Data Analytics in Economics Education: Leveraging AI and Machine Learning for Interpreting Economic Trends

The paper explores the integration of data analytics, AI, and machine learning in economics education. It highlights the importance of equipping students with data literacy and analytical skills to interpret complex economic data and apply these insights to real-world challenges. The integration of data analytics enhances students’ understanding of economic trends, policy evaluation, and investment decision-making. This paper reviews teaching methods and practical applications of AI-powered tools in curriculum development, focusing on enhancing student outcomes, workforce readiness, and ethical considerations in data usage while also highlighting the potential of large datasets for economic forecasting. The study emphasizes the importance of data analytics education in enhancing conceptual understanding, engagement, and technical skills, particularly in today’s economic landscape. It emphasizes the ethical aspects of data use, data privacy, fairness, and responsible interpretation, and the need for innovative educational practices. The paper urges educators, institutions, and policymakers to prioritize data analytics in economics education, promoting interdisciplinary collaboration and industry partnerships to prepare students for a data-centric economy and contribute to economic policy and decision-making.