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Dr. Deepika Chatterjee is an Assistant Professor in the Department of Education at The ICFAI University, Raipur, Chhattisgarh, India. Her academic interests include education and the application of emerging technologies in teaching and learning. She contributes to the exploration of Agentic AI for student performance, engagement, and academic risk assessment.
Student achievement, involvement, and educational advancement are affected by several academic, behavioural, cognitive, and situational elements. Traditional educational analytics typically depend on past grades, attendance records, evaluations, and data from learning management systems to forecast student performance. Nonetheless, these methodologies frequently yield discrete forecasts without ongoing synchronisation of intervention, elucidation, and tailored educational assistance. Agentic Artificial Intelligence (Agentic AI) provides a more flexible structure wherein intelligent agents can observe learning behaviours, evaluate educational trends, anticipate performance and academic hazards, deduce potential influencing elements, and suggest tailored solutions. This section explores Agentic AI for forecasting student performance, analysing engagement, identifying early academic risks, facilitating personalised learning, providing assessment assistance, and supporting academic decision-makingThe chapter additionally discusses explainability, equity, privacy, cybersecurity, ambiguity, human-in-the-loop decision-making, and the ethical application of student analytics. Evaluation methodologies and prospective trajectories concerning multimodal learning analytics, knowledge graphs, federated learning, digital learning twins, and autonomous educational agents are delineated.