Hybrid Student Performance Assessment System

The abundance of data in educational databases makes it increasingly difficult to assess students’ performance. After the COVID 19 epidemic, lessons were switched to blend mode, which combines traditional classroom instruction with online learning. There must be a system in place to evaluate students in the current scenario. Therefore, a redesign of the assessment system is necessary. The assessment system needs to considers the blend mode. This research paper proposed HSPAS (Hybrid Student Performance Assessment System) to assess the student performance and make recommendation to development of students learning. This approach contains three phases of assessment. The First one is the Foundational Assessment; second one is comprehensive assessment and third one is ID3 decision tree-based classification algorithm. The three-phase assessment improve the classification efficiency. The proposed approach is compared with the existing approaches. The experimental results show the efficiency of the proposed system.