Analysis of the effects of large-scale online classes on student learning patterns

Large-scale online classes have grown very common in education and are regarded as an efficient way to provide information and infuse the digital world's learning patterns. Instead, the various analysis of video classes leads to a different situation for student learning abilities. Therefore, in this paper, Different Students Learning Patterns (DSLP) have been proposed for evaluating the various stages of large-scale online classes. DSLP is to analyze online observations of video learning, and students concentrate on learning and perceive education. A strong connection is implemented between students in which the video learning experiences a successful performance and the awareness of video impacts on learning. Besides, DSLP helps the student to influence the media and teachers' attendance; Video learning can increase its understanding of the material. The findings often warn us that the careful preparation and integrated incorporation of VL into other course resources are essential. The experimental results suggest that DSLP offers valuable data on the usefulness of video lectures in university teaching and education and online learning layout consequences. The experimental results show the DSLP to enhance student motivation (94.23%), student participation ratio (98.32%), student engagement (95.11%), flexibility (92.17%), prediction (97.18%), high student behavior analysis (96.38%) and performance ratio (94.01%) when compared to other methods.The model also emphasizes ethical compliance through privacy protection, informed consent, and adherence to data protection laws.