A web-based information system for optimizing a student's academic performance at the university
View/ Open
Date
2023-07-11Author
Namubiru, Winnie
Nambalirwa, Resty
Kananura, Malcolm Mwine
Lutaaya, Isaac Ray
Metadata
Show full item recordAbstract
n this study the researchers developed a web-based information system for optimizing academic performance at the university level with the use of artificial intelligence. The core reason for developing the web-based information system was to address the high rate of dropouts in higher education institutions by providing personalized academic support. The study's findings enable the utilization of artificial intelligence techniques to optimize academic performance by providing personalized support and feedback to students, fostering student engagement and academic success. The study used both qualitative and quantitative approaches and data was collected using interviews and questionnaires data collection methods and also tools like interview guides.In objective one we reviewed existing systems related to optimizing academic performance and these included; Chegg, Tutor me, Course hero, Mystudylife, Quizlet, Cousera. Their findings were to enhance the implementation of a web based system. In objective two the system was designed using various diagrams which included data flow diagrams, entity relationship diagrams, flow charts, use case diagrams, class diagrams, activity diagrams, sequence diagrams, collaboration diagrams, and state chart diagrams. In objective three the system was implemented using Python and Django framework employed for backend development, JavaScript (React.js) for frontend development and Generative Pre-trained Transformer-3 (GPT-3) API for natural language processing. In objective four the developed system was rigorously tested and validated, demonstrating its effectiveness as a viable solution for optimizing academic performance. The study's findings facilitated seamless student interaction with the system, allowing personalized support and information exchange.By leveraging web technology, and natural language processing, the system aims to optimize academic performance and enhance student engagement and motivation. The system's potential to bridge gaps in the current academic support services offers a promising solution to improve retention rates and academic outcomes at the university level.