An Analytical Study on the Efficacy of Blockchain Frameworks for Student Grievance Management

Student grievance redressal is an essential indicator of institutional effectiveness and education quality, that ensures a conducive academic environment. Every educational institute provides a 24 × 7 web or mobile platform for students to register their grievances. However, these centralized solutions often lack transparency, exhibit potential biases, and also raise security and privacy concerns that lead to student reluctance to use them. A blockchain-based grievance redressal system can address these issues by providing transparency, immutability, privacy, accountability, and auditability. However, selecting the most suitable blockchain framework is challenging and a tedious task. So, we analyzed the existing studies on performance analysis of blockchain frameworks and existing studies on grievance redressal. The finding from the reviewed studies indicates that 81% of the studies diverged towards Hyperledger fabric and Hyperledger fabric outperforms other frameworks in performance based on key parameters such as transactional throughput and latency. The consensus mechanism selection also significantly impacts the performance of a blockchain framework. RAFT is more efficient than the Kafka and solo consensus mechanism for Hyperledger fabric, in both low and high transaction volumes for read and write operations at various transfer rates. Hyperledger fabric achieves a 94.6% success rate in multiple operations with RAFT consensus as compared to 72.7% with Kafka. The success rate of Hyperledger fabric is reached to 96%, 98.4%, and 96.6% at 25tps, 50tps, and 100tps respectively for write operations whereas during the read operations, it is reached to 99.6. It is also found that the success rate is increased to 99.12% in dual channel network for write operation at varying transfer rates. This study suggests that Hyperledger Fabric is more effective for implementing a blockchain-based student grievance redressal system.