How does AI use predictive analytics to adjust curricula and support students?

AI uses predictive analytics by applying machine learning to historical performance trends to forecast which students are at risk of falling behind. When such a risk is predicted, AI signals the educator to give that student extra attention, helping identify weaknesses and intervene early. It also continuously analyzes real-time data from assessments, attendance, and performance, prompting curriculum adjustments when needed.

According to the chapter, AI is trained to continuously monitor data collected from student assessments, attendance, and performance in real time. Through continuous data analysis, it alerts educators when the curriculum needs adjustment. For predictive analytics specifically, AI uses machine learning to examine past trends and predict when a student may fall behind. This prediction signals educators to provide special attention to that student, allowing early intervention and necessary curriculum changes before problems worsen. This supports both identifying student weaknesses and making timely adjustments to teaching.