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Voskoglou M., Salem A.B. MACHINE LEARNING TECHNIQUES FOR TEACHING MATHEMATICS
Voskoglou M., Salem A.B. [mvoskoglou@gmail.com]
Graduate Technological Educational Institute of Western Greece, Patras, Greece
Download in PDF: http://fmo-journal.fizmatsspu.sumy.ua/journals/2020-v2-24/2020_2-24-Voskoglou-Salem_FMO.pdf

MACHINE LEARNING TECHNIQUES FOR TEACHING MATHEMATICS

Formulation of the problem. Famous social thinkers of our times are speaking about a forthcoming new industrial revolution that will be characterized by the development of an advanced Internet of things and energy, and by the cyber-physical systems controlled through it. There is no doubt that our students should take full advantage of the potential that the new digital technologies can bring for improving their learning skills.
Materials and methods. This treatise has a review character. The methods of analysis used are based on already reported researches.
Results. The article focuses on the role that the artificial teaching and learning of mathematics could play for education in the forthcoming era of the new industrial revolution Starting with a brief review of the traditional learning theories and methods of teaching mathematics, the article continues by studying the use of computers and of applications of artificial intelligence in mathematics education.
Conclusions. The advantages and disadvantages of artificial with respect to traditional learning are discussed as well as the perspectives for future research on the subject.

Key words: internet of things and energy (IoT & E); learning theories; “5E’s”teaching method; APOS/ACE instructional treatment of mathematics; flipped learning (FL); artificial intelligence (AI); e-learning; machine learning (ML); smart learning system (SLS); ontological engineering; case-based reasoning (CBR); social robots.

ТЕХНІКИ МАШИННОГО НАВЧАННЯ МАТЕМАТИКИ
Майкл Г. Воскоглу
Вищий технологічний освітній інститут Західної Греції, Греція
Абдел-Баді М. Салем
Аін Шамс Університет, Єгипет


Постановка проблеми. Відомі мислителі нашого часу говорять про майбутню нову індустріальну революцію, яка характеризуватиметься розвиненим Інтернетом речей і енергії та керованими через неї кібер-фізичними системами. Немає сумнівів, що наші студенти повинні вміти використовувати потенціал, який нові цифрові технології можуть принести для вдосконалення їх навичок.
Матеріали та методи.
Дана стаття має оглядовий характер. Використовуються методи аналізу існуючих досліджень з даної проблематики.
Результати. У статті приділяється увага ролі машинного навчання та вивчення математики для освіти в майбутній епосі нової промислової революції. Наведено короткий огляд традиційних теорій та методів навчання математики. Досліджено можливості використання комп'ютерів та додатків штучного інтелекту в навчанні математики.

Висновки. У статті обговорюються переваги та недоліки машинного відносно традиційного навчання, а також перспективи подальших досліджень з цього питання.
Ключові слова: інтернет речей та енергії (IoT & E); теорії навчання; метод навчання "5E"; APOS/ACE навчання математики; перевернуте навчання (FL); штучний інтелект (ШІ); електронне навчання; машинне навчання (ML); розумна система навчання (SLS); онтологічна інженерія; міркування на базі прецедентів (ЦБР); соціальні роботи.

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