Khung lý thuyết ứng dụng AI trong dự báo xu hướng lựa chọn ngành học của thí sinh tại Phân hiệu TP. Đà Nẵng

Abstract

This paper proposes a conceptual framework integrating Artificial Intelligence (AI) and Educational Data Mining (EDM) to predict prospective students' major choice trends at university branch campuses in Da Nang City. Grounded in a synthesis of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and Chapman's (1981) college choice model, the study constructs a multidimensional analytical framework incorporating demographic data, digital footprints, and socio-economic variables specific to Central Vietnam. The theoretical findings identify three core groups of input variables influencing major selection decisions while outlining a predictive system architecture utilizing Machine Learning (ML) algorithms. Ultimately, the paper provides a robust theoretical foundation to assist academic institutions and branch campuses in optimizing enrollment strategies and planning educational programs adapted to the evolving local labor market.