Smart Education: Harnessing Machine Learning for Global Talent Forecasting and Educational Innovation in China
Lina Chen, Meidan Yin, Khwaja Mutahir Ahmad, Muhammad Ahtsam Naeem, Sami Ahmed Haider · 2024
This study examines the increasing popularity of international students in China, driven by technological innovations, including the integration of artificial intelligence (AI) in education and targeted scholarship initiatives. The article explores the trans-formative impact of AI on educational quality and learning methodologies during the COVID-19 epidemic, aligning with global trends and enhancing China's appeal as a study destination. This research forecasts future trends in international student enrollment in China by analyzing historical enrollment data by utilizing machine learning-based forecasting models like Long Short-Term Memory (LSTM), Multi-Layer Perceptron (MLP), and Gated Recurrent Unit (GRU). Our investigation provides significant insights into the function of AI in attracting global talent and enhancing the quality of the educational system. Moreover, the results enhance comprehension of how China's educational policies and AI-driven systems will shape the future of international education. The paper is a reference for scholars and policymakers seeking to leverage China's sophisticated AI-enhanced educational methodologies.