Fusion: Practice and Applications

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https://doi.org/10.54216/FPA

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Volume 12 , Issue 2 , PP: 88-97, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

Analysis of Fusion of Machine Learning Tools in Education

Anita Venugopal 1 * , Mukesh Madanan 2 , Thangadurai kadarkarai 3

  • 1 Dhofar University, Oman - (anita@du.edu.om)
  • 2 Dhofar University, Oman - (mukesh@du.edu.om)
  • 3 Dhofar University, Oman - (tkadarkarai@du.edu.om)
  • Doi: https://doi.org/10.54216/FPA.120207

    Received: January 22, 2023 Revised: April 20, 2023 Accepted: June 18, 2023
    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.

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    Cite This Article As :
    Venugopal, Anita. , Madanan, Mukesh. , kadarkarai, Thangadurai. Analysis of Fusion of Machine Learning Tools in Education. Fusion: Practice and Applications, vol. , no. , 2023, pp. 88-97. DOI: https://doi.org/10.54216/FPA.120207
    Venugopal, A. Madanan, M. kadarkarai, T. (2023). Analysis of Fusion of Machine Learning Tools in Education. Fusion: Practice and Applications, (), 88-97. DOI: https://doi.org/10.54216/FPA.120207
    Venugopal, Anita. Madanan, Mukesh. kadarkarai, Thangadurai. Analysis of Fusion of Machine Learning Tools in Education. Fusion: Practice and Applications , no. (2023): 88-97. DOI: https://doi.org/10.54216/FPA.120207
    Venugopal, A. , Madanan, M. , kadarkarai, T. (2023) . Analysis of Fusion of Machine Learning Tools in Education. Fusion: Practice and Applications , () , 88-97 . DOI: https://doi.org/10.54216/FPA.120207
    Venugopal A. , Madanan M. , kadarkarai T. [2023]. Analysis of Fusion of Machine Learning Tools in Education. Fusion: Practice and Applications. (): 88-97. DOI: https://doi.org/10.54216/FPA.120207
    Venugopal, A. Madanan, M. kadarkarai, T. "Analysis of Fusion of Machine Learning Tools in Education," Fusion: Practice and Applications, vol. , no. , pp. 88-97, 2023. DOI: https://doi.org/10.54216/FPA.120207