Volume 9, no. 4Pages 129 - 140
Software Set of Intellectual Support and Security of LMS MAI CLASS.NETA.V. Naumov, G.A. Mkhitaryan, A.A. Rybalko
The article discusses integration of mathematical methods and security components in a learning management system (LMS). The discussed methods provide a statistical analysis of user data in process of online training in mathematical disciplines and adapting the content of the system for different users. The software package allows automatic calculation of questions complexity and user ratings by using statistical data. This helps the system administrator to detect users which use illegal hints or help from others. A procedure is designed for content selection for a variety of tests and control activities, with restrictions and without a time limit for the test. Two probabilistic models were used during development of mathematical methods: the Rasch model to describe the probability of users' answer correctness and Van der Linden model to describe the time it took for a user to respond to the question. The software package contains special optimization procedures that estimate the parameters of these models based on the accumulated statistics across all users. Apart from discussing efficiency of LMS usage with the above mentioned methods, the article also discusses general security architecture of the LMS, a set of technologies used for developing system security with specific implementation examples. Full text
- learning management system; LMS; e-learning; statistical analysis; adaptive characteristics; system security container technologies.
- 1. Naumov A.V., Dzhumurat A.S., Inozemtsev A.O. [Distance Learning System for Mathematical Disciplines CLASS.NET]. Vestnik komp'yuternykh i informatsionnykh tekhnologiy [Herald of Computer and Information Technologies], 2014, vol. 1, no. 10, pp. 36-40. (in Russian)
2. Kibzun A.I., Panarin S.I. Generation of Integral Rating by Statistical Processing of the Test Results. Automation and Remote Control, 2012, no. 6, pp. 1029-1045. DOI: 10.1134/S0005117912060082
3. Kibzun A.I., Inozemtsev A.O. [Using the Maximum Likelihood Method to Estimate Test Complexity Levels. Automation and Remote Control, 2014, no. 4, pp. 607-621. DOI: 10.1134/S000511791404002X
4. Naumov A.V., Inozemtsev A.O. [The Algorithm of Formation of Individual Tasks in Distance Learning Systems]. Vestnik komp'iuternykh i informatsionnykh tekhnologii [Herald of Computer and Information Technologies], 2013, vol. 1, no. 6, pp. 35-42. (in Russian)
5. Rasch G. Probabilistic Models for Some Intelligence and Attainment Tests. The University of Chicago Press, 1980.
6. Van der Linden W.J. Conceptual Issues in Response-Time Modeling. Law School Admission Council, 2008.
7. Naumov A.V., Mkhitaryan G.A. On the Problem of Probabilistic Optimization for Tests within the Time-Limit. Automation and Remote Control, 2016, vol. 77, no. 9, pp. 1612-1621. DOI: 10.1134/S0005117916090083
8. Naumov A.V., Say Khin Aung Tint. [On the Adaptation of Learning Systems for the Retraining of Young Specialists at the Enterprises of Aviation Complex]. Elektronnyy zhurnal 'Trudy MAI', 2011, issue 42, pp. 230-236. (in Russian)
9. Dzhumurat A.S. [Mathematical Methods of Adaptation of LMS CLASS.NET]. Nauka i obrazovanie v sovremennoy konkurentnoy srede: materialy Mezhdunarodnoy nauchno-prakticheskoy konferentsii [Science and Education in Today's Competitive Environment: Materials of the International Scientific-Practical Conference]. Ufa, 2014, vol. 2, no. 6, pp. 211-215.
10. Rybalko А.А. [Virtualization as the Foundation of Computer Security Systems of New Generation]. Vestnik Moskovskogo Aviatsionnogo Instituta, 2009, vol. 16, no. 2, pp. 12-18. (in Russian)
11. Rybalko А.А. [Modelling Cloud Protection with Virtualization Mechanisms]. Vestnik Moskovskogo Aviatsionnogo Instituta, 2010, vol. 16, no. 6, pp. 143-149. (in Russian)