Trainable generator of educational content

Vladimir Rotkin


As the main problem of the research, the possibility of creating a universal educational platform that combines the possibilities of an online generation of educational content with the interface of the training process itself was considered. The methodology of the educational platform has been developed, in which the mass generation of content is carried out at random, based on simulation models of educational objects. A matrix interface is used, which allows performing custom operations by entering a sequence of typical operators. The system forms a reference base of operators, replenishing it from user solutions, which makes it possible to train and improve the system in order to provide methodological support to student users. An active demo layout of an educational content generator was created and tested, using the example of a specific problem from school mathematics. All methodological options function in the layout. There are three interface options: administrative, training and control. It was concluded that the approach based on the simulation of educational objects makes it possible to create a unified algorithmic platform that combines the functions of content generation with educational training. The system contains a unique option to teach yourself based on its interaction with students.


Muhammad Muhammad Suleiman, Adamu Tijjani Yahya & Mohammed Tukur, “Effective Utilization of ICT Tools in Higher Education”. Journal of Xidian University 14(9): pp. 588-594, 2020.

Aboobaker, N. and Zakkariya, K.A. "Influence of digital learning orientation and readiness for change on innovative work behaviour: reflections from the higher education sector", Development and Learning in Organizations, Vol. 34 No. 2, pp. 25-28, 2019.

José Manuel Salum Tomé, “The ICT and New Scenarios for Diversity”. Sustainability in Environment, ISSN 2470-637X (Print) ISSN 2470-6388 (Online), Vol. 5, No. 3, 2020.

Dziuban, C.; Graham, C.R.; Moskal, P.D. et al.. “Blended learning: the new normal and emerging technologies”. Int J Educ Technol High Educ 15, 3, 2018.

Haugsbakken, H., Nykvist, S., & Lysne, D. “The Need to Focus on Digital Pedagogy for Online Learning”. European Journal Of Education, 2(3), 25-31, 2019.

Lacka, Ewelina & Wong, T. C. “Examining the impact of digital technologies on students’ higher education outcomes: the case of the virtual learning environment and social media”, Studies in Higher Education, 2019.

Orthaber, M. “Experiences with a blended learning concept in a first year engineering mechanics course”, ICERI2019 Proceedings, pp. 9229-9239, 2019.

Orthaber, Markus; Stütz, Dominik; Antretter, Thomas; Ebner, Martin. “Concepts for E-Assessments in STEM on the Example of Engineering Mechanics”. International Journal of Emerging Technologies in Learning, Vol 15, No 12, p.p. 136-152, 2020.

Orthaber, M.; Antretter, T.; Jurisits, R.; Schemmel, M. “E-assessment in engineering mechanics: how does it compare to classical paper-pencil exams?”, ICERI2019 Proceedings, pp. 9381-9390, 2019.

Belwal, C. and Cheng, A. M. K. “An Extensible Framework for Real-Time Task Generation and Simulation, 17th International Conference on Embedded and Real-Time”. Computing Systems and Applications, Toyama, , pp. 259-263, 2011.

Abe, K.; Cortez, R. and Vazhenin, A. “Task management strategies for automatic task generation and verification”, International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013), Aizu-Wakamatsu, pp. 601-606, 2013,

Dorodchi, M.; Al-Hossami, E.; Benedict, A. and Demeter, E. “Using Synthetic Data Generators to Promote Open Science in Higher Education Learning Analytics”, International Conference on Big Data (Big Data), Los Angeles, CA, USA, pp. 4672-4675, 2019.

Rüdian, S. & Pinkwart N. “Towards an Automatic Q&A Generation for Online Courses - A Pipeline Based Approach”. In: Isotani S., Millán E., Ogan A., Hastings P., McLaren B., Luckin R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science, vol 11626. Springer, Cham. 2019.

Shengqing Chen, Xiaojian Huang, Jiaze Fang and Jia Liang. “Machine Learning-based Intelligent Formal Reasoning and Proving System”. IOP Conference Series: Materials Science and Engineering, Volume 322, Issue 5, 7 p, 2018.

van Terheyden, A. G. R. and Chalcraft, D. A. “Combining inductive and deductive reasoning”. Computer-Aided Engineering Journal, vol. 4, no. 1, pp. 24-28, 1987.

Turini F.; Baglioni, M.; Furletti, B.; Rinzivillo, S. “Examples of Integration of Induction and Deduction in Knowledge Discovery”. In: Stock O., Schaerf M. (eds) Reasoning, Action and Interaction in AI Theories and Systems. Lecture Notes in Computer Science, vol 4155. Springer, Berlin, Heidelberg, 2006.

Vagale, V.; Niedrite, L.; Ignatjeva, S. “The Use of the Recommended Learning Path in the Personalized Adaptive E-Learning System”. In: Robal T., Haav HM., Penjam J., Matulevičius R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. 2020.

Murano, P. “Anthropomorphic vs. Non-anthropomorphic Software Interface Feedback for Online Systems Usage”. In: Carbonell N., Stephanidis C. (eds) Universal Access Theoretical Perspectives, Practice, and Experience. UI4ALL 2002. Lecture Notes in Computer Science, vol 2615. Springer, Berlin, Heidelberg, 2003.

Naamati Schneider, L. & Meirovich, A. “Student Guided Learning - from Teaching to E – learning”. Revista Romaneasca Pentru Educatie Multidimensionala, 12(1Sup2), 115-121, 2020.

Rotkin, V. “Methodology of immanent learning content”. Journal Scientific Isra-el-Technological Advantages, 19(4): 112-118, 2017. . _LEARNING_CONTENT

Rotkin, Vladimir; Yavich, Roman; Malev, Sergey. “Concept of A.I. Based Knowledge Generator”. Journal of Education and e-Learning Research, Vol. 5, No. 4, 235-241, 2018.

Yavich, Roman; Malev, Sergey; Rotkin, Vladimir. “Triangle Generator for Online Mathematical E-learning”. Higher Education Studies 10(3):72, 2020. (DOI: 10.5539 / hes.v10n3p72)

Zvolinsky, V.P; Rotkin, V.M; Golovi,. V.G. & Matveeva, N.I., “Automated systems for the formation of educational content” [Avtomatizirovannie sistemi formirovania uchebnogo kontenta], Scientific monograph. Volgograd: VSAU. р: 120, 2017. FORMATION_OF_EDUCATIONAL_CONTENT_AVTOMATIZIROVANNYE_SISTEMY_FORMIROVANIA_UCEBNOGO_KONTENTA

Rotkin, V. “Generation of training initial-generation content”. Electrotechnic and Computer Systems, (32(108), 66-73, 2020.

Rotkin, Vladimir. “Intelligent generator of knowledge based on moderated machine learning. Demo layout”. Presentation, ResearchGate. 2020. / RG.2.2.30168.93448



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