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Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector

Although the education sector is improving more quickly than ever with the help of advancing technologies, there are still many areas yet to be discovered, and there will always be room for further enhancements. Two of the most disruptive technologies, machine learning (ML) and blockchain, have help...

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Autores principales: Shah, Dhruvil, Patel, Devarsh, Adesara, Jainish, Hingu, Pruthvi, Shah, Manan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215023/
https://www.ncbi.nlm.nih.gov/pubmed/34151397
http://dx.doi.org/10.1186/s42492-021-00084-y
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author Shah, Dhruvil
Patel, Devarsh
Adesara, Jainish
Hingu, Pruthvi
Shah, Manan
author_facet Shah, Dhruvil
Patel, Devarsh
Adesara, Jainish
Hingu, Pruthvi
Shah, Manan
author_sort Shah, Dhruvil
collection PubMed
description Although the education sector is improving more quickly than ever with the help of advancing technologies, there are still many areas yet to be discovered, and there will always be room for further enhancements. Two of the most disruptive technologies, machine learning (ML) and blockchain, have helped replace conventional approaches used in the education sector with highly technical and effective methods. In this study, a system is proposed that combines these two radiant technologies and helps resolve problems such as forgeries of educational records and fake degrees. The idea here is that if these technologies can be merged and a system can be developed that uses blockchain to store student data and ML to accurately predict the future job roles for students after graduation, the problems of further counterfeiting and insecurity in the student achievements can be avoided. Further, ML models will be used to train and predict valid data. This system will provide the university with an official decentralized database of student records who have graduated from there. In addition, this system provides employers with a platform where the educational records of the employees can be verified. Students can share their educational information in their e-portfolios on platforms such as LinkedIn, which is a platform for managing professional profiles. This allows students, companies, and other industries to find approval for student data more easily.
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spelling pubmed-82150232021-07-01 Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector Shah, Dhruvil Patel, Devarsh Adesara, Jainish Hingu, Pruthvi Shah, Manan Vis Comput Ind Biomed Art Original Article Although the education sector is improving more quickly than ever with the help of advancing technologies, there are still many areas yet to be discovered, and there will always be room for further enhancements. Two of the most disruptive technologies, machine learning (ML) and blockchain, have helped replace conventional approaches used in the education sector with highly technical and effective methods. In this study, a system is proposed that combines these two radiant technologies and helps resolve problems such as forgeries of educational records and fake degrees. The idea here is that if these technologies can be merged and a system can be developed that uses blockchain to store student data and ML to accurately predict the future job roles for students after graduation, the problems of further counterfeiting and insecurity in the student achievements can be avoided. Further, ML models will be used to train and predict valid data. This system will provide the university with an official decentralized database of student records who have graduated from there. In addition, this system provides employers with a platform where the educational records of the employees can be verified. Students can share their educational information in their e-portfolios on platforms such as LinkedIn, which is a platform for managing professional profiles. This allows students, companies, and other industries to find approval for student data more easily. Springer Singapore 2021-06-21 /pmc/articles/PMC8215023/ /pubmed/34151397 http://dx.doi.org/10.1186/s42492-021-00084-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Shah, Dhruvil
Patel, Devarsh
Adesara, Jainish
Hingu, Pruthvi
Shah, Manan
Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title_full Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title_fullStr Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title_full_unstemmed Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title_short Integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
title_sort integrating machine learning and blockchain to develop a system to veto the forgeries and provide efficient results in education sector
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215023/
https://www.ncbi.nlm.nih.gov/pubmed/34151397
http://dx.doi.org/10.1186/s42492-021-00084-y
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