Final answer:
Using big data analytics within an educational context can help teachers identify and assist struggling students by analyzing online engagement and performance data, reminiscent of predictive analytics used by streaming platforms.
Step-by-step explanation:
One approach that could be utilized with big data to provide an early warning system for teachers when a student may need help with their studies involves analyzing students' online behavior and performance. By collecting and examining data such as login frequency, time spent on educational resources, quiz or test scores, and assignment submission patterns, teachers can identify students who may be struggling. This approach mirrors the predictive analytics used by platforms that leverage user viewing habits to anticipate future behavior.By applying data analytics to students' interactions with class materials and online resources, educators can gain insights into a student's engagement and understanding. For example, if a student consistently spends less time on assignments or logs in less frequently than peers, it could suggest a need for additional support. Similarly, if a student's performance on web-based sample quizzes indicates a lack of understanding of certain concepts, teachers can be alerted and intervene to provide targeted assistance.In essence, the educational application of big data allows for a proactive approach to education, helping teachers address learning challenges before they become more significant obstacles to a student's success.