Innovative Educational Technologies, Tools, and Methods for E-learning. Scientific Editor Eugenia Smyrnova-Trybulska "E-learning", 12, Katowice–Cieszyn 2020, 147–158 [http://doi.org/10.34916/el.2020.12.13].
Drushlyak M.G. et al.: The Automated Control of Students Achievements by Using Paper Clicker Plickers. International conventions on Information and communication technology, electronics and Microelectronics – MIPRO 2020, 2020, 688-692 [http://doi.org/10.23919/MIPRO48935.2020.9245281]. DOI: https://doi.org/10.23919/MIPRO48935.2020.9245281
Fernandez A. et al.: Digital transformation initiatives in higher education institutions: A multivocal literature review. Educ Inf Technol 28, 2023, 12351–12382 [http://doi.org/10.1007/s10639-022-11544-0]. DOI: https://doi.org/10.1007/s10639-022-11544-0
Fernandez-Carames T. M., Fraga-Lamas P.: Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities. Applied sciences-Basel 9(21), 2019, 4479 [http://doi.org/10.3390/app9214479]. DOI: https://doi.org/10.3390/app9214479
Grassini S.: Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences 13(7), 2023, 692 [http://doi.org/10.3390/educsci13070692]. DOI: https://doi.org/10.3390/educsci13070692
Hassan R. H., Hassan M. T., Naseer S., Khan Z., Jeon M.: ICT Enabled TVET Education: A Systematic Literature Review. IEEE Access 9, 81624-81650 [http://doi.org/10.1109/ACCESS.2021.3085910]. DOI: https://doi.org/10.1109/ACCESS.2021.3085910
Hernandez-de-Menendez M., Diaz C. E. A., Morales-Menendez R.: Engineering education for smart 4.0 technology: a review. International Journal of interactive design and manufacturing 14(3), 2020, 789-803 [http://doi.org/10.1007/s12008-020-00672-x]. DOI: https://doi.org/10.1007/s12008-020-00672-x
Herrada R. I., Banos R., Alcayde A.: Student Response Systems: A Multidisciplinary Analysis Using Visual Analytics. Education Sciences 10(12), 2020, 348 [http://doi.org/10.3390/educsci10120348]. DOI: https://doi.org/10.3390/educsci10120348
Liu Z. J., Levina V., Frolova, Y.: Information Visualization in the Educational Process: Current Trends. International Journal of emerging technologies in learning 15(13), 2020, 49–62 [http://doi.org/10.3991/ijet.v15i13.14671]. DOI: https://doi.org/10.3991/ijet.v15i13.14671
Mallik S., Gangopadhyay A.: Proactive and reactive engagement of artificial intelligence methods for education: a review. Frontiers in artificial intelligence 6, 2023, 1151391 [http://doi.org/10.3389/frai.2023.1151391]. DOI: https://doi.org/10.3389/frai.2023.1151391
Mhlongo S. et al.: Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review. Heliyon 9(6), 2023, e16348 [http://doi.org/10.1016/j.heliyon.2023.e16348]. DOI: https://doi.org/10.1016/j.heliyon.2023.e16348
Mukul E., Buyukozkan G.: Digital transformation in education: A systematic review of education 4.0. Technological forecasting and social change 194, 2023, 122664 [http://doi.org/10.1016/j.techfore.2023.122664]. DOI: https://doi.org/10.1016/j.techfore.2023.122664
Palamarchuk A. S.: Using cloud service OneDrive in the educational process of the university. Physics and Mathematics Education 2(8), 2016, 87–92.
Rani S.: Amalgamation of Advanced Technologies for Sustainable Development of Smart City Environment: A Review. IEEE Access 9, 2021, 150060-150087 [http://doi.org/10.1109/ACCESS.2021.3125527]. DOI: https://doi.org/10.1109/ACCESS.2021.3125527
Rosli M.S.: A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps. Sustainability 14(18), 2022, 11389 [http://doi.org/10.3390/su141811389]. DOI: https://doi.org/10.3390/su141811389
Rudenko Yu. et al.: Online Learning with the Eyes of Teachers and Students in Educational Institutions of Ukraine. TEM Journal 10(2), 2021, 922‐931 [http://doi.org/10.18421/TEM102-55]. DOI: https://doi.org/10.18421/TEM102-55
Scalera M., Gentile E., Plantamura P., Dimauro G.: A Systematic Mapping Study in Cloud for Educational Innovation. Appl. Sci. 10(13), 2020, 4531 [http://doi.org/10.3390/app10134531]. DOI: https://doi.org/10.3390/app10134531
Semenikhina E. et al.: Cloud-based service GeoGebra and its use in the educational process: the BYOD approach. TEM JOURNAL – Technology, Education, Management, Informatics 8(1), 2019, 65–72 [http://doi.org/10.18421/TEM81-08].
Semenikhina O. et al.: The Formation of Skills to Visualize by the Tools of Computer Visualization. TEM Journal 9(4), 2020, 1704–1710. [http://doi.org/10.18421/TEM94-51]. DOI: https://doi.org/10.18421/TEM94-51
Semenikhina О. V., Drushliak М. G., Khvorostina Yu. V.: Use of GeoGebra cloud service in future math teachers’ teaching. Information Technologies and Learning Tools 73(5), 2019, 48–66 [http://doi.org/10.33407/itlt.v73i5.2500]. DOI: https://doi.org/10.33407/itlt.v73i5.2500
Shamonia V., Semenikhina О., Drushlyak M.: Use of the Proteus for visual modeling of the work of the information system basic elements. Physical and Mathematical Education 2(20), 2019, 160–165 [http://doi.org/10.31110/2413-1571-2019-020-2-025]. DOI: https://doi.org/10.31110/2413-1571-2019-020-2-025
Sharadgah T. A., Sa'di R. A.: A systematic review of research on the use of artificial intelligence in English language teaching and learning (2015-2021): what are the current effects? Journal of information technology education-research 21, 2022, 337–377 [http://doi.org/10.28945/4999]. DOI: https://doi.org/10.28945/4999
Shyshkina M., Nosenko Yu.: Cloud technologies of open science in the process of continuous training of ICT in education. Physical and Mathematical Education 37(5), 2022, 69–74 [http://doi.org/10.31110/2413-1571-2022-037-5-010]. DOI: https://doi.org/10.31110/2413-1571-2022-037-5-010
Smestad B. et al.: Examining dimensions of teachers' digital competence: A systematic review pre- and during COVID-19. Heliyon 9(6), 2023, e16677 [http://doi.org/10.1016/j.heliyon.2023.e16677]. DOI: https://doi.org/10.1016/j.heliyon.2023.e16677
Su J. H., Yang W. P.: Digital competence in early childhood education: A systematic review. Education and information technologies, 2023 [http://doi.org/10.1007/s10639-023-11972-6]. DOI: https://doi.org/10.1007/s10639-023-11972-6
Tamayo J. L. R., Hernandez M. B., Gomez H. G.: Digital Data Visualization with Interactive and Virtual Reality Tools. Review of Current State of the Art and Proposal of a Model. Journal ICONO 14 16(2), 2018 [http://doi.org/10.7195/ri14.v16i2.1174]. DOI: https://doi.org/10.7195/ri14.v16i2.1174
Technology in education: a tool on whose terms? Global education monitoring report, UNESCO, 2023 [https://unesdoc.unesco.org/ark:/48223/pf0000385723].
Thavi R. et al.: Role of cloud computing technology in the education sector. Journal of engineering design and Technology, 2021 [http://doi.org/10.1108/JEDT-08-2021-0417]. DOI: https://doi.org/10.1108/JEDT-08-2021-0417
Turinov A., Galdina A.: Application of computer modeling to solving quantum-mechanical problems. Physical and Mathematical Education 3(13), 2017, 170–177.
Vaicondam Y. et al.: Research Landscape of Digital Learning Over the Past 20 Years: A Bibliometric and Visualisation Analysis. International Journal of Online and biomedical engineering 18(8), 2022, 4–22 [http://doi.org/10.3991/ijoe.v18i08.31963]. DOI: https://doi.org/10.3991/ijoe.v18i08.31963
Vesic D., Lakovic D., Vesic S. L.: Use of information technologies in higher education from the aspect of management. International journal of cognitive research in science engineering and education 11(1), 2023, 143–151 [http://doi.org/10.23947/2334-8496-2023-11-1-143-151]. DOI: https://doi.org/10.23947/2334-8496-2023-11-1-143-151
Xu X. et al.: Review on A big data-based innovative knowledge teaching evaluation system in universities. Journal of innovation & knowledge 7(3), 2022, 100197 [http://doi.org/10.1016/j.jik.2022.100197]. DOI: https://doi.org/10.1016/j.jik.2022.100197
Yurchenko A. et al.: Using online IT-industry courses in the computer sciences specialists’ training. International Journal of Computer Science and Network Security 21(11), 2021, 97–104. [http://doi.org/10.22937/IJCSNS.2021.21.11.13].
Yurchenko A.: Digital physical laboratories as an important means of training of future teachers of physics. Physical and Mathematical Education 1(4), 2015, 55–63.
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