Explores the impact of AI-driven assessment and feedback on teaching learning process at secondary level

Abstract

The assessment management system founded on AI technology provides educational feedback to secondary educational facilities. AI technology research in education expands steadily because teaching institutions rush to implement this technology to create new methods for instruction and better student outcomes. AI evaluation systems make assessment quality better because they function as human evaluators to give quick results and customized educational help for students. A combination of methods is used to evaluate secondary school AI-based assessment systems where both faculty adaptation and student involvement and academic performance receive analysis. The application of AI to produce feedback strengthens learning efficiency and enhances student motivation because teachers obtain specific gap evaluation results. The paper identifies student information confidentiality challenges alongside barriers to complete AI advantages because of technical dependency and personnel training requirements. The delivery of data-driven educational practices with personalized learning becomes feasible through AI assessment platforms but implementation requires suitable academic goals and moral frameworks according to research findings.