Researchers are exploring various methods to predict student academic performance, including the use of heterogeneous ensemble learning, deep learning, and machine learning techniques. Different frameworks and models are being developed, incorporating factors such as psychological and family factors, stress, and internet of things technology. The approaches aim to provide more accurate predictions and insights into student performance, with some focusing on specific areas like physical education and sports education.