Predictive Analytics in Education: Early Intervention and Proactive Support With Gen AI Cloud

Predictive Analytics in Education: Early Intervention and Proactive Support With Gen AI Cloud

Praveen Kumar Maroju (Clientserver Technology Solutions, USA) and Venu Madhav Aragani (Eliassen Group, USA)
DOI: 10.4018/979-8-3693-7723-9.ch019
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Abstract

Predictive analytics, empowered by generative AI and cloud technologies, has the potential to revolutionize educational practices by facilitating early intervention and proactive support for students. This chapter explores the integration of predictive analytics in educational settings, focusing on how data-driven insights can identify at-risk students and tailor interventions to their specific needs. By leveraging generative AI algorithms, educators can analyze vast amounts of data, including academic performance, engagement levels, and socio-emotional factors, to predict potential challenges before they escalate. The chapter highlights case studies that demonstrate successful implementations of predictive analytics in schools and universities, showcasing improved student outcomes, enhanced engagement, and more personalized learning experiences. Additionally, it discusses the ethical considerations and challenges associated with data privacy and bias in AI systems.
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