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

Visual Computing for Industry, Biomedicine, and Art

Manan Shah¹  Pruthvi Hingu²  Dhruvil Shah²  Jainish Adesara²  Devarsh Patel² 

[1] Department of Chemical Engineering, School of Technology, Pandit Deendayal Energy University, 382426, Gandhinagar, Gujarat, India;Department of Computer Engineering, Vishwakarma Government Engineering College, 382424, Ahmedabad, Gujarat, India;

关键词: Machine learning;    Blockchain;    Education;   

DOI  :  10.1186/s42492-021-00084-y

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY