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Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA

This paper summarises the level of knowledge held by educators in the United States on the use of artificial intelligence and machine learning in the classroom. The education industry seems to have reaped little benefits from the AI & ML industry's growth thus far. In any event, the creatio...

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Detalles Bibliográficos
Autores principales: Simhadri, Naga, Swamy, T. N. V. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176308/
https://www.ncbi.nlm.nih.gov/pubmed/37362281
http://dx.doi.org/10.1007/s00500-023-08329-z
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author Simhadri, Naga
Swamy, T. N. V. R.
author_facet Simhadri, Naga
Swamy, T. N. V. R.
author_sort Simhadri, Naga
collection PubMed
description This paper summarises the level of knowledge held by educators in the United States on the use of artificial intelligence and machine learning in the classroom. The education industry seems to have reaped little benefits from the AI & ML industry's growth thus far. In any event, the creation of new ML & AI-based systems is mostly aimed towards areas with higher societal needs, such as medical diagnostics and individual transportation, rather than institutions of higher education. With this analysis, we want to shed some light on the mysterious state of application development in the US education industry. The report was written using a triangulation of research approaches to achieve this objective. First, we surveyed the current state-of-the-art reports from other countries and reviewed the relevant literature on AI & ML applications in the field of education. In the second phase, we analysed, to the extent possible, official documents from the United States education sector that dealt with AI and ML based on fuzzy digitalization initiatives. Third, in order to corroborate and expand upon the impressions received from the relevant literature and the document analysis, 15 guideline-based expert interviews were undertaken. Based on this data, we provide a selection of the AI & ML systems in use in universities and colleges now, analyse the benefits and drawbacks of implementing them, and speculate on their potential future evolution. While it would be a stretch to say that this paper presents a comprehensive overview of the subject, it does provide light on key areas of application and potential future research directions for AI and ML.
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spelling pubmed-101763082023-05-14 Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA Simhadri, Naga Swamy, T. N. V. R. Soft comput Focus This paper summarises the level of knowledge held by educators in the United States on the use of artificial intelligence and machine learning in the classroom. The education industry seems to have reaped little benefits from the AI & ML industry's growth thus far. In any event, the creation of new ML & AI-based systems is mostly aimed towards areas with higher societal needs, such as medical diagnostics and individual transportation, rather than institutions of higher education. With this analysis, we want to shed some light on the mysterious state of application development in the US education industry. The report was written using a triangulation of research approaches to achieve this objective. First, we surveyed the current state-of-the-art reports from other countries and reviewed the relevant literature on AI & ML applications in the field of education. In the second phase, we analysed, to the extent possible, official documents from the United States education sector that dealt with AI and ML based on fuzzy digitalization initiatives. Third, in order to corroborate and expand upon the impressions received from the relevant literature and the document analysis, 15 guideline-based expert interviews were undertaken. Based on this data, we provide a selection of the AI & ML systems in use in universities and colleges now, analyse the benefits and drawbacks of implementing them, and speculate on their potential future evolution. While it would be a stretch to say that this paper presents a comprehensive overview of the subject, it does provide light on key areas of application and potential future research directions for AI and ML. Springer Berlin Heidelberg 2023-05-12 /pmc/articles/PMC10176308/ /pubmed/37362281 http://dx.doi.org/10.1007/s00500-023-08329-z Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Focus
Simhadri, Naga
Swamy, T. N. V. R.
Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title_full Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title_fullStr Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title_full_unstemmed Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title_short Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA
title_sort awareness among teaching on ai and ml applications based on fuzzy in education sector at usa
topic Focus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176308/
https://www.ncbi.nlm.nih.gov/pubmed/37362281
http://dx.doi.org/10.1007/s00500-023-08329-z
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