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Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education

Artificial intelligence is an emerging technology that revolutionizes human lives. Despite the fact that this technology is used in higher education, many professors are unaware of it. In this current scenario, there is a huge need to arise, implement information bridge technology, and enhance commu...

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Autores principales: Hemachandran, K., Verma, Priti, Pareek, Purvi, Arora, Nidhi, Rajesh Kumar, Korupalli V., Ahanger, Tariq Ahamed, Pise, Anil Audumbar, Ratna, Rajnish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110123/
https://www.ncbi.nlm.nih.gov/pubmed/35586099
http://dx.doi.org/10.1155/2022/1410448
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author Hemachandran, K.
Verma, Priti
Pareek, Purvi
Arora, Nidhi
Rajesh Kumar, Korupalli V.
Ahanger, Tariq Ahamed
Pise, Anil Audumbar
Ratna, Rajnish
author_facet Hemachandran, K.
Verma, Priti
Pareek, Purvi
Arora, Nidhi
Rajesh Kumar, Korupalli V.
Ahanger, Tariq Ahamed
Pise, Anil Audumbar
Ratna, Rajnish
author_sort Hemachandran, K.
collection PubMed
description Artificial intelligence is an emerging technology that revolutionizes human lives. Despite the fact that this technology is used in higher education, many professors are unaware of it. In this current scenario, there is a huge need to arise, implement information bridge technology, and enhance communication in the classroom. Through this paper, the authors try to predict the future of higher education with the help of artificial intelligence. This research article throws light on the current education system the problems faced by the subject faculties, students, changing government rules, and regulations in the educational sector. Various arguments and challenges on the implementation of artificial intelligence are prevailing in the educational sector. In this concern, we have built a use case model by using a student assessment data of our students and then built a synthesized using generative adversarial network (GAN). The dataset analyzed, visualized, and fed to different machine learning algorithms such as logistic Regression (LR), linear discriminant analysis (LDA), K-nearest neighbors (KNN), classification and regression trees (CART), naive Bayes (NB), support vector machines (SVM), and finally random forest (RF) algorithm and achieved a maximum accuracy of 58%. This article aims to bridge the gap between human lecturers and the machine. We are also concerned about the psychological emotions of the faculty and the students when artificial intelligence takes control.
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spelling pubmed-91101232022-05-17 Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education Hemachandran, K. Verma, Priti Pareek, Purvi Arora, Nidhi Rajesh Kumar, Korupalli V. Ahanger, Tariq Ahamed Pise, Anil Audumbar Ratna, Rajnish Comput Intell Neurosci Research Article Artificial intelligence is an emerging technology that revolutionizes human lives. Despite the fact that this technology is used in higher education, many professors are unaware of it. In this current scenario, there is a huge need to arise, implement information bridge technology, and enhance communication in the classroom. Through this paper, the authors try to predict the future of higher education with the help of artificial intelligence. This research article throws light on the current education system the problems faced by the subject faculties, students, changing government rules, and regulations in the educational sector. Various arguments and challenges on the implementation of artificial intelligence are prevailing in the educational sector. In this concern, we have built a use case model by using a student assessment data of our students and then built a synthesized using generative adversarial network (GAN). The dataset analyzed, visualized, and fed to different machine learning algorithms such as logistic Regression (LR), linear discriminant analysis (LDA), K-nearest neighbors (KNN), classification and regression trees (CART), naive Bayes (NB), support vector machines (SVM), and finally random forest (RF) algorithm and achieved a maximum accuracy of 58%. This article aims to bridge the gap between human lecturers and the machine. We are also concerned about the psychological emotions of the faculty and the students when artificial intelligence takes control. Hindawi 2022-05-09 /pmc/articles/PMC9110123/ /pubmed/35586099 http://dx.doi.org/10.1155/2022/1410448 Text en Copyright © 2022 K. Hemachandran et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hemachandran, K.
Verma, Priti
Pareek, Purvi
Arora, Nidhi
Rajesh Kumar, Korupalli V.
Ahanger, Tariq Ahamed
Pise, Anil Audumbar
Ratna, Rajnish
Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title_full Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title_fullStr Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title_full_unstemmed Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title_short Artificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
title_sort artificial intelligence: a universal virtual tool to augment tutoring in higher education
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110123/
https://www.ncbi.nlm.nih.gov/pubmed/35586099
http://dx.doi.org/10.1155/2022/1410448
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