Pengembangan Sistem Kursus Online Smart Study Club (SSC) Berbasis Adaptif Learning Path Menggunakan Kerangka Kerja Scrum

Abstract

Online course-based learning generally still applies uniform materials and assessments to all students without considering differences in individual abilities. This condition results in a less personalized learning process and has the potential to reduce learning effectiveness. This study aims to develop a web-based online course system that implements an Adaptive Learning Path (ALP) to adjust the material and the difficulty level of questions based on student abilities. The study used a Research and Development (R&D) method with software development based on the Scrum framework, which includes the product backlog, sprint planning, sprint execution, and sprint review stages. The system implements the Item Response Theory (IRT) Rasch Model algorithm with the Maximum Likelihood Estimation (MLE) method to estimate student abilities and determine questions adaptively. The results of the study produced an online course platform equipped with adaptive learning path features, IRT-based automatic quizzes, a leaderboard, and a material management administration panel. Black box testing results showed that all system functions ran well and were valid, while beta testing on 26 users obtained a feasibility level of 86.8%, which is categorized as very feasible. These findings indicate that the developed system is able to support more personalized, adaptive, and effective learning according to the abilities of each student.