Abstract: For maintaining sustainable economy, the government of Malaysia is working towards improvising the standards of education in higher education institutes. According to reports, around 32% of enrolled students in Public Universities of Malaysia are unable to graduate on time due to unknown reasons. To ensure more students graduate on time with high quality of education, continuous monitoring of the student is essential. Continual tracking will allow the student as well as the educator to analyze the weak performer at an early stage. Tracking the student performance manually is challenging but with the advancements in information technology, keeping a track of student performance has been relatively easier. Therefore, the fundamental aim of this paper is to present a novel blockchain framework for record keeping and student performance tracking. We name this framework BloSPer (Blockchain Student Performance Tracking System). BloSPer has an edge over the existing systems as current systems face problems of single point of failure and unreliable data. The proposed framework will enable the students and educators to track the performance of the students in a more convenient and transparent manner. Due to this, it will be simpler for them to analyze the reasons of a students’ poor performance. Moreover, the data gathered through the system will be more reliable and worthy for data analytics because of tamper resistance provided through blockchain. This will result in much knowledgeable decisions by the institutions regarding improving the performance of each individual candidate.

Aisha Zahid Junejo, Anton Dziatkovskii, Manzoor Ahmed Hashmani, Uladzimir Hryneuski and Ekaterina Ovechkina, “Blockchain based Framework for Efficient Student Performance Tracking (BloSPer)” International Journal of Advanced Computer Science and Applications(IJACSA), 13(11), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131105

@article{Junejo2022,
title = {Blockchain based Framework for Efficient Student Performance Tracking (BloSPer)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131105},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131105},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Aisha Zahid Junejo and Anton Dziatkovskii and Manzoor Ahmed Hashmani and Uladzimir Hryneuski and Ekaterina Ovechkina}
}