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A systematic study on blockchain technology in education: initiatives, products, applications, benefits, challenges and research direction

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Abstract

Blockchain facilitates the education sector from its unique bundles of characteristics, like decentralization, immutability, reliability, transparency, traceability, security, and integrity. These characteristics improve the ecosystem’s accountability, collaboration, credibility, identification, transparency, and trustability. Despite these attractive features and benefits, blockchain technology in education still needs to overcome many challenges that require consistent effort. This paper systematically studies leading blockchain proposals in the education sector. Our study mainly focuses on four categories: (i) Blockchain-based initiatives, (ii) Existing blockchain-based products/solutions, (iii) Applications/Use cases, benefits and challenges in the adoption of blockchain, and (iv) Future research direction in the education sector. We categorize the distinct challenges based on the Technology-Organization-Environment (TOE) framework. This article covers research articles published in eight well-known scientific databases between 2017 and the first quarter of 2023. We screen the articles with the help of the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) approach. This article also explores other educational areas that could benefit from blockchain due to its potential and attractive features.

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The authors confirm contribution to the paper as follows: PR Literature search and study, Literature analysis, Draft manuscript preparation. RKS Literature analysis, Draft manuscript preparation, Critically revised the work, Supervised the work. SK Supervised the work. All authors reviewed the paper and approved the final version of the manuscript.

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Correspondence to Prity Rani.

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Rani, P., Sachan, R.K. & Kukreja, S. A systematic study on blockchain technology in education: initiatives, products, applications, benefits, challenges and research direction. Computing 106, 405–447 (2024). https://doi.org/10.1007/s00607-023-01228-z

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