A visualized analysis on student performance by using cloud business intelligence

• Main Author: Cheah, Cheng Qian
• Format: Final Year Project / Dissertation / Thesis
• Published: 2022
• Subjects: T Technology (General)
• Online Access: http://eprints.utar.edu.my/4768/1/fyp_IB_2022_CCQ.pdf; http://eprints.utar.edu.my/4768/

During in this state of global pandemic, it is claimed that there is a rise in trend of poor academic performance among student in certain courses or other specific skills. In this matter, due to this uprising yet concerning issue, it is crucial that the deteriorations of students’ academic performance seek a proper solution. Previous research has primarily relied on the traditional and simple method to analyze students’ performance. However, the results and outcomes are not too accurate due to lack of limited data as well as analysis of students’ CLO performance. Therefore, possible factors have examined to have certain degree of relevance in affecting students' performance in certain skills or courses. The aim of this project is to gain deeper understanding and insights to find out which skills or courses where most students can’t perform well and to propose a solution into solving the issue by implementing analysis tools using software tools like Python and MS Power BI. Hence, a comparison of business intelligence tools will be carried out to choose an appropriate BI tool to conduct the analysis due to vast amount of software which available in the IT market. Next, a simple prototype of a system is developed to conduct the analysis alongside a business intelligence tool to graphically display and visualize the analysis results along with graphs on the existing dashboard. To analyze students’ performance, a sample data of students’ results is created to check its CLO through specific and measurable statements in which defines students’ knowledge, skills, and attitudes by demonstrating by the completion of a course. Cognitive, Practical and Affective acts as an indicator to see which student did not perform well in which components in a course and indicates what a student should understand and be able to do after learning. The dashboards developed will be used as a module to analyze students’ performance. After analyzing the findings through graphical objects, formulations and recommendations, the results and outcomes of the data analysis are shown and presented and then described based on the finding. Recommendations to overcome the issue is proposed and conclusions are drawn for future research opportunities as well as data collection. The results of this project will help us gain a better insight and understanding on the academic performance of students as well as knowing which area of weaknesses are they into so that students in higher education could be able to have a huge leap in academic performance.