AI-DRIVEN ASSESSMENT TOOLS: ENHANCING OBJECTIVITY IN INTERNATIONAL EDUCATION SYSTEMS

Abstract

The globalized nature of education demands robust and objective assessment
tools to accurately measure student progress across diverse learning contexts. This
paper explores the potential of AI-driven assessment tools to enhance objectivity in
international education systems. We discuss how AI algorithms can analyze student
data, provide personalized feedback, and create adaptive assessments, reducing
human bias and promoting equitable evaluation. We examine the benefits of AIpowered assessment tools, including increased efficiency, improved accuracy, and the ability to identify learning gaps and provide targeted interventions. However, we
also address the challenges associated with AI-driven assessment, such as data
privacy concerns, algorithmic bias, and the need for human oversight. The paper
concludes by highlighting the importance of responsible AI implementation in
education, ensuring ethical and equitable use of these tools to enhance global
learning and create a more just and effective education system