How can AI help in identifying at-risk students?

The option highlighting the role of AI in analyzing academic performance and engagement metrics to flag students needing support is correct because it underscores the practical application of AI in educational settings. AI can process large volumes of data, including grades, attendance records, and participation levels in various activities. By utilizing algorithms that identify patterns and trends, AI can detect students who may be struggling or disengaged, even before they explicitly seek help.

This approach allows educators to intervene early, offering targeted support to those who need it. It enhances personalized learning experiences, where interventions can be tailored based on individual data. Rather than treating all students uniformly, AI emphasizes the importance of understanding each student's unique situation to foster better academic outcomes.

The other options do not align with the context of AI's supportive role in education. Ensuring all students receive equal grades would overlook the diversity of student performance and needs. Decreasing focus on individual student performance contradicts the goal of personalized education, which aims to enhance outcomes based on individual data. Standardizing assessments may not effectively address the unique challenges faced by at-risk students. Thus, the use of AI to analyze performance and engagement is vital for timely interventions and support.