Review on evaluation techniques for better student learning outcomes using machine learning

The article is devoted to the searching for vulnerabilities in software problem, as well as the possibilities of application of such a promising area in information technology as machine learning. For this purpose, a review of scientific publications in this area from Russian and foreign citation databases is made. A comparative analysis of the review's results was made according to the following criteria: publication year, application field, idea, solved problem of machine learning, degree of realization of its models and methods; for each criterion basic conclusions were drawn. As a result, 7 principles of building a new conceptual system of searching for vulnerabilities in software with the help of machine learning are proposed, the short meaning of which is as follows: program's multilateral study, combination of known methods, the use of machine learning in each method and algorithm of its management, the possibility of correcting the expert's work, storing information in a database and its synchronization with external, advisory nature of the found vulnerabilities; single software application usage. Based on the stated principles, a graphical scheme of such a system has been developed.

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Review on evaluation techniques for better student learning outcomes using machine learning

Cited by 4 publications

References 30 publications

Machine Learning Approaches for Kids’ E-learning Monitoring

Machine Learning Approaches for Kids’ E-learning Monitoring

A model to combine qualitative and quantitative measures in education for better assessment of learning outcomes

Machine Learning vs Software Vulnerability Detection: Applicability Analysis and Conceptual System Synthesis

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