{"version":"1.0","provider_name":"BUM","provider_url":"https:\/\/bum-apeiron.com","author_name":"admin","author_url":"https:\/\/bum-apeiron.com\/index.php\/author\/jita-au-com\/","title":"Personalization of Teaching in E-learning Systems - BUM","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"uQfN3UET33\"><a href=\"https:\/\/bum-apeiron.com\/index.php\/2024\/04\/02\/personalization-of-teaching-in-e-learning-systems\/\">Personalization of Teaching in E-learning Systems<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/bum-apeiron.com\/index.php\/2024\/04\/02\/personalization-of-teaching-in-e-learning-systems\/embed\/#?secret=uQfN3UET33\" width=\"600\" height=\"338\" title=\"&#8220;Personalization of Teaching in E-learning Systems&#8221; &#8212; BUM\" data-secret=\"uQfN3UET33\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! 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Avramovi\u0107 Personalization of Teaching in E-learning Systems Original scientific paper DOI:https:\/\/doi.org\/ 10.7251\/JIT2002120R Download Article PDF Abstract Personalized teaching offers students the opportunity to study independently, with a focus towards fostering anddeveloping their research traits, to intensively develop students\u2019 abilities and competencies. Traditional teaching is a common mode of education through which tutors use the same teaching method, regardless of the differences and complex personalities of students in a single class or group. Such an approach to teaching has the effect of slowing down the progression of talented students on one hand while making it harder for less successful students to follow classes on the other. The consequences of this approach to teaching are a rapid loss of learning motivation and perception of classes and learning as unpleasant obligations. Contemporary e-learning systems offer personalized learning, by tailoring it to the needs and unique traits of each student. Usage of neural networks in data processing for personalized learning will ensure the formation of adequate classes, full understanding, and adoption of the material prescribed by the curriculum, compliance with the general curriculum, and constant insight into the students\u2019 progress. Keywords: personalized learning, e-learning, neural network. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators."}