Self-Adaptive Feedback E-Learning Scheme for Elementary Math in Kuwait

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Mathematics is widely recognized as the most important and essential discipline because it serves as the foundation for many notable scientific and technical breakthroughs over the centuries. Students' attitudes toward mathematics can be significantly improved by using computers as a medium of instruction, according to several studies. Artificial Intelligence, and thus Machine Learning, is a critical driving force in the advancement of innovation and growth in a wide range of industries today, with the education sector being no exception in this regard. An Adaptive Feedback E-Learning Scheme for Elementary Math in Kuwait is being developed and implemented to improve the quality of mathematics education for the next generation of elementary school students. The proposed methodology attempts to close the gap between students' Math learning abilities and those of their teachers using Artificial Intelligence and Machine Learning methods. The adaptive Learning approach seeks to create a compelling learning experience that is adapted to the individual needs of each learner in a personalized manner. To determine the strengths and weaknesses of each student who enters the system, the suggested model operates in two modes: Diagnostic Mode and Remediation Mode. Additional rounds between the two modes may be required to address all a student's deficiencies for him or her to achieve an appropriate degree of mastery of the various arithmetic topics. Work on this project is being carried out in collaboration with the Kuwait Foundation for Advancement of Sciences (KFAS), Kuwait University (KU), and the Kuwaiti Ministry of Education (MoE).

Original languageEnglish
Title of host publicationICECIE 2022 - 2022 4th International Conference on Electrical, Control and Instrumentation Engineering, Proceedings
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781665480765
DOIs
StatePublished - 2022
Event4th International Conference on Electrical, Control and Instrumentation Engineering, ICECIE 2022 - Kuala Lumpur, Malaysia
Duration: 26 Nov 2022 → …

Publication series

NameProceedings, International Conference on Electrical, Control and Instrumentation Engineering, ICECIE
Volume2022-November
ISSN (Print)2832-9821
ISSN (Electronic)2832-9848

Conference

Conference4th International Conference on Electrical, Control and Instrumentation Engineering, ICECIE 2022
Country/TerritoryMalaysia
CityKuala Lumpur
Period26/11/22 → …

Keywords

  • Bayesian model
  • e-learning assessment
  • elementary schools
  • feedback authoring
  • feedback personalization
  • Math learning
  • Monte Carlo simulation
  • stochastic gradient descent

Funding Agency

  • Kuwait Foundation for the Advancement of Sciences

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