Data Visualization of Student Academic Performance Analysis

Abstract

Understanding and enhancing student academic performance has become increasingly crucial, yet educators often face data overload, making identifying and prioritizing factors influencing student performance difficult. This study seeks to create a comprehensive system for visualizing and analysing student academic performance. The research follows the waterfall model, with clearly defined phases to ensure an organized and complete development process. The study's main objectives include determining the requirements and techniques to analyse student academic performance and developing and designing a data visualization dashboard using Microsoft Power BI. The final phase consists of evaluating of the student performance dashboard using the Technology Acceptance Model (TAM). A total of 35 respondents was randomly chosen for evaluation and hands-on sessions. The dimensions encompassed Perceived Ease of Use, Perceived Usefulness, Attitude towards Using, and Behavioural Intention. The Attitude of Using received the highest mean score of 4.39, closely followed by Behavioural Intention with a score of 4.38. The results indicate that the participants have a high level of satisfaction with using the dashboard, considering it advantageous and indicating a desire for future implementation. Finally, the project exhibits potential for further advancement, encompassing predictive analytics and tailored learning recommendations, aiming to provide even more precise and actionable insights into student performance.