Application of Blockchain Technology in Teaching Evaluation in Applied Technology Universities

This paper explores the integration of blockchain technology into the teaching quality evaluation system of universities. A practical teaching quality evaluation index system for applied technology universities is developed, ensuring data authenticity through blockchain’s de-trusting mechanism. To enhance data storage efficiency, the PBFT consensus algorithm is improved and incorporated into a technical architecture adopting an “off-chain storage + on-chain sharing” model. The algorithm scoring formula and improved PBFT consensus algorithm are analyzed to demonstrate their effectiveness. Practical applications in applied technology universities highlight the benefits of blockchain in higher education evaluation. The CBFT-based consensus algorithm achieves average CPU utilization of 13.4% compared to 18.5% in traditional algorithms, while ensuring data transparency and tamper-proofing. Additionally, the algorithm improves transaction throughput and reduces resource consumption, enabling efficient operation of the teaching evaluation system in applied sciences universities.

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Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2024-12-31
DOI
https://doi.org/10.61091/jcmcc123-36
Primary Topic
Medical Research and Treatments
Type
article
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article

Application of Blockchain Technology in Teaching Evaluation in Applied Technology Universities

Hui Rong
Journal of Combinatorial Mathematics and Combinatorial Computing
Medical Research and Treatments
article

Application of Blockchain Technology in Teaching Evaluation in Applied Technology Universities

Hui Rong
article en

Abstract

This paper explores the integration of blockchain technology into the teaching quality evaluation system of universities. A practical teaching quality evaluation index system for applied technology universities is developed, ensuring data authenticity through blockchain’s de-trusting mechanism. To enhance data storage efficiency, the PBFT consensus algorithm is improved and incorporated into a technical architecture adopting an “off-chain storage + on-chain sharing” model. The algorithm scoring formula and improved PBFT consensus algorithm are analyzed to demonstrate their effectiveness. Practical applications in applied technology universities highlight the benefits of blockchain in higher education evaluation. The CBFT-based consensus algorithm achieves average CPU utilization of 13.4% compared to 18.5% in traditional algorithms, while ensuring data transparency and tamper-proofing. Additionally, the algorithm improves transaction throughput and reduces resource consumption, enabling efficient operation of the teaching evaluation system in applied sciences universities.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 123(1)
Decent work and economic growth
Openalex Percentile: Top 53%
Medical Research and Treatments
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Application of Blockchain Technology in Teaching Evaluation in Applied Technology Universities — Hui Rong · Journal of Combinatorial Mathematics and Combinatorial Computing (2024) | TGRS Research Map | TGRS