Analysis of Fusion of Machine Learning Tools in Education

Anita Venugopal^1,*, Mukesh Madanan²,Thangadurai kadarkarai³

¹Dhofar University, Oman

²Dhofar University, Oman

³Dhofar University, Oman

Emails: anita@du.edu.om;  mukesh@du.edu.om;  tkadarkarai@du.edu.om

Abstract

In this modern world, artificial intelligence has revolutionized human life in multiple ways. Like other fields, education industry is also transforming with the influence of AI with its smart learning platform and automation of tasks. The introduction of fusion of machine learning tools (FMLT) in the field of education helps to predict learning outcomes and identify challenges in learning. The objective of this paper is to study the fusion of application of machine learning tools in education. This paper highlights the role of data driven FMLT in teaching and learning and also analyzes students and teachers’ experiences as well as challenges faced during the implementation of FMLT system. This article discusses various machine learning tools that can be fused into academics. The experiment is conducted on students at graduate level and the results reveal an increase of 88% in terms of learning efficiency for the proposed FMLT system compared to traditional methods, which reflects high positive impact of the contributions of FMLT in academics. Results of the findings also reveal that FMLT applications facilitate thinking, creativity, class engagement and quality teaching inside and outside classrooms. The feedback findings express mixed attitudes concerning the use of machine learning tools in classrooms.

Keywords: Fusion machine learning; Artificial intelligence; Education; Teaching and learning.