A NOVEL STUDY FOR THE USE OF E-LEARNING TOOLS IN TEACHING AND LEARNING

Dedar Ahmed Saber Kafrooshe

Dedar Ahmed Saber Kafrooshe Electrical and Computer Engineering, altinbas university, Istanbul, Turkey

Keywords: Smart system, modernization, electronic learning, SVM, e-learning.

Abstract

This paper, explores AI-based digital education archives. Modernization methodologies and models have been debated, published, and contrasted as learning data expansion has accelerated. Turkey is one of several Western nations that has switched from paper to digital to prepare for online education. We created a Python intelligent system application to refresh long-archived electronic learning resources. It also lays the groundwork for a deep learning-trained digital ecosystem (SVM). The SVM model helps define limited duties. Major archives are developing preservation standards for digital artifacts and artificial intelligence learning (i.e. open access, closed, restricted, proprietary). It was cleaned up and formatted using electronic learning accession, normalization, and transformation. Between 2015 and 2022, most electronic learning was efficiently modernized to digitize it. This is the percentage of major archives that will switch to paperless electronic learning between 2015 and 2022. Since most records in major university repositories were still on paper in 2015, electronic learning was not very modernized. The intelligent system converts paper-based electronic learning to digital format annually and has a 98.68% accuracy rate for all electronic learning. It's expected to finish in 2022. Such an advanced system can greatly improve university electronic learning and understanding its progress and operation.

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