Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Peleshenko, Tatyana; Lidzhiev, Artem; Shkirya, Daniel; Vinodha, D. Title A name given to the resource Development of an Adaptive Mathematical Education System for Middle Grades Using Machine Learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1616 LNNS;pp.363-373 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-032-04365-8_36" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-04365-8_36</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019504674?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019504674?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Peleshenko T., North Caucasus Federal University, Stavropol, 355017, Russian Federation; Lidzhiev A., North Caucasus Federal University, Stavropol, 355017, Russian Federation; Shkirya D., North Caucasus Federal University, Stavropol, 355017, Russian Federation; Vinodha D., Christ University, Karnataka, Bangalore, 560074, India Description An account of the resource The aim of the study is to improve the study of mathematics topics for middle school children by developing a software implementation of an adaptive educational system using machine learning. During the research, the topic of quadratic equations was chosen as the basis for the research and development of an adaptive system. During the testing of the adaptive system, mistakes were specifically made to simulate the consolidation of knowledge during the educational process and make sure that it works and is able to adapt to the individual level of each student, increasing the level of knowledge gained and contributing to the consolidation of the material. To achieve this goal, Python code was developed in the Jupyter Notebook development environment. Python libraries were also used, in particular the scikit-learn library for implementing machine learning. The presented approach and software implementation can be used both by teachers to check students and track their progress, and by students themselves to assimilate and consolidate the material and knowledge gained in the lessons. The results obtained during the study demonstrate an increase in the effectiveness of adaptive learning methods using machine learning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Subject The topic of the resource Adaptive educational system; Adaptive learning methodology; Individual learning; Logical regression algorithm; Machine learning; Python; Quadratic equations; Scikit-learn library Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-303204364-1; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online