DEVELOPMENT AND EVALUATION OF A CROSS-SUBJECT ATTENDANCE PATTERN SYSTEM

Abstract

Student attendance is crucial for academic success and compliance with institutional policies, such as the 80% attendance rule for exam eligibility. However, existing systems often operate in subject silos, making it difficult to identify students whose absenteeism spans multiple courses. This study aimed to develop and evaluate the Cross-Subject Student Attendance Pattern (CSSAP) system, a web-based platform designed to consolidate attendance data across subjects, facilitate collaboration among lecturers, and support timely intervention for at-risk students. The platform was built using PHP for server-side logic and MySQL for database management, creating a dynamic web application accessible through standard browsers. A field test was conducted with 36 participants (30 students, 6 lecturers) to evaluate usability, functionality, and user acceptance via a Likert-scale questionnaire and open-ended feedback. The evaluation revealed strong positive feedback across all measured dimensions. CSSAP addresses a critical gap in academic administration by providing a centralised, collaborative tool for attendance monitoring. Effective monitoring is conceptualised as a three-stage process: recording (initial data collection), reporting (sharing data with stakeholders), and using the data to inform decisions and interventions. The system empowers lecturers to make data-driven, fair decisions regarding student barring and enables early intervention. The CSSAP system serves as a model for other institutions seeking to modernise attendance management and enhance student support mechanisms through accessible web-based solutions.