In an ever-changing educational environment, measuring student attention is crucial. This study compares various artificial intelligence methods to evaluate students’ attention. We carefully assessed these methods and identified key results, highlighting promising approaches to revolutionize measuring student attention. These results have significant implications for optimizing teaching and learning, paving the way for tangible improvements in academic performance. Our rigorous methodology strengthens the credibility of our study, and this research makes a unique contribution to the field of student attention measurement.