TY - GEN
T1 - The Model of Personalized Machine Learning to Enhance Students’ Achievements
AU - Rusdi, Mikail Rifqi
AU - Enrico, T. S.Gregorio
AU - Salomo, Austin Ordell
AU - Gaol, Ford Lumban
AU - Matsuo, Tokuro
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
PY - 2023
Y1 - 2023
N2 - Global technological improvements are accelerating and influencing numerous industries, including education. Using machine learning, technological innovations can be utilized in the education industry. Machine learning is a subset of artificial intelligence (AI) that enables computers or teaching machines to make intel-ligent decisions by learning from all past data. The framework for machine learning involves acquiring and retaining a large quantity of data and translating it into orga-nized knowledge. AI advancements enable educators to acquire a deeper knowledge of their students’ learning progression. Using Personalized Machine Learning can increase the efficiency of student learning by analyzing their performance in real time and modifying teaching techniques and the curriculum based on this information. It helps to have a tailored approach that adapts to the individual in order to provide a better education.
AB - Global technological improvements are accelerating and influencing numerous industries, including education. Using machine learning, technological innovations can be utilized in the education industry. Machine learning is a subset of artificial intelligence (AI) that enables computers or teaching machines to make intel-ligent decisions by learning from all past data. The framework for machine learning involves acquiring and retaining a large quantity of data and translating it into orga-nized knowledge. AI advancements enable educators to acquire a deeper knowledge of their students’ learning progression. Using Personalized Machine Learning can increase the efficiency of student learning by analyzing their performance in real time and modifying teaching techniques and the curriculum based on this information. It helps to have a tailored approach that adapts to the individual in order to provide a better education.
KW - Artificial intelligence education
KW - Machine learning
KW - Personalized machine learning
UR - https://www.scopus.com/pages/publications/85166930641
UR - https://www.scopus.com/pages/publications/85166930641#tab=citedBy
U2 - 10.1007/978-981-99-1726-6_54
DO - 10.1007/978-981-99-1726-6_54
M3 - Conference contribution
AN - SCOPUS:85166930641
SN - 9789819917259
T3 - Lecture Notes in Networks and Systems
SP - 701
EP - 712
BT - Intelligent Sustainable Systems - Proceedings of ICISS 2023
A2 - Raj, Jennifer S.
A2 - Perikos, Isidoros
A2 - Balas, Valentina Emilia
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Intelligent Sustainable Systems, ICISS 2023
Y2 - 3 February 2023 through 4 February 2023
ER -