Adaptive E-Assessment Framework

The important part of the learning process is practice and evaluation. Evaluation is intended to determine students' abilities so that the learning process can be improved according to student needs. Unfortunately, exercises and evaluations that are appropriate to the student's personality are difficult to do traditionally by teachers. In order to make the evaluation process easier and more personal, a system that is able to assist the process of training and evaluating students is needed. The adaptive training system allows the system to provide questions that can increase students' motivation and abilities. In addition, the form of the questions can be in accordance with the circumstances of the students. A methodology based on qualitative research using the Grounded Theory method was applied in this study. The proposed framework consists of several layers, including the User layer, Input Output layer, Model and AI/Machine Learning layers. Input Output can consist of a variety hardware. The model layer can consist of student model and domain model. The AI/Machine Learning layer can consist of item classification modules, student condition monitoring, questions recommendations, student performance evaluations, learning path recommendations, gamification engine, prevention action, questions generator. It is intended that the framework created would satisfy the proper evaluation requirements of each student in order to encourage learning and enhance student abilities. This framework is intended for use in secondary schools.