Students Performance Monitoring and Customized Recommendation Prediction in Learning Education using Deep Learning

Abstract

This paper is focused on the development of a student academic result alert system using Short Service Message (SMS). The motivation behind the work was borne out of the numerous problems that students encounter before seeing their results. The issue of checking examination results through notice boards in anxiety has been a challenge from time immemorial. In some cases where results are posted on websites, students will have to pay for internet services to check their grades. Similarly, the privacy that should be upheld with respect to results publishing is not through public display. With these problems in mind, the authors developed a system to deliver students’ results and grades through SMS using a dedicated Application Programming Interface (API). The factfinding methods employed in the work were both primary and secondary methods. Primary method involved the use of questionnaire and observation of documents, while we deployed Object Oriented Analysis and Design Methodology (OOADM) as the design methodology. The software tools used are HTML (Hyper Text Markup Language), PHP (Hypertext PreProcessor) for the front-end and MYSQL for the database solution. The software developed is a highly interactive and has the capability of preventing unauthorized access or mutilation of students’ results, thus maintaining data integrity. It also sends student’s results directly to their phones and that of their sponsors.