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This article is cited in 1 scientific paper (total in 1 paper)
Programming & Computer Software
Software set of intellectual support and security of LMS MAI CLASS.NET
A. V. Naumov, G. A. Mkhitaryan, A. A. Rybalko Moscow Aviation Institute, Moscow, Russian Federation
Abstract:
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.
Keywords:
learning management system; LMS; e-learning; statistical analysis; adaptive characteristics; system security container technologies.
Received: 01.04.2016
Citation:
A. V. Naumov, G. A. Mkhitaryan, A. A. Rybalko, “Software set of intellectual support and security of LMS MAI CLASS.NET”, Vestnik YuUrGU. Ser. Mat. Model. Progr., 9:4 (2016), 129–140
Linking options:
https://www.mathnet.ru/eng/vyuru350 https://www.mathnet.ru/eng/vyuru/v9/i4/p129
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Abstract page: | 308 | Full-text PDF : | 202 | References: | 44 |
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