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Convergent approach to synthesis of the information learning environment for higher education

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The article considers a convergent approach to the synthesis of the information learning environment for higher education, which includes tools for managing educational content and learning trajectories. The process of convergence is defined as synchronization and coordination of electronic educational resources, educational programs and skill levels of specialists. The process is presented within the framework of interaction and lifecycle model synchronization for components of the information learning environment. The environment ensures the convergence of new educational models (electronic, mobile, cloud, mixed, ubiquitous) on the basis of a unified educational management system. The system includes the Alfresco educational content management subsystem, the Moodle learning management subsystem, the learning material presentation subsystem, the knowledge assessment subsystem, the learning activity management subsystem, the requirements of education standards and employers analysis subsystem.

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  • Alfresco website. Retrieved from (accessed 30 June 2018).

  • Arshinov, V. I., & Budanov, V. G. (2016). The paradigm of complexity and sociohumanitarian projections of convergent technologies. Voprosy filosofii [Problems of Philosophy]., 1, 59–70 [in Russian].

    Google Scholar 

  • Bainbridge, M. S., & Roco, M. C. (2005). Managing Nano-bio-info-CognoInnovations: Converging Technologies in Society. NY: Springer.

    Google Scholar 

  • Bersin, J. (2004). How did we get Here? The history of blended learning. The Blended Learning Book: Best Practices, Proven Methodologies, and Lessons Learned. NY, John Wiley & Sons.

  • Bhatia, G., Anand, M., & Shrivastava, P. (2012). Cloud computing technology in education system. International Journal of Advanced Technology & Engineering Research, 2, 2250–3536.

    Google Scholar 

  • Canton, J. (2004). Designing the future: NBIC technologies and human performance enhancement. Annals of the New York Academy of Sciences, 1013, 186–198.

    Article  Google Scholar 

  • Chan, T., Hue, C., Chou, C., & Tzeng, O. (2001). Four spaces of network learning models. Computers & Education., 37, 141–161.

    Article  Google Scholar 

  • Chul, L., & Gunno, P. (2016). The impact of convergence between science and technology on innovation. The Journal of Technology Transfer, 2, 1–23.

    Google Scholar 

  • Cloete, E. (2001). Electronic education system model. Computers & Education, 36, 171–182.

    Article  Google Scholar 

  • Cooch, M. (2010). Moodle 2.0 First Look. Packt publishing.

  • Cope, C., & Staehr, L. (2005). Improving students’ learning approaches through intervention in an information systems learning environment. Studies in Higher Education, 30(2), 181–197.

    Article  Google Scholar 

  • Cordova A. (2016). 10 Big Ideas for Future NSF Investments National Science Foundation. Retrieved from

  • Culén, Alma Leora & Gasparini, Andrea. (2019). STEAM Education: Why Learn Design Thinking?: Science, Technology, Engineering, Arts and Mathematics. In book: Promoting Language and STEAM as Human Rights in Education, pp.91–108.

  • Deev, M.V., Glotova, T.V., & Krevskiy, I.G. (2014). Models of supporting continuing education of specialists for high-tech sector. In Proceedings of the 11th Joint Conference Knowledge-Based Software Engineering. (vol. 466, pp. 100–112). Volgograd (Russia): Springer.

  • Deev, M.V., Glotova, T.V., & Krevskiy, I.G. (2015). Individualized Learning Trajectories Using Distance Education Technologies. Creativity in Intelligent, Technologies and Data Science. Series "Communications in Computer and Information Science". 535, 778–792.

  • Duncan-Howell, J., & Lee, K. (2007). M-learning: Finding a place for mobile technologies within tertiary educational settings, in ICT Proceedings ascilite: Providing choices for learners and learning. Singapore. Retrieved from

  • Finogeev, A. G., Fionova, L. R., Finogeev, A. A., & Vinh, T. Q. (2015). Learning Management System for the Development of Professional Competencies. Creativity in Intelligent Technologies and Data Science. Series «Communications in Computer and Information Science», 535, 793–803.

    Google Scholar 

  • Finogeev, A. G., Parygin, D. S., & Finogeev, A. A. (2017). The convergence computing model for big sensor data mining and knowledge discovery. Human-centric Computing and Information Sciences., 7, 11.

    Article  Google Scholar 

  • Hamidi, F. (2011). Information Technology in Education. Procedia Computer Science, 3, 369–375.

    Article  Google Scholar 

  • Harmelen, M. (2008). Design trajectories: Four experiments in PLE implementation. Interactive Learning Environments, 16(1), 35–46.

    Article  Google Scholar 

  • Herr D.J.C. (2016) The need for convergence and emergence in 21st century Nano-STEAM+ educational ecosystems. In K. Winkelmann and G. Bhushan, (Eds.), Global Perspectives of Nanoscience and Engineering Education, pp. 81-115, springer international publishing (springer nature) ISBN 978-3-319-31833-2.

  • Hirner, L., & Kochtanek, T. (2012). Quality indicators of online programs. Community College Journal of Research and Practice, 36(2), 122–130.

    Article  Google Scholar 

  • Horton, W. (2000). Designing web-based training: How to teach anyone anything anywhere anytime. NY: John Wiley & Sons.

    Google Scholar 

  • Hwang, Gwo-Jen. (2006). Criteria and strategies of ubiquitous learning, in Proceedings of the Sensor Networks, Ubiquitous, and Trustworthy Computing, (pp. 72–77). IEEE International Conference.

  • Januszewski, A. (2001). Educational technology: The development of a concept. Libraries Unlimited. isbn:1-56308-749-9.

    Google Scholar 

  • Kalogeras, S. (2015). Media-education convergence. International Journal of Information and Communication Technology Education., 9, 1–11.

    Article  Google Scholar 

  • Kravets, A. G., Belov, A. G., & Sadovnikova, N. P. (2016). Models and methods of professional competence level research. Recent Patents on Computer Science., 9(2), 150–159.

    Article  Google Scholar 

  • LAMS Internationalization website. Retrieved from (accessed 24 June 2018).

  • Martens, A., Sandkuhl, K., Lantow, B., Lehmann, H., Lettau, W.-D., & Radisch, F. (2019). An evaluation approach for smart support of teaching and learning processes. Smart Learning Environments, 6, 2.

    Article  Google Scholar 

  • Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309–326.

    Article  Google Scholar 

  • Mouna, D., Tlili, A., Essalmi, F., & Jemni, M. (2018). Implicit modeling of learners’ personalities in a game-based learning environment using their gaming behaviors. Smart Learning Environments, 5, 29.

    Article  Google Scholar 

  • National Research Council (U.S.). Committee on Key Challenge Areas for Convergence and Health. (2014). Convergence: Facilitating Transdiciplinary Integration of Life Sciences, Physical Sciences, Engineering and Beyond, National Academies Press (NAP 18722), ISBN 978–0=309=30151–0.

  • Olofsson, A. D., Lindberg, J. O., & Hauge, T. E. (2011). Blogs and the design of reflective peer-to-peer technology-enhanced learning and formative assessment. Campus-Wide Information Systems, 28, 183–194.

    Article  Google Scholar 

  • Personal Learning Environment. (2008). Retrieved from

  • Roco M.C. (2015) Principles and methods that facilitate convergence. In: Bainbridge W., Roco M. (eds) Handbook of science and technology convergence. Springer, Cham.

  • Roco, M., & Bainbridge W. (2004). Converging Technologies for Improving Human Performance: Nanotechnology, biotechnology, Information Technology and Cognitive Science. Arlington. . Retrieved from

  • Schatsky, D., Muraskin, C., & Gurumurthy, R. (2015). Cognitive technologies: The real opportunities for business. Deloitte Review., 16, 56–74.

    Google Scholar 

  • Severance, C., & Whyte, A. (2008). The coming functionality mash-up in personal learning environments. Interactive Learning Environments., 16(1), 47–62.

    Article  Google Scholar 

  • Sharp PA, Cooney CL, Kastner MA, Lees J, Sasisekharan R, Yaffe MB, Bhatia SN, Jacks TE, Lauffenburger DA, Langer R, Hammond PT, Sur M (2011) The third revolution: the convergence of the life sciences, physical sciences, and engineering. Massachusetts Institute of Technology, Washington, DC, [online]. Available:

  • G. Siemens (2005). Connectivism: A learning theory for the digital age. Retrieved from

  • SRC-NSF Report (2016). Intelligent Cognitive Assistants Workshop Summary and Recommendations,

  • Tseng, J. C., Chu, H. C., Hwang, G. J., & Tsai, C. C. (2008). Development of an adaptive learning system with two sources of personalization information. Computers and Education, 51(2), 776–786.

  • Van Gog, T., Sluijsmans, D., Joosten, B., & Prins, F. (2010). Formative assessment in an online learning environment to support flexible on-the-job learning in complex professional domains. Educational Technology Research and Development, 58(3), 311–324.

    Article  Google Scholar 

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The reported study was funded by Russian Foundation for Basic Research (RFBR) according to the project № 19-013-00409, 18-07-00975, 18-010-00204


The reported study was funded by RFBR according to the projects: № 19–013-00409, 18-010-00204, 18–07-00975.

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Correspondence to Alexey Finogeev.

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Finogeev, A., Gamidullaeva, L., Bershadsky, A. et al. Convergent approach to synthesis of the information learning environment for higher education. Educ Inf Technol 25, 11–30 (2020).

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