Online learning is widely distributed. This type of learning can take place at specific
university by means of learning management system or by means of massive open online course
platforms independently of universities. Management problems arise in existing training
systems if a training course contains assignments, result of implementation of which cannot be
checked by standard tests. This relates to knowledge and skills assimilation management and
to training process management. A class of assignments which causes difficulties in online
learning and training management (complex open ended assignments) is described in the paper.
A concept of online automated training process management based on the use of error bank in
implementing such tasks is suggested. The concept is based on system and process management
approach, classification of errors made by students during complex open ended assignment
implementation, the principle of management subsidiarity, automated training. Using of a
specific software package, which contains software modules for automated scoring,
information collection and processing, decision making, on a par with learning management
systems with functionality of the automated training is proposed to increase the effectiveness of
management
1. Talyzina N.F. Upravlenie protsessom usvoeniya znaniy. M.: Izd-vo Mosk.unta,1984. 345s.
2. Pozharkova I.N., Noskova E.E., Troyak E.Yu. Formirovanie individual'noy
obrazovatel'noy traektorii kak komponenta praktiko-orientirovannoy sredy
obucheniya // Pedagogicheskiy IMIDZh. 2018. № 3 (40). S. 179–192. DOI:
10.32343/2409-5052-2018-11-3-179-192.
3. Sonwalkar N.The First Adaptive MOOC: A Case Study on Pedagogy
Framework and Scalable Cloud Architecture// MOOCs Forum. 2013. Pp.22-
29. DOI: 10.1089/mooc.2013.0007. URL:
www.liebertpub.com/doi/10.1089/mooc.2013.0007.
4. Onah D.F., Sinclair J.E. Massive open online courses – an adaptive learning
framework// Proceeding of the 9th International Technology, Education and
Development Conference (INTED2015), 2-4 March, 2015, Madrid, Spain. Pp.
1258-1266.DOI: 10.13140/RG.2.1.4237.0083.
5. Daniel J., Vázquez C.E., Gisbert M. The Future of MOOCs: Adaptive
Learning or Business Model?// RUSC. Universities and Knowledge Society
Journal. 2015. V.12. №1. Pp. 64-73. URL:
https://rusc.uoc.edu/rusc/ca/index.php/rusc/article/view/v12n1-danielvazquez-gisbert/2455.html. DOI: 10.7238/rusc.v12i1.2475.
6. Rosen Y., Rushkin I., Rubin R. The effects of adaptive learning in a massive
open online course on learners' skill development// Proceedings of the Fifth
Annual ACM Conference on Learning at Scale, June 26 - 28, 2018, London,
United Kingdom. URL: learningatscale.acm.org/las2018/toc.html. DOI:
10.1145/3231644.3231651.
7. Mukhanova A.A., Mukhanov S.A. Tekhnologiya proektirovaniya i otsenki
testov v SDO Moodle // Sbornik nauchnykh trudov SWorld. – Vyp.3. T.22. –
Odessa: KUPRIENKO SV, 2013. – S. 27-35.
8. Latypova V.A. Slozhnye otkrytye zadachi v smeshannom i distantsionnom
avtomatizirovannom obuchenii // Inzhenernyy vestnik Dona. 2015. №3. S.58.
URL: ivdon.ru/ru/magazine/archive/n3y2015/3211.
9. Ofitsial'nyy sayt programmy Bizagi URL: bizagi.com.
10. Aalst V., Khey K. Upravlenie potokami rabot: modeli, metody i sistemy. M.:
FIZMATLIT, 2007. 316s.
Latypova Victoria Alexandrovna
Email: vikalaty@yandex.ru
Ufa State Aviation Technical University
Ufa, Russian Federation
