Intelligent Automation of Student Performance Assessment based on Cloud Services

• Main Authors: Xinyu Cai, Natalya Garnova, Alla Filippova, Sergey Glushkov
• Format: Article
• Language: English
• Published: Kassel University Press 2021-01-01
• Series: International Journal of Emerging Technologies in Learning (iJET)
• Subjects: efficiency improvement; information technologies; innovative approaches; power bi; process automation; student performance.
• Online Access: https://online-journals.org/index.php/i-jet/article/view/18827

The purpose of the study is to analyze the modern approach to the student performance assessment system and propose options for its improvement by automating the student result processing system. An experiment to analyze the implementation of an automated student result processing system based on the Power BI service developed by Microsoft and compare the results of the control and experimental groups was conducted at Sechenov University and the Capital University of Economics and Business. In total, 12 departments took part in the experiment (there were 6 departments that used the Power BI service and 6 departments that relied on the electronic university journal). The group that worked with Microsoft Power BI received visual results of student performance, which graphically displayed the dynamics. In turn, the group that created analytics with the help of the electronic university journal could not see most indicators of the student performance dynamics; in addition, it took 6 times more time to create such incomplete analytics compared to the analysis performed in the Power BI service. The practice of other educational institutions and organizations has shown that automation tools are being actively implemented at universities; however, the experience of using Microsoft Power BI in the educational environment is quite limited due to its recent introduction.