Jay-Ar G. Balauag
ABSTRACT
This study aimed to assess the effectiveness of a licensing examination readiness system for professional teachers, incorporating predictive analytics and decision support, in helping prospective educators prepare for the licensing examination. The study employed descriptive and developmental design methods, integrating qualitative and quantitative techniques to address licensure readiness challenges among teacher education graduates. The research highlights the challenges that teacher education graduates encounter while preparing for the LEPT, focusing on issues such as stress, time management, and resource accessibility. Using a logistic regression model that considers various factors, including study habits, demographic characteristics, and academic performance, the system forecasts student readiness. The effectiveness of the model was evaluated through a systematic approach comprising feature engineering, data preprocessing, model training, and performance evaluation. For students identified as not ready, the system includes a decision support mechanism that provides tailored recommendations and targeted interventions. To assess the system’s adherence to ISO/IEC 25010 Software Quality Standards, a comprehensive questionnaire was administered to IT specialists. The findings indicate that the system demonstrates very high compliance with several quality criteria, such as usability, security, maintainability, portability, compatibility, functionality, performance efficiency, and suitability. The system’s ability to meet these requirements highlights its potential for effective deployment in real educational contexts. Based on the study’s findings, the developed method offers a practical solution for addressing the challenges associated with preparing for teacher licensing exams. By providing data-driven insights, tailored suggestions, and targeted interventions, the system can significantly enhance student preparedness and improve the overall success rate of teacher education graduates.
Keywords: Decision support systems, ISO 25010, licensure examination, predictive analytics, teacher education